Annotation of imach/src/imach.c, revision 1.361
1.361 ! brouard 1: /* $Id: imach.c,v 1.360 2024/04/30 10:59:22 brouard Exp $
1.126 brouard 2: $State: Exp $
1.360 brouard 3: $Log: imach.c,v $
1.361 ! brouard 4: Revision 1.360 2024/04/30 10:59:22 brouard
! 5: Summary: Version 0.99s4 and estimation of std of e.j/e..
! 6:
1.360 brouard 7: Revision 1.359 2024/04/24 21:21:17 brouard
8: Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes
9:
1.359 brouard 10: Revision 1.6 2024/04/24 21:10:29 brouard
11: Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes
1.358 brouard 12:
1.359 brouard 13: Revision 1.5 2023/10/09 09:10:01 brouard
14: Summary: trying to reconsider
1.357 brouard 15:
1.359 brouard 16: Revision 1.4 2023/06/22 12:50:51 brouard
17: Summary: stil on going
1.357 brouard 18:
1.359 brouard 19: Revision 1.3 2023/06/22 11:28:07 brouard
20: *** empty log message ***
1.356 brouard 21:
1.359 brouard 22: Revision 1.2 2023/06/22 11:22:40 brouard
23: Summary: with svd but not working yet
1.355 brouard 24:
1.354 brouard 25: Revision 1.353 2023/05/08 18:48:22 brouard
26: *** empty log message ***
27:
1.353 brouard 28: Revision 1.352 2023/04/29 10:46:21 brouard
29: *** empty log message ***
30:
1.352 brouard 31: Revision 1.351 2023/04/29 10:43:47 brouard
32: Summary: 099r45
33:
1.351 brouard 34: Revision 1.350 2023/04/24 11:38:06 brouard
35: *** empty log message ***
36:
1.350 brouard 37: Revision 1.349 2023/01/31 09:19:37 brouard
38: Summary: Improvements in models with age*Vn*Vm
39:
1.348 brouard 40: Revision 1.347 2022/09/18 14:36:44 brouard
41: Summary: version 0.99r42
42:
1.347 brouard 43: Revision 1.346 2022/09/16 13:52:36 brouard
44: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
45:
1.346 brouard 46: Revision 1.345 2022/09/16 13:40:11 brouard
47: Summary: Version 0.99r41
48:
49: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
50:
1.345 brouard 51: Revision 1.344 2022/09/14 19:33:30 brouard
52: Summary: version 0.99r40
53:
54: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
55:
1.344 brouard 56: Revision 1.343 2022/09/14 14:22:16 brouard
57: Summary: version 0.99r39
58:
59: * imach.c (Module): Version 0.99r39 with colored dummy covariates
60: (fixed or time varying), using new last columns of
61: ILK_parameter.txt file.
62:
1.343 brouard 63: Revision 1.342 2022/09/11 19:54:09 brouard
64: Summary: 0.99r38
65:
66: * imach.c (Module): Adding timevarying products of any kinds,
67: should work before shifting cotvar from ncovcol+nqv columns in
68: order to have a correspondance between the column of cotvar and
69: the id of column.
70: (Module): Some cleaning and adding covariates in ILK.txt
71:
1.342 brouard 72: Revision 1.341 2022/09/11 07:58:42 brouard
73: Summary: Version 0.99r38
74:
75: After adding change in cotvar.
76:
1.341 brouard 77: Revision 1.340 2022/09/11 07:53:11 brouard
78: Summary: Version imach 0.99r37
79:
80: * imach.c (Module): Adding timevarying products of any kinds,
81: should work before shifting cotvar from ncovcol+nqv columns in
82: order to have a correspondance between the column of cotvar and
83: the id of column.
84:
1.340 brouard 85: Revision 1.339 2022/09/09 17:55:22 brouard
86: Summary: version 0.99r37
87:
88: * imach.c (Module): Many improvements for fixing products of fixed
89: timevarying as well as fixed * fixed, and test with quantitative
90: covariate.
91:
1.339 brouard 92: Revision 1.338 2022/09/04 17:40:33 brouard
93: Summary: 0.99r36
94:
95: * imach.c (Module): Now the easy runs i.e. without result or
96: model=1+age only did not work. The defautl combination should be 1
97: and not 0 because everything hasn't been tranformed yet.
98:
1.338 brouard 99: Revision 1.337 2022/09/02 14:26:02 brouard
100: Summary: version 0.99r35
101:
102: * src/imach.c: Version 0.99r35 because it outputs same results with
103: 1+age+V1+V1*age for females and 1+age for females only
104: (education=1 noweight)
105:
1.337 brouard 106: Revision 1.336 2022/08/31 09:52:36 brouard
107: *** empty log message ***
108:
1.336 brouard 109: Revision 1.335 2022/08/31 08:23:16 brouard
110: Summary: improvements...
111:
1.335 brouard 112: Revision 1.334 2022/08/25 09:08:41 brouard
113: Summary: In progress for quantitative
114:
1.334 brouard 115: Revision 1.333 2022/08/21 09:10:30 brouard
116: * src/imach.c (Module): Version 0.99r33 A lot of changes in
117: reassigning covariates: my first idea was that people will always
118: use the first covariate V1 into the model but in fact they are
119: producing data with many covariates and can use an equation model
120: with some of the covariate; it means that in a model V2+V3 instead
121: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
122: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
123: the equation model is restricted to two variables only (V2, V3)
124: and the combination for V2 should be codtabm(k,1) instead of
125: (codtabm(k,2), and the code should be
126: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
127: made. All of these should be simplified once a day like we did in
128: hpxij() for example by using precov[nres] which is computed in
129: decoderesult for each nres of each resultline. Loop should be done
130: on the equation model globally by distinguishing only product with
131: age (which are changing with age) and no more on type of
132: covariates, single dummies, single covariates.
133:
1.333 brouard 134: Revision 1.332 2022/08/21 09:06:25 brouard
135: Summary: Version 0.99r33
136:
137: * src/imach.c (Module): Version 0.99r33 A lot of changes in
138: reassigning covariates: my first idea was that people will always
139: use the first covariate V1 into the model but in fact they are
140: producing data with many covariates and can use an equation model
141: with some of the covariate; it means that in a model V2+V3 instead
142: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
143: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
144: the equation model is restricted to two variables only (V2, V3)
145: and the combination for V2 should be codtabm(k,1) instead of
146: (codtabm(k,2), and the code should be
147: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
148: made. All of these should be simplified once a day like we did in
149: hpxij() for example by using precov[nres] which is computed in
150: decoderesult for each nres of each resultline. Loop should be done
151: on the equation model globally by distinguishing only product with
152: age (which are changing with age) and no more on type of
153: covariates, single dummies, single covariates.
154:
1.332 brouard 155: Revision 1.331 2022/08/07 05:40:09 brouard
156: *** empty log message ***
157:
1.331 brouard 158: Revision 1.330 2022/08/06 07:18:25 brouard
159: Summary: last 0.99r31
160:
161: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
162:
1.330 brouard 163: Revision 1.329 2022/08/03 17:29:54 brouard
164: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
165:
1.329 brouard 166: Revision 1.328 2022/07/27 17:40:48 brouard
167: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
168:
1.328 brouard 169: Revision 1.327 2022/07/27 14:47:35 brouard
170: Summary: Still a problem for one-step probabilities in case of quantitative variables
171:
1.327 brouard 172: Revision 1.326 2022/07/26 17:33:55 brouard
173: Summary: some test with nres=1
174:
1.326 brouard 175: Revision 1.325 2022/07/25 14:27:23 brouard
176: Summary: r30
177:
178: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
179: coredumped, revealed by Feiuno, thank you.
180:
1.325 brouard 181: Revision 1.324 2022/07/23 17:44:26 brouard
182: *** empty log message ***
183:
1.324 brouard 184: Revision 1.323 2022/07/22 12:30:08 brouard
185: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
186:
1.323 brouard 187: Revision 1.322 2022/07/22 12:27:48 brouard
188: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
189:
1.322 brouard 190: Revision 1.321 2022/07/22 12:04:24 brouard
191: Summary: r28
192:
193: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
194:
1.321 brouard 195: Revision 1.320 2022/06/02 05:10:11 brouard
196: *** empty log message ***
197:
1.320 brouard 198: Revision 1.319 2022/06/02 04:45:11 brouard
199: * imach.c (Module): Adding the Wald tests from the log to the main
200: htm for better display of the maximum likelihood estimators.
201:
1.319 brouard 202: Revision 1.318 2022/05/24 08:10:59 brouard
203: * imach.c (Module): Some attempts to find a bug of wrong estimates
204: of confidencce intervals with product in the equation modelC
205:
1.318 brouard 206: Revision 1.317 2022/05/15 15:06:23 brouard
207: * imach.c (Module): Some minor improvements
208:
1.317 brouard 209: Revision 1.316 2022/05/11 15:11:31 brouard
210: Summary: r27
211:
1.316 brouard 212: Revision 1.315 2022/05/11 15:06:32 brouard
213: *** empty log message ***
214:
1.315 brouard 215: Revision 1.314 2022/04/13 17:43:09 brouard
216: * imach.c (Module): Adding link to text data files
217:
1.314 brouard 218: Revision 1.313 2022/04/11 15:57:42 brouard
219: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
220:
1.313 brouard 221: Revision 1.312 2022/04/05 21:24:39 brouard
222: *** empty log message ***
223:
1.312 brouard 224: Revision 1.311 2022/04/05 21:03:51 brouard
225: Summary: Fixed quantitative covariates
226:
227: Fixed covariates (dummy or quantitative)
228: with missing values have never been allowed but are ERRORS and
229: program quits. Standard deviations of fixed covariates were
230: wrongly computed. Mean and standard deviations of time varying
231: covariates are still not computed.
232:
1.311 brouard 233: Revision 1.310 2022/03/17 08:45:53 brouard
234: Summary: 99r25
235:
236: Improving detection of errors: result lines should be compatible with
237: the model.
238:
1.310 brouard 239: Revision 1.309 2021/05/20 12:39:14 brouard
240: Summary: Version 0.99r24
241:
1.309 brouard 242: Revision 1.308 2021/03/31 13:11:57 brouard
243: Summary: Version 0.99r23
244:
245:
246: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
247:
1.308 brouard 248: Revision 1.307 2021/03/08 18:11:32 brouard
249: Summary: 0.99r22 fixed bug on result:
250:
1.307 brouard 251: Revision 1.306 2021/02/20 15:44:02 brouard
252: Summary: Version 0.99r21
253:
254: * imach.c (Module): Fix bug on quitting after result lines!
255: (Module): Version 0.99r21
256:
1.306 brouard 257: Revision 1.305 2021/02/20 15:28:30 brouard
258: * imach.c (Module): Fix bug on quitting after result lines!
259:
1.305 brouard 260: Revision 1.304 2021/02/12 11:34:20 brouard
261: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
262:
1.304 brouard 263: Revision 1.303 2021/02/11 19:50:15 brouard
264: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
265:
1.303 brouard 266: Revision 1.302 2020/02/22 21:00:05 brouard
267: * (Module): imach.c Update mle=-3 (for computing Life expectancy
268: and life table from the data without any state)
269:
1.302 brouard 270: Revision 1.301 2019/06/04 13:51:20 brouard
271: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
272:
1.301 brouard 273: Revision 1.300 2019/05/22 19:09:45 brouard
274: Summary: version 0.99r19 of May 2019
275:
1.300 brouard 276: Revision 1.299 2019/05/22 18:37:08 brouard
277: Summary: Cleaned 0.99r19
278:
1.299 brouard 279: Revision 1.298 2019/05/22 18:19:56 brouard
280: *** empty log message ***
281:
1.298 brouard 282: Revision 1.297 2019/05/22 17:56:10 brouard
283: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
284:
1.297 brouard 285: Revision 1.296 2019/05/20 13:03:18 brouard
286: Summary: Projection syntax simplified
287:
288:
289: We can now start projections, forward or backward, from the mean date
290: of inteviews up to or down to a number of years of projection:
291: prevforecast=1 yearsfproj=15.3 mobil_average=0
292: or
293: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
294: or
295: prevbackcast=1 yearsbproj=12.3 mobil_average=1
296: or
297: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
298:
1.296 brouard 299: Revision 1.295 2019/05/18 09:52:50 brouard
300: Summary: doxygen tex bug
301:
1.295 brouard 302: Revision 1.294 2019/05/16 14:54:33 brouard
303: Summary: There was some wrong lines added
304:
1.294 brouard 305: Revision 1.293 2019/05/09 15:17:34 brouard
306: *** empty log message ***
307:
1.293 brouard 308: Revision 1.292 2019/05/09 14:17:20 brouard
309: Summary: Some updates
310:
1.292 brouard 311: Revision 1.291 2019/05/09 13:44:18 brouard
312: Summary: Before ncovmax
313:
1.291 brouard 314: Revision 1.290 2019/05/09 13:39:37 brouard
315: Summary: 0.99r18 unlimited number of individuals
316:
317: The number n which was limited to 20,000 cases is now unlimited, from firstobs to lastobs. If the number is too for the virtual memory, probably an error will occur.
318:
1.290 brouard 319: Revision 1.289 2018/12/13 09:16:26 brouard
320: Summary: Bug for young ages (<-30) will be in r17
321:
1.289 brouard 322: Revision 1.288 2018/05/02 20:58:27 brouard
323: Summary: Some bugs fixed
324:
1.288 brouard 325: Revision 1.287 2018/05/01 17:57:25 brouard
326: Summary: Bug fixed by providing frequencies only for non missing covariates
327:
1.287 brouard 328: Revision 1.286 2018/04/27 14:27:04 brouard
329: Summary: some minor bugs
330:
1.286 brouard 331: Revision 1.285 2018/04/21 21:02:16 brouard
332: Summary: Some bugs fixed, valgrind tested
333:
1.285 brouard 334: Revision 1.284 2018/04/20 05:22:13 brouard
335: Summary: Computing mean and stdeviation of fixed quantitative variables
336:
1.284 brouard 337: Revision 1.283 2018/04/19 14:49:16 brouard
338: Summary: Some minor bugs fixed
339:
1.283 brouard 340: Revision 1.282 2018/02/27 22:50:02 brouard
341: *** empty log message ***
342:
1.282 brouard 343: Revision 1.281 2018/02/27 19:25:23 brouard
344: Summary: Adding second argument for quitting
345:
1.281 brouard 346: Revision 1.280 2018/02/21 07:58:13 brouard
347: Summary: 0.99r15
348:
349: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
350:
1.280 brouard 351: Revision 1.279 2017/07/20 13:35:01 brouard
352: Summary: temporary working
353:
1.279 brouard 354: Revision 1.278 2017/07/19 14:09:02 brouard
355: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
356:
1.278 brouard 357: Revision 1.277 2017/07/17 08:53:49 brouard
358: Summary: BOM files can be read now
359:
1.277 brouard 360: Revision 1.276 2017/06/30 15:48:31 brouard
361: Summary: Graphs improvements
362:
1.276 brouard 363: Revision 1.275 2017/06/30 13:39:33 brouard
364: Summary: Saito's color
365:
1.275 brouard 366: Revision 1.274 2017/06/29 09:47:08 brouard
367: Summary: Version 0.99r14
368:
1.274 brouard 369: Revision 1.273 2017/06/27 11:06:02 brouard
370: Summary: More documentation on projections
371:
1.273 brouard 372: Revision 1.272 2017/06/27 10:22:40 brouard
373: Summary: Color of backprojection changed from 6 to 5(yellow)
374:
1.272 brouard 375: Revision 1.271 2017/06/27 10:17:50 brouard
376: Summary: Some bug with rint
377:
1.271 brouard 378: Revision 1.270 2017/05/24 05:45:29 brouard
379: *** empty log message ***
380:
1.270 brouard 381: Revision 1.269 2017/05/23 08:39:25 brouard
382: Summary: Code into subroutine, cleanings
383:
1.269 brouard 384: Revision 1.268 2017/05/18 20:09:32 brouard
385: Summary: backprojection and confidence intervals of backprevalence
386:
1.268 brouard 387: Revision 1.267 2017/05/13 10:25:05 brouard
388: Summary: temporary save for backprojection
389:
1.267 brouard 390: Revision 1.266 2017/05/13 07:26:12 brouard
391: Summary: Version 0.99r13 (improvements and bugs fixed)
392:
1.266 brouard 393: Revision 1.265 2017/04/26 16:22:11 brouard
394: Summary: imach 0.99r13 Some bugs fixed
395:
1.265 brouard 396: Revision 1.264 2017/04/26 06:01:29 brouard
397: Summary: Labels in graphs
398:
1.264 brouard 399: Revision 1.263 2017/04/24 15:23:15 brouard
400: Summary: to save
401:
1.263 brouard 402: Revision 1.262 2017/04/18 16:48:12 brouard
403: *** empty log message ***
404:
1.262 brouard 405: Revision 1.261 2017/04/05 10:14:09 brouard
406: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
407:
1.261 brouard 408: Revision 1.260 2017/04/04 17:46:59 brouard
409: Summary: Gnuplot indexations fixed (humm)
410:
1.260 brouard 411: Revision 1.259 2017/04/04 13:01:16 brouard
412: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
413:
1.259 brouard 414: Revision 1.258 2017/04/03 10:17:47 brouard
415: Summary: Version 0.99r12
416:
417: Some cleanings, conformed with updated documentation.
418:
1.258 brouard 419: Revision 1.257 2017/03/29 16:53:30 brouard
420: Summary: Temp
421:
1.257 brouard 422: Revision 1.256 2017/03/27 05:50:23 brouard
423: Summary: Temporary
424:
1.256 brouard 425: Revision 1.255 2017/03/08 16:02:28 brouard
426: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
427:
1.255 brouard 428: Revision 1.254 2017/03/08 07:13:00 brouard
429: Summary: Fixing data parameter line
430:
1.254 brouard 431: Revision 1.253 2016/12/15 11:59:41 brouard
432: Summary: 0.99 in progress
433:
1.253 brouard 434: Revision 1.252 2016/09/15 21:15:37 brouard
435: *** empty log message ***
436:
1.252 brouard 437: Revision 1.251 2016/09/15 15:01:13 brouard
438: Summary: not working
439:
1.251 brouard 440: Revision 1.250 2016/09/08 16:07:27 brouard
441: Summary: continue
442:
1.250 brouard 443: Revision 1.249 2016/09/07 17:14:18 brouard
444: Summary: Starting values from frequencies
445:
1.249 brouard 446: Revision 1.248 2016/09/07 14:10:18 brouard
447: *** empty log message ***
448:
1.248 brouard 449: Revision 1.247 2016/09/02 11:11:21 brouard
450: *** empty log message ***
451:
1.247 brouard 452: Revision 1.246 2016/09/02 08:49:22 brouard
453: *** empty log message ***
454:
1.246 brouard 455: Revision 1.245 2016/09/02 07:25:01 brouard
456: *** empty log message ***
457:
1.245 brouard 458: Revision 1.244 2016/09/02 07:17:34 brouard
459: *** empty log message ***
460:
1.244 brouard 461: Revision 1.243 2016/09/02 06:45:35 brouard
462: *** empty log message ***
463:
1.243 brouard 464: Revision 1.242 2016/08/30 15:01:20 brouard
465: Summary: Fixing a lots
466:
1.242 brouard 467: Revision 1.241 2016/08/29 17:17:25 brouard
468: Summary: gnuplot problem in Back projection to fix
469:
1.241 brouard 470: Revision 1.240 2016/08/29 07:53:18 brouard
471: Summary: Better
472:
1.240 brouard 473: Revision 1.239 2016/08/26 15:51:03 brouard
474: Summary: Improvement in Powell output in order to copy and paste
475:
476: Author:
477:
1.239 brouard 478: Revision 1.238 2016/08/26 14:23:35 brouard
479: Summary: Starting tests of 0.99
480:
1.238 brouard 481: Revision 1.237 2016/08/26 09:20:19 brouard
482: Summary: to valgrind
483:
1.237 brouard 484: Revision 1.236 2016/08/25 10:50:18 brouard
485: *** empty log message ***
486:
1.236 brouard 487: Revision 1.235 2016/08/25 06:59:23 brouard
488: *** empty log message ***
489:
1.235 brouard 490: Revision 1.234 2016/08/23 16:51:20 brouard
491: *** empty log message ***
492:
1.234 brouard 493: Revision 1.233 2016/08/23 07:40:50 brouard
494: Summary: not working
495:
1.233 brouard 496: Revision 1.232 2016/08/22 14:20:21 brouard
497: Summary: not working
498:
1.232 brouard 499: Revision 1.231 2016/08/22 07:17:15 brouard
500: Summary: not working
501:
1.231 brouard 502: Revision 1.230 2016/08/22 06:55:53 brouard
503: Summary: Not working
504:
1.230 brouard 505: Revision 1.229 2016/07/23 09:45:53 brouard
506: Summary: Completing for func too
507:
1.229 brouard 508: Revision 1.228 2016/07/22 17:45:30 brouard
509: Summary: Fixing some arrays, still debugging
510:
1.227 brouard 511: Revision 1.226 2016/07/12 18:42:34 brouard
512: Summary: temp
513:
1.226 brouard 514: Revision 1.225 2016/07/12 08:40:03 brouard
515: Summary: saving but not running
516:
1.225 brouard 517: Revision 1.224 2016/07/01 13:16:01 brouard
518: Summary: Fixes
519:
1.224 brouard 520: Revision 1.223 2016/02/19 09:23:35 brouard
521: Summary: temporary
522:
1.223 brouard 523: Revision 1.222 2016/02/17 08:14:50 brouard
524: Summary: Probably last 0.98 stable version 0.98r6
525:
1.222 brouard 526: Revision 1.221 2016/02/15 23:35:36 brouard
527: Summary: minor bug
528:
1.220 brouard 529: Revision 1.219 2016/02/15 00:48:12 brouard
530: *** empty log message ***
531:
1.219 brouard 532: Revision 1.218 2016/02/12 11:29:23 brouard
533: Summary: 0.99 Back projections
534:
1.218 brouard 535: Revision 1.217 2015/12/23 17:18:31 brouard
536: Summary: Experimental backcast
537:
1.217 brouard 538: Revision 1.216 2015/12/18 17:32:11 brouard
539: Summary: 0.98r4 Warning and status=-2
540:
541: Version 0.98r4 is now:
542: - displaying an error when status is -1, date of interview unknown and date of death known;
543: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
544: Older changes concerning s=-2, dating from 2005 have been supersed.
545:
1.216 brouard 546: Revision 1.215 2015/12/16 08:52:24 brouard
547: Summary: 0.98r4 working
548:
1.215 brouard 549: Revision 1.214 2015/12/16 06:57:54 brouard
550: Summary: temporary not working
551:
1.214 brouard 552: Revision 1.213 2015/12/11 18:22:17 brouard
553: Summary: 0.98r4
554:
1.213 brouard 555: Revision 1.212 2015/11/21 12:47:24 brouard
556: Summary: minor typo
557:
1.212 brouard 558: Revision 1.211 2015/11/21 12:41:11 brouard
559: Summary: 0.98r3 with some graph of projected cross-sectional
560:
561: Author: Nicolas Brouard
562:
1.211 brouard 563: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 564: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 565: Summary: Adding ftolpl parameter
566: Author: N Brouard
567:
568: We had difficulties to get smoothed confidence intervals. It was due
569: to the period prevalence which wasn't computed accurately. The inner
570: parameter ftolpl is now an outer parameter of the .imach parameter
571: file after estepm. If ftolpl is small 1.e-4 and estepm too,
572: computation are long.
573:
1.209 brouard 574: Revision 1.208 2015/11/17 14:31:57 brouard
575: Summary: temporary
576:
1.208 brouard 577: Revision 1.207 2015/10/27 17:36:57 brouard
578: *** empty log message ***
579:
1.207 brouard 580: Revision 1.206 2015/10/24 07:14:11 brouard
581: *** empty log message ***
582:
1.206 brouard 583: Revision 1.205 2015/10/23 15:50:53 brouard
584: Summary: 0.98r3 some clarification for graphs on likelihood contributions
585:
1.205 brouard 586: Revision 1.204 2015/10/01 16:20:26 brouard
587: Summary: Some new graphs of contribution to likelihood
588:
1.204 brouard 589: Revision 1.203 2015/09/30 17:45:14 brouard
590: Summary: looking at better estimation of the hessian
591:
592: Also a better criteria for convergence to the period prevalence And
593: therefore adding the number of years needed to converge. (The
594: prevalence in any alive state shold sum to one
595:
1.203 brouard 596: Revision 1.202 2015/09/22 19:45:16 brouard
597: Summary: Adding some overall graph on contribution to likelihood. Might change
598:
1.202 brouard 599: Revision 1.201 2015/09/15 17:34:58 brouard
600: Summary: 0.98r0
601:
602: - Some new graphs like suvival functions
603: - Some bugs fixed like model=1+age+V2.
604:
1.201 brouard 605: Revision 1.200 2015/09/09 16:53:55 brouard
606: Summary: Big bug thanks to Flavia
607:
608: Even model=1+age+V2. did not work anymore
609:
1.200 brouard 610: Revision 1.199 2015/09/07 14:09:23 brouard
611: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
612:
1.199 brouard 613: Revision 1.198 2015/09/03 07:14:39 brouard
614: Summary: 0.98q5 Flavia
615:
1.198 brouard 616: Revision 1.197 2015/09/01 18:24:39 brouard
617: *** empty log message ***
618:
1.197 brouard 619: Revision 1.196 2015/08/18 23:17:52 brouard
620: Summary: 0.98q5
621:
1.196 brouard 622: Revision 1.195 2015/08/18 16:28:39 brouard
623: Summary: Adding a hack for testing purpose
624:
625: After reading the title, ftol and model lines, if the comment line has
626: a q, starting with #q, the answer at the end of the run is quit. It
627: permits to run test files in batch with ctest. The former workaround was
628: $ echo q | imach foo.imach
629:
1.195 brouard 630: Revision 1.194 2015/08/18 13:32:00 brouard
631: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
632:
1.194 brouard 633: Revision 1.193 2015/08/04 07:17:42 brouard
634: Summary: 0.98q4
635:
1.193 brouard 636: Revision 1.192 2015/07/16 16:49:02 brouard
637: Summary: Fixing some outputs
638:
1.192 brouard 639: Revision 1.191 2015/07/14 10:00:33 brouard
640: Summary: Some fixes
641:
1.191 brouard 642: Revision 1.190 2015/05/05 08:51:13 brouard
643: Summary: Adding digits in output parameters (7 digits instead of 6)
644:
645: Fix 1+age+.
646:
1.190 brouard 647: Revision 1.189 2015/04/30 14:45:16 brouard
648: Summary: 0.98q2
649:
1.189 brouard 650: Revision 1.188 2015/04/30 08:27:53 brouard
651: *** empty log message ***
652:
1.188 brouard 653: Revision 1.187 2015/04/29 09:11:15 brouard
654: *** empty log message ***
655:
1.187 brouard 656: Revision 1.186 2015/04/23 12:01:52 brouard
657: Summary: V1*age is working now, version 0.98q1
658:
659: Some codes had been disabled in order to simplify and Vn*age was
660: working in the optimization phase, ie, giving correct MLE parameters,
661: but, as usual, outputs were not correct and program core dumped.
662:
1.186 brouard 663: Revision 1.185 2015/03/11 13:26:42 brouard
664: Summary: Inclusion of compile and links command line for Intel Compiler
665:
1.185 brouard 666: Revision 1.184 2015/03/11 11:52:39 brouard
667: Summary: Back from Windows 8. Intel Compiler
668:
1.184 brouard 669: Revision 1.183 2015/03/10 20:34:32 brouard
670: Summary: 0.98q0, trying with directest, mnbrak fixed
671:
672: We use directest instead of original Powell test; probably no
673: incidence on the results, but better justifications;
674: We fixed Numerical Recipes mnbrak routine which was wrong and gave
675: wrong results.
676:
1.183 brouard 677: Revision 1.182 2015/02/12 08:19:57 brouard
678: Summary: Trying to keep directest which seems simpler and more general
679: Author: Nicolas Brouard
680:
1.182 brouard 681: Revision 1.181 2015/02/11 23:22:24 brouard
682: Summary: Comments on Powell added
683:
684: Author:
685:
1.181 brouard 686: Revision 1.180 2015/02/11 17:33:45 brouard
687: Summary: Finishing move from main to function (hpijx and prevalence_limit)
688:
1.180 brouard 689: Revision 1.179 2015/01/04 09:57:06 brouard
690: Summary: back to OS/X
691:
1.179 brouard 692: Revision 1.178 2015/01/04 09:35:48 brouard
693: *** empty log message ***
694:
1.178 brouard 695: Revision 1.177 2015/01/03 18:40:56 brouard
696: Summary: Still testing ilc32 on OSX
697:
1.177 brouard 698: Revision 1.176 2015/01/03 16:45:04 brouard
699: *** empty log message ***
700:
1.176 brouard 701: Revision 1.175 2015/01/03 16:33:42 brouard
702: *** empty log message ***
703:
1.175 brouard 704: Revision 1.174 2015/01/03 16:15:49 brouard
705: Summary: Still in cross-compilation
706:
1.174 brouard 707: Revision 1.173 2015/01/03 12:06:26 brouard
708: Summary: trying to detect cross-compilation
709:
1.173 brouard 710: Revision 1.172 2014/12/27 12:07:47 brouard
711: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
712:
1.172 brouard 713: Revision 1.171 2014/12/23 13:26:59 brouard
714: Summary: Back from Visual C
715:
716: Still problem with utsname.h on Windows
717:
1.171 brouard 718: Revision 1.170 2014/12/23 11:17:12 brouard
719: Summary: Cleaning some \%% back to %%
720:
721: The escape was mandatory for a specific compiler (which one?), but too many warnings.
722:
1.170 brouard 723: Revision 1.169 2014/12/22 23:08:31 brouard
724: Summary: 0.98p
725:
726: Outputs some informations on compiler used, OS etc. Testing on different platforms.
727:
1.169 brouard 728: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 729: Summary: update
1.169 brouard 730:
1.168 brouard 731: Revision 1.167 2014/12/22 13:50:56 brouard
732: Summary: Testing uname and compiler version and if compiled 32 or 64
733:
734: Testing on Linux 64
735:
1.167 brouard 736: Revision 1.166 2014/12/22 11:40:47 brouard
737: *** empty log message ***
738:
1.166 brouard 739: Revision 1.165 2014/12/16 11:20:36 brouard
740: Summary: After compiling on Visual C
741:
742: * imach.c (Module): Merging 1.61 to 1.162
743:
1.165 brouard 744: Revision 1.164 2014/12/16 10:52:11 brouard
745: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
746:
747: * imach.c (Module): Merging 1.61 to 1.162
748:
1.164 brouard 749: Revision 1.163 2014/12/16 10:30:11 brouard
750: * imach.c (Module): Merging 1.61 to 1.162
751:
1.163 brouard 752: Revision 1.162 2014/09/25 11:43:39 brouard
753: Summary: temporary backup 0.99!
754:
1.162 brouard 755: Revision 1.1 2014/09/16 11:06:58 brouard
756: Summary: With some code (wrong) for nlopt
757:
758: Author:
759:
760: Revision 1.161 2014/09/15 20:41:41 brouard
761: Summary: Problem with macro SQR on Intel compiler
762:
1.161 brouard 763: Revision 1.160 2014/09/02 09:24:05 brouard
764: *** empty log message ***
765:
1.160 brouard 766: Revision 1.159 2014/09/01 10:34:10 brouard
767: Summary: WIN32
768: Author: Brouard
769:
1.159 brouard 770: Revision 1.158 2014/08/27 17:11:51 brouard
771: *** empty log message ***
772:
1.158 brouard 773: Revision 1.157 2014/08/27 16:26:55 brouard
774: Summary: Preparing windows Visual studio version
775: Author: Brouard
776:
777: In order to compile on Visual studio, time.h is now correct and time_t
778: and tm struct should be used. difftime should be used but sometimes I
779: just make the differences in raw time format (time(&now).
780: Trying to suppress #ifdef LINUX
781: Add xdg-open for __linux in order to open default browser.
782:
1.157 brouard 783: Revision 1.156 2014/08/25 20:10:10 brouard
784: *** empty log message ***
785:
1.156 brouard 786: Revision 1.155 2014/08/25 18:32:34 brouard
787: Summary: New compile, minor changes
788: Author: Brouard
789:
1.155 brouard 790: Revision 1.154 2014/06/20 17:32:08 brouard
791: Summary: Outputs now all graphs of convergence to period prevalence
792:
1.154 brouard 793: Revision 1.153 2014/06/20 16:45:46 brouard
794: Summary: If 3 live state, convergence to period prevalence on same graph
795: Author: Brouard
796:
1.153 brouard 797: Revision 1.152 2014/06/18 17:54:09 brouard
798: Summary: open browser, use gnuplot on same dir than imach if not found in the path
799:
1.152 brouard 800: Revision 1.151 2014/06/18 16:43:30 brouard
801: *** empty log message ***
802:
1.151 brouard 803: Revision 1.150 2014/06/18 16:42:35 brouard
804: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
805: Author: brouard
806:
1.150 brouard 807: Revision 1.149 2014/06/18 15:51:14 brouard
808: Summary: Some fixes in parameter files errors
809: Author: Nicolas Brouard
810:
1.149 brouard 811: Revision 1.148 2014/06/17 17:38:48 brouard
812: Summary: Nothing new
813: Author: Brouard
814:
815: Just a new packaging for OS/X version 0.98nS
816:
1.148 brouard 817: Revision 1.147 2014/06/16 10:33:11 brouard
818: *** empty log message ***
819:
1.147 brouard 820: Revision 1.146 2014/06/16 10:20:28 brouard
821: Summary: Merge
822: Author: Brouard
823:
824: Merge, before building revised version.
825:
1.146 brouard 826: Revision 1.145 2014/06/10 21:23:15 brouard
827: Summary: Debugging with valgrind
828: Author: Nicolas Brouard
829:
830: Lot of changes in order to output the results with some covariates
831: After the Edimburgh REVES conference 2014, it seems mandatory to
832: improve the code.
833: No more memory valgrind error but a lot has to be done in order to
834: continue the work of splitting the code into subroutines.
835: Also, decodemodel has been improved. Tricode is still not
836: optimal. nbcode should be improved. Documentation has been added in
837: the source code.
838:
1.144 brouard 839: Revision 1.143 2014/01/26 09:45:38 brouard
840: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
841:
842: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
843: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
844:
1.143 brouard 845: Revision 1.142 2014/01/26 03:57:36 brouard
846: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
847:
848: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
849:
1.142 brouard 850: Revision 1.141 2014/01/26 02:42:01 brouard
851: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
852:
1.141 brouard 853: Revision 1.140 2011/09/02 10:37:54 brouard
854: Summary: times.h is ok with mingw32 now.
855:
1.140 brouard 856: Revision 1.139 2010/06/14 07:50:17 brouard
857: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
858: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
859:
1.139 brouard 860: Revision 1.138 2010/04/30 18:19:40 brouard
861: *** empty log message ***
862:
1.138 brouard 863: Revision 1.137 2010/04/29 18:11:38 brouard
864: (Module): Checking covariates for more complex models
865: than V1+V2. A lot of change to be done. Unstable.
866:
1.137 brouard 867: Revision 1.136 2010/04/26 20:30:53 brouard
868: (Module): merging some libgsl code. Fixing computation
869: of likelione (using inter/intrapolation if mle = 0) in order to
870: get same likelihood as if mle=1.
871: Some cleaning of code and comments added.
872:
1.136 brouard 873: Revision 1.135 2009/10/29 15:33:14 brouard
874: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
875:
1.135 brouard 876: Revision 1.134 2009/10/29 13:18:53 brouard
877: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
878:
1.134 brouard 879: Revision 1.133 2009/07/06 10:21:25 brouard
880: just nforces
881:
1.133 brouard 882: Revision 1.132 2009/07/06 08:22:05 brouard
883: Many tings
884:
1.132 brouard 885: Revision 1.131 2009/06/20 16:22:47 brouard
886: Some dimensions resccaled
887:
1.131 brouard 888: Revision 1.130 2009/05/26 06:44:34 brouard
889: (Module): Max Covariate is now set to 20 instead of 8. A
890: lot of cleaning with variables initialized to 0. Trying to make
891: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
892:
1.130 brouard 893: Revision 1.129 2007/08/31 13:49:27 lievre
894: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
895:
1.129 lievre 896: Revision 1.128 2006/06/30 13:02:05 brouard
897: (Module): Clarifications on computing e.j
898:
1.128 brouard 899: Revision 1.127 2006/04/28 18:11:50 brouard
900: (Module): Yes the sum of survivors was wrong since
901: imach-114 because nhstepm was no more computed in the age
902: loop. Now we define nhstepma in the age loop.
903: (Module): In order to speed up (in case of numerous covariates) we
904: compute health expectancies (without variances) in a first step
905: and then all the health expectancies with variances or standard
906: deviation (needs data from the Hessian matrices) which slows the
907: computation.
908: In the future we should be able to stop the program is only health
909: expectancies and graph are needed without standard deviations.
910:
1.127 brouard 911: Revision 1.126 2006/04/28 17:23:28 brouard
912: (Module): Yes the sum of survivors was wrong since
913: imach-114 because nhstepm was no more computed in the age
914: loop. Now we define nhstepma in the age loop.
915: Version 0.98h
916:
1.126 brouard 917: Revision 1.125 2006/04/04 15:20:31 lievre
918: Errors in calculation of health expectancies. Age was not initialized.
919: Forecasting file added.
920:
921: Revision 1.124 2006/03/22 17:13:53 lievre
922: Parameters are printed with %lf instead of %f (more numbers after the comma).
923: The log-likelihood is printed in the log file
924:
925: Revision 1.123 2006/03/20 10:52:43 brouard
926: * imach.c (Module): <title> changed, corresponds to .htm file
927: name. <head> headers where missing.
928:
929: * imach.c (Module): Weights can have a decimal point as for
930: English (a comma might work with a correct LC_NUMERIC environment,
931: otherwise the weight is truncated).
932: Modification of warning when the covariates values are not 0 or
933: 1.
934: Version 0.98g
935:
936: Revision 1.122 2006/03/20 09:45:41 brouard
937: (Module): Weights can have a decimal point as for
938: English (a comma might work with a correct LC_NUMERIC environment,
939: otherwise the weight is truncated).
940: Modification of warning when the covariates values are not 0 or
941: 1.
942: Version 0.98g
943:
944: Revision 1.121 2006/03/16 17:45:01 lievre
945: * imach.c (Module): Comments concerning covariates added
946:
947: * imach.c (Module): refinements in the computation of lli if
948: status=-2 in order to have more reliable computation if stepm is
949: not 1 month. Version 0.98f
950:
951: Revision 1.120 2006/03/16 15:10:38 lievre
952: (Module): refinements in the computation of lli if
953: status=-2 in order to have more reliable computation if stepm is
954: not 1 month. Version 0.98f
955:
956: Revision 1.119 2006/03/15 17:42:26 brouard
957: (Module): Bug if status = -2, the loglikelihood was
958: computed as likelihood omitting the logarithm. Version O.98e
959:
960: Revision 1.118 2006/03/14 18:20:07 brouard
961: (Module): varevsij Comments added explaining the second
962: table of variances if popbased=1 .
963: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
964: (Module): Function pstamp added
965: (Module): Version 0.98d
966:
967: Revision 1.117 2006/03/14 17:16:22 brouard
968: (Module): varevsij Comments added explaining the second
969: table of variances if popbased=1 .
970: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
971: (Module): Function pstamp added
972: (Module): Version 0.98d
973:
974: Revision 1.116 2006/03/06 10:29:27 brouard
975: (Module): Variance-covariance wrong links and
976: varian-covariance of ej. is needed (Saito).
977:
978: Revision 1.115 2006/02/27 12:17:45 brouard
979: (Module): One freematrix added in mlikeli! 0.98c
980:
981: Revision 1.114 2006/02/26 12:57:58 brouard
982: (Module): Some improvements in processing parameter
983: filename with strsep.
984:
985: Revision 1.113 2006/02/24 14:20:24 brouard
986: (Module): Memory leaks checks with valgrind and:
987: datafile was not closed, some imatrix were not freed and on matrix
988: allocation too.
989:
990: Revision 1.112 2006/01/30 09:55:26 brouard
991: (Module): Back to gnuplot.exe instead of wgnuplot.exe
992:
993: Revision 1.111 2006/01/25 20:38:18 brouard
994: (Module): Lots of cleaning and bugs added (Gompertz)
995: (Module): Comments can be added in data file. Missing date values
996: can be a simple dot '.'.
997:
998: Revision 1.110 2006/01/25 00:51:50 brouard
999: (Module): Lots of cleaning and bugs added (Gompertz)
1000:
1001: Revision 1.109 2006/01/24 19:37:15 brouard
1002: (Module): Comments (lines starting with a #) are allowed in data.
1003:
1004: Revision 1.108 2006/01/19 18:05:42 lievre
1005: Gnuplot problem appeared...
1006: To be fixed
1007:
1008: Revision 1.107 2006/01/19 16:20:37 brouard
1009: Test existence of gnuplot in imach path
1010:
1011: Revision 1.106 2006/01/19 13:24:36 brouard
1012: Some cleaning and links added in html output
1013:
1014: Revision 1.105 2006/01/05 20:23:19 lievre
1015: *** empty log message ***
1016:
1017: Revision 1.104 2005/09/30 16:11:43 lievre
1018: (Module): sump fixed, loop imx fixed, and simplifications.
1019: (Module): If the status is missing at the last wave but we know
1020: that the person is alive, then we can code his/her status as -2
1021: (instead of missing=-1 in earlier versions) and his/her
1022: contributions to the likelihood is 1 - Prob of dying from last
1023: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1024: the healthy state at last known wave). Version is 0.98
1025:
1026: Revision 1.103 2005/09/30 15:54:49 lievre
1027: (Module): sump fixed, loop imx fixed, and simplifications.
1028:
1029: Revision 1.102 2004/09/15 17:31:30 brouard
1030: Add the possibility to read data file including tab characters.
1031:
1032: Revision 1.101 2004/09/15 10:38:38 brouard
1033: Fix on curr_time
1034:
1035: Revision 1.100 2004/07/12 18:29:06 brouard
1036: Add version for Mac OS X. Just define UNIX in Makefile
1037:
1038: Revision 1.99 2004/06/05 08:57:40 brouard
1039: *** empty log message ***
1040:
1041: Revision 1.98 2004/05/16 15:05:56 brouard
1042: New version 0.97 . First attempt to estimate force of mortality
1043: directly from the data i.e. without the need of knowing the health
1044: state at each age, but using a Gompertz model: log u =a + b*age .
1045: This is the basic analysis of mortality and should be done before any
1046: other analysis, in order to test if the mortality estimated from the
1047: cross-longitudinal survey is different from the mortality estimated
1048: from other sources like vital statistic data.
1049:
1050: The same imach parameter file can be used but the option for mle should be -3.
1051:
1.324 brouard 1052: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1053: former routines in order to include the new code within the former code.
1054:
1055: The output is very simple: only an estimate of the intercept and of
1056: the slope with 95% confident intervals.
1057:
1058: Current limitations:
1059: A) Even if you enter covariates, i.e. with the
1060: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1061: B) There is no computation of Life Expectancy nor Life Table.
1062:
1063: Revision 1.97 2004/02/20 13:25:42 lievre
1064: Version 0.96d. Population forecasting command line is (temporarily)
1065: suppressed.
1066:
1067: Revision 1.96 2003/07/15 15:38:55 brouard
1068: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1069: rewritten within the same printf. Workaround: many printfs.
1070:
1071: Revision 1.95 2003/07/08 07:54:34 brouard
1072: * imach.c (Repository):
1073: (Repository): Using imachwizard code to output a more meaningful covariance
1074: matrix (cov(a12,c31) instead of numbers.
1075:
1076: Revision 1.94 2003/06/27 13:00:02 brouard
1077: Just cleaning
1078:
1079: Revision 1.93 2003/06/25 16:33:55 brouard
1080: (Module): On windows (cygwin) function asctime_r doesn't
1081: exist so I changed back to asctime which exists.
1082: (Module): Version 0.96b
1083:
1084: Revision 1.92 2003/06/25 16:30:45 brouard
1085: (Module): On windows (cygwin) function asctime_r doesn't
1086: exist so I changed back to asctime which exists.
1087:
1088: Revision 1.91 2003/06/25 15:30:29 brouard
1089: * imach.c (Repository): Duplicated warning errors corrected.
1090: (Repository): Elapsed time after each iteration is now output. It
1091: helps to forecast when convergence will be reached. Elapsed time
1092: is stamped in powell. We created a new html file for the graphs
1093: concerning matrix of covariance. It has extension -cov.htm.
1094:
1095: Revision 1.90 2003/06/24 12:34:15 brouard
1096: (Module): Some bugs corrected for windows. Also, when
1097: mle=-1 a template is output in file "or"mypar.txt with the design
1098: of the covariance matrix to be input.
1099:
1100: Revision 1.89 2003/06/24 12:30:52 brouard
1101: (Module): Some bugs corrected for windows. Also, when
1102: mle=-1 a template is output in file "or"mypar.txt with the design
1103: of the covariance matrix to be input.
1104:
1105: Revision 1.88 2003/06/23 17:54:56 brouard
1106: * imach.c (Repository): Create a sub-directory where all the secondary files are. Only imach, htm, gp and r(imach) are on the main directory. Correct time and other things.
1107:
1108: Revision 1.87 2003/06/18 12:26:01 brouard
1109: Version 0.96
1110:
1111: Revision 1.86 2003/06/17 20:04:08 brouard
1112: (Module): Change position of html and gnuplot routines and added
1113: routine fileappend.
1114:
1115: Revision 1.85 2003/06/17 13:12:43 brouard
1116: * imach.c (Repository): Check when date of death was earlier that
1117: current date of interview. It may happen when the death was just
1118: prior to the death. In this case, dh was negative and likelihood
1119: was wrong (infinity). We still send an "Error" but patch by
1120: assuming that the date of death was just one stepm after the
1121: interview.
1122: (Repository): Because some people have very long ID (first column)
1123: we changed int to long in num[] and we added a new lvector for
1124: memory allocation. But we also truncated to 8 characters (left
1125: truncation)
1126: (Repository): No more line truncation errors.
1127:
1128: Revision 1.84 2003/06/13 21:44:43 brouard
1129: * imach.c (Repository): Replace "freqsummary" at a correct
1130: place. It differs from routine "prevalence" which may be called
1131: many times. Probs is memory consuming and must be used with
1132: parcimony.
1133: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1134:
1135: Revision 1.83 2003/06/10 13:39:11 lievre
1136: *** empty log message ***
1137:
1138: Revision 1.82 2003/06/05 15:57:20 brouard
1139: Add log in imach.c and fullversion number is now printed.
1140:
1141: */
1142: /*
1143: Interpolated Markov Chain
1144:
1145: Short summary of the programme:
1146:
1.227 brouard 1147: This program computes Healthy Life Expectancies or State-specific
1148: (if states aren't health statuses) Expectancies from
1149: cross-longitudinal data. Cross-longitudinal data consist in:
1150:
1151: -1- a first survey ("cross") where individuals from different ages
1152: are interviewed on their health status or degree of disability (in
1153: the case of a health survey which is our main interest)
1154:
1155: -2- at least a second wave of interviews ("longitudinal") which
1156: measure each change (if any) in individual health status. Health
1157: expectancies are computed from the time spent in each health state
1158: according to a model. More health states you consider, more time is
1159: necessary to reach the Maximum Likelihood of the parameters involved
1160: in the model. The simplest model is the multinomial logistic model
1161: where pij is the probability to be observed in state j at the second
1162: wave conditional to be observed in state i at the first
1163: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1164: etc , where 'age' is age and 'sex' is a covariate. If you want to
1165: have a more complex model than "constant and age", you should modify
1166: the program where the markup *Covariates have to be included here
1167: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1168: convergence.
1169:
1170: The advantage of this computer programme, compared to a simple
1171: multinomial logistic model, is clear when the delay between waves is not
1172: identical for each individual. Also, if a individual missed an
1173: intermediate interview, the information is lost, but taken into
1174: account using an interpolation or extrapolation.
1175:
1176: hPijx is the probability to be observed in state i at age x+h
1177: conditional to the observed state i at age x. The delay 'h' can be
1178: split into an exact number (nh*stepm) of unobserved intermediate
1179: states. This elementary transition (by month, quarter,
1180: semester or year) is modelled as a multinomial logistic. The hPx
1181: matrix is simply the matrix product of nh*stepm elementary matrices
1182: and the contribution of each individual to the likelihood is simply
1183: hPijx.
1184:
1185: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1186: of the life expectancies. It also computes the period (stable) prevalence.
1187:
1188: Back prevalence and projections:
1.227 brouard 1189:
1190: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1191: double agemaxpar, double ftolpl, int *ncvyearp, double
1192: dateprev1,double dateprev2, int firstpass, int lastpass, int
1193: mobilavproj)
1194:
1195: Computes the back prevalence limit for any combination of
1196: covariate values k at any age between ageminpar and agemaxpar and
1197: returns it in **bprlim. In the loops,
1198:
1199: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1200: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1201:
1202: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1203: Computes for any combination of covariates k and any age between bage and fage
1204: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1205: oldm=oldms;savm=savms;
1.227 brouard 1206:
1.267 brouard 1207: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1208: Computes the transition matrix starting at age 'age' over
1209: 'nhstepm*hstepm*stepm' months (i.e. until
1210: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1211: nhstepm*hstepm matrices.
1212:
1213: Returns p3mat[i][j][h] after calling
1214: p3mat[i][j][h]=matprod2(newm,
1215: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1216: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1217: oldm);
1.226 brouard 1218:
1219: Important routines
1220:
1221: - func (or funcone), computes logit (pij) distinguishing
1222: o fixed variables (single or product dummies or quantitative);
1223: o varying variables by:
1224: (1) wave (single, product dummies, quantitative),
1225: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1226: % fixed dummy (treated) or quantitative (not done because time-consuming);
1227: % varying dummy (not done) or quantitative (not done);
1228: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1229: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1230: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1231: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1232: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1233:
1.226 brouard 1234:
1235:
1.324 brouard 1236: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1237: Institut national d'études démographiques, Paris.
1.126 brouard 1238: This software have been partly granted by Euro-REVES, a concerted action
1239: from the European Union.
1240: It is copyrighted identically to a GNU software product, ie programme and
1241: software can be distributed freely for non commercial use. Latest version
1242: can be accessed at http://euroreves.ined.fr/imach .
1243:
1244: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1245: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1246:
1247: **********************************************************************/
1248: /*
1249: main
1250: read parameterfile
1251: read datafile
1252: concatwav
1253: freqsummary
1254: if (mle >= 1)
1255: mlikeli
1256: print results files
1257: if mle==1
1258: computes hessian
1259: read end of parameter file: agemin, agemax, bage, fage, estepm
1260: begin-prev-date,...
1261: open gnuplot file
1262: open html file
1.145 brouard 1263: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1264: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1265: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1266: freexexit2 possible for memory heap.
1267:
1268: h Pij x | pij_nom ficrestpij
1269: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1270: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1271: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1272:
1273: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1274: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1275: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1276: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1277: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1278:
1.126 brouard 1279: forecasting if prevfcast==1 prevforecast call prevalence()
1280: health expectancies
1281: Variance-covariance of DFLE
1282: prevalence()
1283: movingaverage()
1284: varevsij()
1285: if popbased==1 varevsij(,popbased)
1286: total life expectancies
1287: Variance of period (stable) prevalence
1288: end
1289: */
1290:
1.187 brouard 1291: /* #define DEBUG */
1292: /* #define DEBUGBRENT */
1.203 brouard 1293: /* #define DEBUGLINMIN */
1294: /* #define DEBUGHESS */
1295: #define DEBUGHESSIJ
1.224 brouard 1296: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1297: #define POWELL /* Instead of NLOPT */
1.224 brouard 1298: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1299: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1300: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1301: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.359 brouard 1302: /* #define POWELLORIGINCONJUGATE /\* Don't use conjugate but biggest decrease if valuable *\/ */
1303: /* #define NOTMINFIT */
1.126 brouard 1304:
1305: #include <math.h>
1306: #include <stdio.h>
1307: #include <stdlib.h>
1308: #include <string.h>
1.226 brouard 1309: #include <ctype.h>
1.159 brouard 1310:
1311: #ifdef _WIN32
1312: #include <io.h>
1.172 brouard 1313: #include <windows.h>
1314: #include <tchar.h>
1.159 brouard 1315: #else
1.126 brouard 1316: #include <unistd.h>
1.159 brouard 1317: #endif
1.126 brouard 1318:
1319: #include <limits.h>
1320: #include <sys/types.h>
1.171 brouard 1321:
1322: #if defined(__GNUC__)
1323: #include <sys/utsname.h> /* Doesn't work on Windows */
1324: #endif
1325:
1.126 brouard 1326: #include <sys/stat.h>
1327: #include <errno.h>
1.159 brouard 1328: /* extern int errno; */
1.126 brouard 1329:
1.157 brouard 1330: /* #ifdef LINUX */
1331: /* #include <time.h> */
1332: /* #include "timeval.h" */
1333: /* #else */
1334: /* #include <sys/time.h> */
1335: /* #endif */
1336:
1.126 brouard 1337: #include <time.h>
1338:
1.136 brouard 1339: #ifdef GSL
1340: #include <gsl/gsl_errno.h>
1341: #include <gsl/gsl_multimin.h>
1342: #endif
1343:
1.167 brouard 1344:
1.162 brouard 1345: #ifdef NLOPT
1346: #include <nlopt.h>
1347: typedef struct {
1348: double (* function)(double [] );
1349: } myfunc_data ;
1350: #endif
1351:
1.126 brouard 1352: /* #include <libintl.h> */
1353: /* #define _(String) gettext (String) */
1354:
1.349 brouard 1355: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1356:
1357: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1358: #define GNUPLOTVERSION 5.1
1359: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1360: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1361: #define FILENAMELENGTH 256
1.126 brouard 1362:
1363: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1364: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1365:
1.349 brouard 1366: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1367: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1368:
1369: #define NINTERVMAX 8
1.144 brouard 1370: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1371: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1372: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1373: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1374: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1375: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1376: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1377: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1378: /* #define AGESUP 130 */
1.288 brouard 1379: /* #define AGESUP 150 */
1380: #define AGESUP 200
1.268 brouard 1381: #define AGEINF 0
1.218 brouard 1382: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1383: #define AGEBASE 40
1.194 brouard 1384: #define AGEOVERFLOW 1.e20
1.164 brouard 1385: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1386: #ifdef _WIN32
1387: #define DIRSEPARATOR '\\'
1388: #define CHARSEPARATOR "\\"
1389: #define ODIRSEPARATOR '/'
1390: #else
1.126 brouard 1391: #define DIRSEPARATOR '/'
1392: #define CHARSEPARATOR "/"
1393: #define ODIRSEPARATOR '\\'
1394: #endif
1395:
1.361 ! brouard 1396: /* $Id: imach.c,v 1.360 2024/04/30 10:59:22 brouard Exp $ */
1.126 brouard 1397: /* $State: Exp $ */
1.196 brouard 1398: #include "version.h"
1399: char version[]=__IMACH_VERSION__;
1.360 brouard 1400: char copyright[]="April 2024,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2024";
1.361 ! brouard 1401: char fullversion[]="$Revision: 1.360 $ $Date: 2024/04/30 10:59:22 $";
1.126 brouard 1402: char strstart[80];
1403: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1404: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1405: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1406: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1407: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1408: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1409: int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age but including products */
1.330 brouard 1410: int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.335 brouard 1411: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1412: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1413: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1414: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1415: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1416: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1417: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1418: int cptcoveff=0; /* Total number of single dummy covariates (fixed or time varying) to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */
1.233 brouard 1419: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1420: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1421: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1422: int ncovvta=0; /* +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1423: int ncovta=0; /*age*V3*V2 +age*V2+agev3+ageV4 +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1424: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1425: int ncovva=0; /* +age*V6 + age*V7+ge*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1.234 brouard 1426: int nsd=0; /**< Total number of single dummy variables (output) */
1427: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1428: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1429: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1430: int ntveff=0; /**< ntveff number of effective time varying variables */
1431: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1432: int cptcov=0; /* Working variable */
1.334 brouard 1433: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1434: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1435: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1436: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1437: int nlstate=2; /* Number of live states */
1438: int ndeath=1; /* Number of dead states */
1.130 brouard 1439: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1440: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1441: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1442: int popbased=0;
1443:
1444: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1445: int maxwav=0; /* Maxim number of waves */
1446: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1447: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1.359 brouard 1448: int gipmx = 0;
1449: double gsw = 0; /* Global variables on the number of contributions
1.126 brouard 1450: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1451: int mle=1, weightopt=0;
1.126 brouard 1452: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1453: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1454: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1455: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1456: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1457: int selected(int kvar); /* Is covariate kvar selected for printing results */
1458:
1.130 brouard 1459: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1460: double **matprod2(); /* test */
1.126 brouard 1461: double **oldm, **newm, **savm; /* Working pointers to matrices */
1462: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1463: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1464:
1.136 brouard 1465: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1466: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1467: FILE *ficlog, *ficrespow;
1.130 brouard 1468: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1469: double fretone; /* Only one call to likelihood */
1.130 brouard 1470: long ipmx=0; /* Number of contributions */
1.126 brouard 1471: double sw; /* Sum of weights */
1472: char filerespow[FILENAMELENGTH];
1473: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1474: FILE *ficresilk;
1475: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1476: FILE *ficresprobmorprev;
1477: FILE *fichtm, *fichtmcov; /* Html File */
1478: FILE *ficreseij;
1479: char filerese[FILENAMELENGTH];
1480: FILE *ficresstdeij;
1481: char fileresstde[FILENAMELENGTH];
1482: FILE *ficrescveij;
1483: char filerescve[FILENAMELENGTH];
1484: FILE *ficresvij;
1485: char fileresv[FILENAMELENGTH];
1.269 brouard 1486:
1.126 brouard 1487: char title[MAXLINE];
1.234 brouard 1488: char model[MAXLINE]; /**< The model line */
1.217 brouard 1489: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1490: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1491: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1492: char command[FILENAMELENGTH];
1493: int outcmd=0;
1494:
1.217 brouard 1495: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1496: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1497: char filelog[FILENAMELENGTH]; /* Log file */
1498: char filerest[FILENAMELENGTH];
1499: char fileregp[FILENAMELENGTH];
1500: char popfile[FILENAMELENGTH];
1501:
1502: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1503:
1.157 brouard 1504: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1505: /* struct timezone tzp; */
1506: /* extern int gettimeofday(); */
1507: struct tm tml, *gmtime(), *localtime();
1508:
1509: extern time_t time();
1510:
1511: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1512: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1513: time_t rlast_btime; /* raw time */
1.157 brouard 1514: struct tm tm;
1515:
1.126 brouard 1516: char strcurr[80], strfor[80];
1517:
1518: char *endptr;
1519: long lval;
1520: double dval;
1521:
1522: #define NR_END 1
1523: #define FREE_ARG char*
1524: #define FTOL 1.0e-10
1525:
1526: #define NRANSI
1.240 brouard 1527: #define ITMAX 200
1528: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1529:
1530: #define TOL 2.0e-4
1531:
1532: #define CGOLD 0.3819660
1533: #define ZEPS 1.0e-10
1534: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1535:
1536: #define GOLD 1.618034
1537: #define GLIMIT 100.0
1538: #define TINY 1.0e-20
1539:
1540: static double maxarg1,maxarg2;
1541: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1542: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1543:
1544: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1545: #define rint(a) floor(a+0.5)
1.166 brouard 1546: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1547: #define mytinydouble 1.0e-16
1.166 brouard 1548: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1549: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1550: /* static double dsqrarg; */
1551: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1552: static double sqrarg;
1553: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1554: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1555: int agegomp= AGEGOMP;
1556:
1557: int imx;
1558: int stepm=1;
1559: /* Stepm, step in month: minimum step interpolation*/
1560:
1561: int estepm;
1562: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1563:
1564: int m,nb;
1565: long *num;
1.197 brouard 1566: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1567: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1568: covariate for which somebody answered excluding
1569: undefined. Usually 2: 0 and 1. */
1570: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1571: covariate for which somebody answered including
1572: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1573: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1574: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1575: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1576: double **precov; /* New global variable to store for each resultline, values of model covariates given by the resultlines (in order to speed up) */
1.126 brouard 1577: double *ageexmed,*agecens;
1578: double dateintmean=0;
1.296 brouard 1579: double anprojd, mprojd, jprojd; /* For eventual projections */
1580: double anprojf, mprojf, jprojf;
1.126 brouard 1581:
1.296 brouard 1582: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1583: double anbackf, mbackf, jbackf;
1584: double jintmean,mintmean,aintmean;
1.126 brouard 1585: double *weight;
1586: int **s; /* Status */
1.141 brouard 1587: double *agedc;
1.145 brouard 1588: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1589: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1590: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1591: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1592: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1593: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1594: double idx;
1595: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1596: /* Some documentation */
1597: /* Design original data
1598: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1599: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1600: * ntv=3 nqtv=1
1.330 brouard 1601: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1602: * For time varying covariate, quanti or dummies
1603: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1604: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1605: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1606: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1607: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1608: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1609: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1610: * k= 1 2 3 4 5 6 7 8 9 10 11
1611: */
1612: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1613: /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
1614: # States 1=Coresidence, 2 Living alone, 3 Institution
1615: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1616: */
1.349 brouard 1617: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1618: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1619: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1620: /* fixed or varying), 1 for age product, 2 for*/
1621: /* product without age, 3 for age and double product */
1622: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1623: /*(single or product without age), 2 dummy*/
1624: /* with age product, 3 quant with age product*/
1625: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1626: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1627: /*TnsdVar[Tvar] 1 2 3 */
1628: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1629: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1630: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1631: /* nsq 1 2 */ /* Counting single quantit tv */
1632: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1633: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1634: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1635: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1636: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1637: /* model="V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
1638: /* p Tvard[1][1]@21 = {6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0}*/
1.354 brouard 1639: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>} */
1.350 brouard 1640: /* p Tvardk[1][1]@24 = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0}*/
1641: /* p Tvardk[1][1]@22 = {0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0} */
1.349 brouard 1642: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1643: /* Tvardk[4][1]=4;Tvardk[4][2]=3;Tvardk[7][1]=1;Tvardk[7][2]=2 */ /* Variables of a prod at position in the model equation*/
1.319 brouard 1644: /* TvarF TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 1645: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1646: /* Type */
1647: /* V 1 2 3 4 5 */
1648: /* F F V V V */
1649: /* D Q D D Q */
1650: /* */
1651: int *TvarsD;
1.330 brouard 1652: int *TnsdVar;
1.234 brouard 1653: int *TvarsDind;
1654: int *TvarsQ;
1655: int *TvarsQind;
1656:
1.318 brouard 1657: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1658: int nresult=0;
1.258 brouard 1659: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1660: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1661: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1662: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1663: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1664: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1665: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1666: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1667: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1668: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1669: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1670:
1671: /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
1672: # States 1=Coresidence, 2 Living alone, 3 Institution
1673: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1674: */
1.234 brouard 1675: /* int *TDvar; /\**< TDvar[1]=4, TDvarF[2]=3, TDvar[3]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
1.232 brouard 1676: int *TvarF; /**< TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1677: int *TvarFind; /**< TvarFind[1]=6, TvarFind[2]=7, Tvarind[3]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1678: int *TvarV; /**< TvarV[1]=Tvar[1]=5, TvarV[2]=Tvar[2]=4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1679: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1680: int *TvarA; /**< TvarA[1]=Tvar[5]=5, TvarA[2]=Tvar[8]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1681: int *TvarAind; /**< TvarindA[1]=5, TvarAind[2]=8 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 1682: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1683: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1684: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1685: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1686: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1687: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1688: int *TvarVQ; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1689: int *TvarVQind; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1.339 brouard 1690: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1691: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1692: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1693: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1694: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1695: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1696: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1697: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1698: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1699: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1700: /* TvarVVind={2,5,5,6,6}, for V3 and then the product V1*V3 is decomposed into V1 and V3 and V1*V3*age into 6,6 */
1.230 brouard 1701: int *Tvarsel; /**< Selected covariates for output */
1702: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1703: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 age*Vn*Vm */
1.227 brouard 1704: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1705: int *Dummy; /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.238 brouard 1706: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1707: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1708: int *Tage;
1.227 brouard 1709: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1710: int *Tmodelind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.230 brouard 1711: int *TmodelInvind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1712: int *TmodelInvQind; /** Tmodelqind[1]=1 for V5(quantitative varying) position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.145 brouard 1713: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1714: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1715: int **Tvard;
1.330 brouard 1716: int **Tvardk;
1.227 brouard 1717: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1718: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1719: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1720: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1721: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1722: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1723: double *lsurv, *lpop, *tpop;
1724:
1.231 brouard 1725: #define FD 1; /* Fixed dummy covariate */
1726: #define FQ 2; /* Fixed quantitative covariate */
1727: #define FP 3; /* Fixed product covariate */
1728: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1729: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1730: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1731: #define VD 10; /* Varying dummy covariate */
1732: #define VQ 11; /* Varying quantitative covariate */
1733: #define VP 12; /* Varying product covariate */
1734: #define VPDD 13; /* Varying product dummy*dummy covariate */
1735: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1736: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1737: #define APFD 16; /* Age product * fixed dummy covariate */
1738: #define APFQ 17; /* Age product * fixed quantitative covariate */
1739: #define APVD 18; /* Age product * varying dummy covariate */
1740: #define APVQ 19; /* Age product * varying quantitative covariate */
1741:
1742: #define FTYPE 1; /* Fixed covariate */
1743: #define VTYPE 2; /* Varying covariate (loop in wave) */
1744: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1745:
1746: struct kmodel{
1747: int maintype; /* main type */
1748: int subtype; /* subtype */
1749: };
1750: struct kmodel modell[NCOVMAX];
1751:
1.143 brouard 1752: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1753: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1754:
1755: /**************** split *************************/
1756: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1757: {
1758: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1759: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1760: */
1761: char *ss; /* pointer */
1.186 brouard 1762: int l1=0, l2=0; /* length counters */
1.126 brouard 1763:
1764: l1 = strlen(path ); /* length of path */
1765: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1766: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1767: if ( ss == NULL ) { /* no directory, so determine current directory */
1768: strcpy( name, path ); /* we got the fullname name because no directory */
1769: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1770: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1771: /* get current working directory */
1772: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1773: #ifdef WIN32
1774: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1775: #else
1776: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1777: #endif
1.126 brouard 1778: return( GLOCK_ERROR_GETCWD );
1779: }
1780: /* got dirc from getcwd*/
1781: printf(" DIRC = %s \n",dirc);
1.205 brouard 1782: } else { /* strip directory from path */
1.126 brouard 1783: ss++; /* after this, the filename */
1784: l2 = strlen( ss ); /* length of filename */
1785: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1786: strcpy( name, ss ); /* save file name */
1787: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1788: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1789: printf(" DIRC2 = %s \n",dirc);
1790: }
1791: /* We add a separator at the end of dirc if not exists */
1792: l1 = strlen( dirc ); /* length of directory */
1793: if( dirc[l1-1] != DIRSEPARATOR ){
1794: dirc[l1] = DIRSEPARATOR;
1795: dirc[l1+1] = 0;
1796: printf(" DIRC3 = %s \n",dirc);
1797: }
1798: ss = strrchr( name, '.' ); /* find last / */
1799: if (ss >0){
1800: ss++;
1801: strcpy(ext,ss); /* save extension */
1802: l1= strlen( name);
1803: l2= strlen(ss)+1;
1804: strncpy( finame, name, l1-l2);
1805: finame[l1-l2]= 0;
1806: }
1807:
1808: return( 0 ); /* we're done */
1809: }
1810:
1811:
1812: /******************************************/
1813:
1814: void replace_back_to_slash(char *s, char*t)
1815: {
1816: int i;
1817: int lg=0;
1818: i=0;
1819: lg=strlen(t);
1820: for(i=0; i<= lg; i++) {
1821: (s[i] = t[i]);
1822: if (t[i]== '\\') s[i]='/';
1823: }
1824: }
1825:
1.132 brouard 1826: char *trimbb(char *out, char *in)
1.137 brouard 1827: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1828: char *s;
1829: s=out;
1830: while (*in != '\0'){
1.137 brouard 1831: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1832: in++;
1833: }
1834: *out++ = *in++;
1835: }
1836: *out='\0';
1837: return s;
1838: }
1839:
1.351 brouard 1840: char *trimbtab(char *out, char *in)
1841: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1842: char *s;
1843: s=out;
1844: while (*in != '\0'){
1845: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1846: in++;
1847: }
1848: *out++ = *in++;
1849: }
1850: *out='\0';
1851: return s;
1852: }
1853:
1.187 brouard 1854: /* char *substrchaine(char *out, char *in, char *chain) */
1855: /* { */
1856: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1857: /* char *s, *t; */
1858: /* t=in;s=out; */
1859: /* while ((*in != *chain) && (*in != '\0')){ */
1860: /* *out++ = *in++; */
1861: /* } */
1862:
1863: /* /\* *in matches *chain *\/ */
1864: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1865: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1866: /* } */
1867: /* in--; chain--; */
1868: /* while ( (*in != '\0')){ */
1869: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1870: /* *out++ = *in++; */
1871: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1872: /* } */
1873: /* *out='\0'; */
1874: /* out=s; */
1875: /* return out; */
1876: /* } */
1877: char *substrchaine(char *out, char *in, char *chain)
1878: {
1879: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1880: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1881:
1882: char *strloc;
1883:
1.349 brouard 1884: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1885: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1886: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out); /* strloc=+age*age+V2 chain="+age*age", out="V1+V1*age+age*age+V2" */
1.187 brouard 1887: if(strloc != NULL){
1.349 brouard 1888: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1889: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1); /* move number of bytes corresponding to the length of "+V2" which is 3, plus one is 4 (including the null)*/
1890: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1891: }
1.349 brouard 1892: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); /* strloc=+V2 chain="+age*age", in="V1+V1*age+age*age+V2", out="V1+V1*age+V2" */
1.187 brouard 1893: return out;
1894: }
1895:
1896:
1.145 brouard 1897: char *cutl(char *blocc, char *alocc, char *in, char occ)
1898: {
1.187 brouard 1899: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1900: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1901: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1902: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1903: */
1.160 brouard 1904: char *s, *t;
1.145 brouard 1905: t=in;s=in;
1906: while ((*in != occ) && (*in != '\0')){
1907: *alocc++ = *in++;
1908: }
1909: if( *in == occ){
1910: *(alocc)='\0';
1911: s=++in;
1912: }
1913:
1914: if (s == t) {/* occ not found */
1915: *(alocc-(in-s))='\0';
1916: in=s;
1917: }
1918: while ( *in != '\0'){
1919: *blocc++ = *in++;
1920: }
1921:
1922: *blocc='\0';
1923: return t;
1924: }
1.137 brouard 1925: char *cutv(char *blocc, char *alocc, char *in, char occ)
1926: {
1.187 brouard 1927: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1928: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1929: gives blocc="abcdef2ghi" and alocc="j".
1930: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1931: */
1932: char *s, *t;
1933: t=in;s=in;
1934: while (*in != '\0'){
1935: while( *in == occ){
1936: *blocc++ = *in++;
1937: s=in;
1938: }
1939: *blocc++ = *in++;
1940: }
1941: if (s == t) /* occ not found */
1942: *(blocc-(in-s))='\0';
1943: else
1944: *(blocc-(in-s)-1)='\0';
1945: in=s;
1946: while ( *in != '\0'){
1947: *alocc++ = *in++;
1948: }
1949:
1950: *alocc='\0';
1951: return s;
1952: }
1953:
1.126 brouard 1954: int nbocc(char *s, char occ)
1955: {
1956: int i,j=0;
1957: int lg=20;
1958: i=0;
1959: lg=strlen(s);
1960: for(i=0; i<= lg; i++) {
1.234 brouard 1961: if (s[i] == occ ) j++;
1.126 brouard 1962: }
1963: return j;
1964: }
1965:
1.349 brouard 1966: int nboccstr(char *textin, char *chain)
1967: {
1968: /* Counts the number of occurence of "chain" in string textin */
1969: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1970: char *strloc;
1971:
1972: int i,j=0;
1973:
1974: i=0;
1975:
1976: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1977: for(;;) {
1978: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1979: if(strloc != NULL){
1980: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1981: j++;
1982: }else
1983: break;
1984: }
1985: return j;
1986:
1987: }
1.137 brouard 1988: /* void cutv(char *u,char *v, char*t, char occ) */
1989: /* { */
1990: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1991: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1992: /* gives u="abcdef2ghi" and v="j" *\/ */
1993: /* int i,lg,j,p=0; */
1994: /* i=0; */
1995: /* lg=strlen(t); */
1996: /* for(j=0; j<=lg-1; j++) { */
1997: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1998: /* } */
1.126 brouard 1999:
1.137 brouard 2000: /* for(j=0; j<p; j++) { */
2001: /* (u[j] = t[j]); */
2002: /* } */
2003: /* u[p]='\0'; */
1.126 brouard 2004:
1.137 brouard 2005: /* for(j=0; j<= lg; j++) { */
2006: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
2007: /* } */
2008: /* } */
1.126 brouard 2009:
1.160 brouard 2010: #ifdef _WIN32
2011: char * strsep(char **pp, const char *delim)
2012: {
2013: char *p, *q;
2014:
2015: if ((p = *pp) == NULL)
2016: return 0;
2017: if ((q = strpbrk (p, delim)) != NULL)
2018: {
2019: *pp = q + 1;
2020: *q = '\0';
2021: }
2022: else
2023: *pp = 0;
2024: return p;
2025: }
2026: #endif
2027:
1.126 brouard 2028: /********************** nrerror ********************/
2029:
2030: void nrerror(char error_text[])
2031: {
2032: fprintf(stderr,"ERREUR ...\n");
2033: fprintf(stderr,"%s\n",error_text);
2034: exit(EXIT_FAILURE);
2035: }
2036: /*********************** vector *******************/
2037: double *vector(int nl, int nh)
2038: {
2039: double *v;
2040: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2041: if (!v) nrerror("allocation failure in vector");
2042: return v-nl+NR_END;
2043: }
2044:
2045: /************************ free vector ******************/
2046: void free_vector(double*v, int nl, int nh)
2047: {
2048: free((FREE_ARG)(v+nl-NR_END));
2049: }
2050:
2051: /************************ivector *******************************/
2052: int *ivector(long nl,long nh)
2053: {
2054: int *v;
2055: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2056: if (!v) nrerror("allocation failure in ivector");
2057: return v-nl+NR_END;
2058: }
2059:
2060: /******************free ivector **************************/
2061: void free_ivector(int *v, long nl, long nh)
2062: {
2063: free((FREE_ARG)(v+nl-NR_END));
2064: }
2065:
2066: /************************lvector *******************************/
2067: long *lvector(long nl,long nh)
2068: {
2069: long *v;
2070: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2071: if (!v) nrerror("allocation failure in ivector");
2072: return v-nl+NR_END;
2073: }
2074:
2075: /******************free lvector **************************/
2076: void free_lvector(long *v, long nl, long nh)
2077: {
2078: free((FREE_ARG)(v+nl-NR_END));
2079: }
2080:
2081: /******************* imatrix *******************************/
2082: int **imatrix(long nrl, long nrh, long ncl, long nch)
2083: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2084: {
2085: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2086: int **m;
2087:
2088: /* allocate pointers to rows */
2089: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2090: if (!m) nrerror("allocation failure 1 in matrix()");
2091: m += NR_END;
2092: m -= nrl;
2093:
2094:
2095: /* allocate rows and set pointers to them */
2096: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2097: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2098: m[nrl] += NR_END;
2099: m[nrl] -= ncl;
2100:
2101: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2102:
2103: /* return pointer to array of pointers to rows */
2104: return m;
2105: }
2106:
2107: /****************** free_imatrix *************************/
2108: void free_imatrix(m,nrl,nrh,ncl,nch)
2109: int **m;
2110: long nch,ncl,nrh,nrl;
2111: /* free an int matrix allocated by imatrix() */
2112: {
2113: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2114: free((FREE_ARG) (m+nrl-NR_END));
2115: }
2116:
2117: /******************* matrix *******************************/
2118: double **matrix(long nrl, long nrh, long ncl, long nch)
2119: {
2120: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2121: double **m;
2122:
2123: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2124: if (!m) nrerror("allocation failure 1 in matrix()");
2125: m += NR_END;
2126: m -= nrl;
2127:
2128: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2129: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2130: m[nrl] += NR_END;
2131: m[nrl] -= ncl;
2132:
2133: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2134: return m;
1.145 brouard 2135: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2136: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2137: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2138: */
2139: }
2140:
2141: /*************************free matrix ************************/
2142: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2143: {
2144: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2145: free((FREE_ARG)(m+nrl-NR_END));
2146: }
2147:
2148: /******************* ma3x *******************************/
2149: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2150: {
2151: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2152: double ***m;
2153:
2154: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2155: if (!m) nrerror("allocation failure 1 in matrix()");
2156: m += NR_END;
2157: m -= nrl;
2158:
2159: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2160: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2161: m[nrl] += NR_END;
2162: m[nrl] -= ncl;
2163:
2164: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2165:
2166: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2167: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2168: m[nrl][ncl] += NR_END;
2169: m[nrl][ncl] -= nll;
2170: for (j=ncl+1; j<=nch; j++)
2171: m[nrl][j]=m[nrl][j-1]+nlay;
2172:
2173: for (i=nrl+1; i<=nrh; i++) {
2174: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2175: for (j=ncl+1; j<=nch; j++)
2176: m[i][j]=m[i][j-1]+nlay;
2177: }
2178: return m;
2179: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2180: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2181: */
2182: }
2183:
2184: /*************************free ma3x ************************/
2185: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2186: {
2187: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2188: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2189: free((FREE_ARG)(m+nrl-NR_END));
2190: }
2191:
2192: /*************** function subdirf ***********/
2193: char *subdirf(char fileres[])
2194: {
2195: /* Caution optionfilefiname is hidden */
2196: strcpy(tmpout,optionfilefiname);
2197: strcat(tmpout,"/"); /* Add to the right */
2198: strcat(tmpout,fileres);
2199: return tmpout;
2200: }
2201:
2202: /*************** function subdirf2 ***********/
2203: char *subdirf2(char fileres[], char *preop)
2204: {
1.314 brouard 2205: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2206: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2207: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2208: /* Caution optionfilefiname is hidden */
2209: strcpy(tmpout,optionfilefiname);
2210: strcat(tmpout,"/");
2211: strcat(tmpout,preop);
2212: strcat(tmpout,fileres);
2213: return tmpout;
2214: }
2215:
2216: /*************** function subdirf3 ***********/
2217: char *subdirf3(char fileres[], char *preop, char *preop2)
2218: {
2219:
2220: /* Caution optionfilefiname is hidden */
2221: strcpy(tmpout,optionfilefiname);
2222: strcat(tmpout,"/");
2223: strcat(tmpout,preop);
2224: strcat(tmpout,preop2);
2225: strcat(tmpout,fileres);
2226: return tmpout;
2227: }
1.213 brouard 2228:
2229: /*************** function subdirfext ***********/
2230: char *subdirfext(char fileres[], char *preop, char *postop)
2231: {
2232:
2233: strcpy(tmpout,preop);
2234: strcat(tmpout,fileres);
2235: strcat(tmpout,postop);
2236: return tmpout;
2237: }
1.126 brouard 2238:
1.213 brouard 2239: /*************** function subdirfext3 ***********/
2240: char *subdirfext3(char fileres[], char *preop, char *postop)
2241: {
2242:
2243: /* Caution optionfilefiname is hidden */
2244: strcpy(tmpout,optionfilefiname);
2245: strcat(tmpout,"/");
2246: strcat(tmpout,preop);
2247: strcat(tmpout,fileres);
2248: strcat(tmpout,postop);
2249: return tmpout;
2250: }
2251:
1.162 brouard 2252: char *asc_diff_time(long time_sec, char ascdiff[])
2253: {
2254: long sec_left, days, hours, minutes;
2255: days = (time_sec) / (60*60*24);
2256: sec_left = (time_sec) % (60*60*24);
2257: hours = (sec_left) / (60*60) ;
2258: sec_left = (sec_left) %(60*60);
2259: minutes = (sec_left) /60;
2260: sec_left = (sec_left) % (60);
2261: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2262: return ascdiff;
2263: }
2264:
1.126 brouard 2265: /***************** f1dim *************************/
2266: extern int ncom;
2267: extern double *pcom,*xicom;
2268: extern double (*nrfunc)(double []);
2269:
2270: double f1dim(double x)
2271: {
2272: int j;
2273: double f;
2274: double *xt;
2275:
2276: xt=vector(1,ncom);
2277: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2278: f=(*nrfunc)(xt);
2279: free_vector(xt,1,ncom);
2280: return f;
2281: }
2282:
2283: /*****************brent *************************/
2284: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2285: {
2286: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2287: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2288: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2289: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2290: * returned function value.
2291: */
1.126 brouard 2292: int iter;
2293: double a,b,d,etemp;
1.159 brouard 2294: double fu=0,fv,fw,fx;
1.164 brouard 2295: double ftemp=0.;
1.126 brouard 2296: double p,q,r,tol1,tol2,u,v,w,x,xm;
2297: double e=0.0;
2298:
2299: a=(ax < cx ? ax : cx);
2300: b=(ax > cx ? ax : cx);
2301: x=w=v=bx;
2302: fw=fv=fx=(*f)(x);
2303: for (iter=1;iter<=ITMAX;iter++) {
2304: xm=0.5*(a+b);
2305: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2306: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2307: printf(".");fflush(stdout);
2308: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2309: #ifdef DEBUGBRENT
1.126 brouard 2310: printf("br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
2311: fprintf(ficlog,"br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
2312: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2313: #endif
2314: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2315: *xmin=x;
2316: return fx;
2317: }
2318: ftemp=fu;
2319: if (fabs(e) > tol1) {
2320: r=(x-w)*(fx-fv);
2321: q=(x-v)*(fx-fw);
2322: p=(x-v)*q-(x-w)*r;
2323: q=2.0*(q-r);
2324: if (q > 0.0) p = -p;
2325: q=fabs(q);
2326: etemp=e;
2327: e=d;
2328: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2329: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2330: else {
1.224 brouard 2331: d=p/q;
2332: u=x+d;
2333: if (u-a < tol2 || b-u < tol2)
2334: d=SIGN(tol1,xm-x);
1.126 brouard 2335: }
2336: } else {
2337: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2338: }
2339: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2340: fu=(*f)(u);
2341: if (fu <= fx) {
2342: if (u >= x) a=x; else b=x;
2343: SHFT(v,w,x,u)
1.183 brouard 2344: SHFT(fv,fw,fx,fu)
2345: } else {
2346: if (u < x) a=u; else b=u;
2347: if (fu <= fw || w == x) {
1.224 brouard 2348: v=w;
2349: w=u;
2350: fv=fw;
2351: fw=fu;
1.183 brouard 2352: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2353: v=u;
2354: fv=fu;
1.183 brouard 2355: }
2356: }
1.126 brouard 2357: }
2358: nrerror("Too many iterations in brent");
2359: *xmin=x;
2360: return fx;
2361: }
2362:
2363: /****************** mnbrak ***********************/
2364:
2365: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2366: double (*func)(double))
1.183 brouard 2367: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2368: the downhill direction (defined by the function as evaluated at the initial points) and returns
2369: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2370: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2371: */
1.126 brouard 2372: double ulim,u,r,q, dum;
2373: double fu;
1.187 brouard 2374:
2375: double scale=10.;
2376: int iterscale=0;
2377:
2378: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2379: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2380:
2381:
2382: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2383: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2384: /* *bx = *ax - (*ax - *bx)/scale; */
2385: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2386: /* } */
2387:
1.126 brouard 2388: if (*fb > *fa) {
2389: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2390: SHFT(dum,*fb,*fa,dum)
2391: }
1.126 brouard 2392: *cx=(*bx)+GOLD*(*bx-*ax);
2393: *fc=(*func)(*cx);
1.183 brouard 2394: #ifdef DEBUG
1.224 brouard 2395: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2396: fprintf(ficlog,"mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1.183 brouard 2397: #endif
1.224 brouard 2398: while (*fb > *fc) { /* Declining a,b,c with fa> fb > fc. If fc=inf it exits and if flat fb=fc it exits too.*/
1.126 brouard 2399: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2400: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2401: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2402: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2403: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2404: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2405: fu=(*func)(u);
1.163 brouard 2406: #ifdef DEBUG
2407: /* f(x)=A(x-u)**2+f(u) */
2408: double A, fparabu;
2409: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2410: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2411: printf("\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
2412: fprintf(ficlog,"\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
1.183 brouard 2413: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2414: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2415: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2416: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2417: #endif
1.184 brouard 2418: #ifdef MNBRAKORIGINAL
1.183 brouard 2419: #else
1.191 brouard 2420: /* if (fu > *fc) { */
2421: /* #ifdef DEBUG */
2422: /* printf("mnbrak4 fu > fc \n"); */
2423: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2424: /* #endif */
2425: /* /\* SHFT(u,*cx,*cx,u) /\\* ie a=c, c=u and u=c; in that case, next SHFT(a,b,c,u) will give a=b=b, b=c=u, c=u=c and *\\/ *\/ */
2426: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2427: /* dum=u; /\* Shifting c and u *\/ */
2428: /* u = *cx; */
2429: /* *cx = dum; */
2430: /* dum = fu; */
2431: /* fu = *fc; */
2432: /* *fc =dum; */
2433: /* } else { /\* end *\/ */
2434: /* #ifdef DEBUG */
2435: /* printf("mnbrak3 fu < fc \n"); */
2436: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2437: /* #endif */
2438: /* dum=u; /\* Shifting c and u *\/ */
2439: /* u = *cx; */
2440: /* *cx = dum; */
2441: /* dum = fu; */
2442: /* fu = *fc; */
2443: /* *fc =dum; */
2444: /* } */
1.224 brouard 2445: #ifdef DEBUGMNBRAK
2446: double A, fparabu;
2447: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2448: fparabu= *fa - A*(*ax-u)*(*ax-u);
2449: printf("\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
2450: fprintf(ficlog,"\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
1.183 brouard 2451: #endif
1.191 brouard 2452: dum=u; /* Shifting c and u */
2453: u = *cx;
2454: *cx = dum;
2455: dum = fu;
2456: fu = *fc;
2457: *fc =dum;
1.183 brouard 2458: #endif
1.162 brouard 2459: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2460: #ifdef DEBUG
1.224 brouard 2461: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2462: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2463: #endif
1.126 brouard 2464: fu=(*func)(u);
2465: if (fu < *fc) {
1.183 brouard 2466: #ifdef DEBUG
1.224 brouard 2467: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2468: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2469: #endif
2470: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2471: SHFT(*fb,*fc,fu,(*func)(u))
2472: #ifdef DEBUG
2473: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2474: #endif
2475: }
1.162 brouard 2476: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2477: #ifdef DEBUG
1.224 brouard 2478: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2479: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2480: #endif
1.126 brouard 2481: u=ulim;
2482: fu=(*func)(u);
1.183 brouard 2483: } else { /* u could be left to b (if r > q parabola has a maximum) */
2484: #ifdef DEBUG
1.224 brouard 2485: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2486: fprintf(ficlog,"\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1.183 brouard 2487: #endif
1.126 brouard 2488: u=(*cx)+GOLD*(*cx-*bx);
2489: fu=(*func)(u);
1.224 brouard 2490: #ifdef DEBUG
2491: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2492: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2493: #endif
1.183 brouard 2494: } /* end tests */
1.126 brouard 2495: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2496: SHFT(*fa,*fb,*fc,fu)
2497: #ifdef DEBUG
1.224 brouard 2498: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2499: fprintf(ficlog, "\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
1.183 brouard 2500: #endif
2501: } /* end while; ie return (a, b, c, fa, fb, fc) such that a < b < c with f(a) > f(b) and fb < f(c) */
1.126 brouard 2502: }
2503:
2504: /*************** linmin ************************/
1.162 brouard 2505: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2506: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2507: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2508: the value of func at the returned location p . This is actually all accomplished by calling the
2509: routines mnbrak and brent .*/
1.126 brouard 2510: int ncom;
2511: double *pcom,*xicom;
2512: double (*nrfunc)(double []);
2513:
1.224 brouard 2514: #ifdef LINMINORIGINAL
1.126 brouard 2515: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2516: #else
2517: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2518: #endif
1.126 brouard 2519: {
2520: double brent(double ax, double bx, double cx,
2521: double (*f)(double), double tol, double *xmin);
2522: double f1dim(double x);
2523: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2524: double *fc, double (*func)(double));
2525: int j;
2526: double xx,xmin,bx,ax;
2527: double fx,fb,fa;
1.187 brouard 2528:
1.203 brouard 2529: #ifdef LINMINORIGINAL
2530: #else
2531: double scale=10., axs, xxs; /* Scale added for infinity */
2532: #endif
2533:
1.126 brouard 2534: ncom=n;
2535: pcom=vector(1,n);
2536: xicom=vector(1,n);
2537: nrfunc=func;
2538: for (j=1;j<=n;j++) {
2539: pcom[j]=p[j];
1.202 brouard 2540: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2541: }
1.187 brouard 2542:
1.203 brouard 2543: #ifdef LINMINORIGINAL
2544: xx=1.;
2545: #else
2546: axs=0.0;
2547: xxs=1.;
2548: do{
2549: xx= xxs;
2550: #endif
1.187 brouard 2551: ax=0.;
2552: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2553: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2554: /* xt[x,j]=pcom[j]+x*xicom[j] f(ax) = f(xt(a,j=1,n)) = f(p(j) + 0 * xi(j)) and f(xx) = f(xt(x, j=1,n)) = f(p(j) + 1 * xi(j)) */
2555: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2556: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2557: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2558: /* Find a bracket a,x,b in direction n=xi ie xicom, order may change. Scale is [0:xxs*xi[j]] et non plus [0:xi[j]]*/
1.203 brouard 2559: #ifdef LINMINORIGINAL
2560: #else
2561: if (fx != fx){
1.224 brouard 2562: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2563: printf("|");
2564: fprintf(ficlog,"|");
1.203 brouard 2565: #ifdef DEBUGLINMIN
1.224 brouard 2566: printf("\nLinmin NAN : input [axs=%lf:xxs=%lf], mnbrak outputs fx=%lf <(fb=%lf and fa=%lf) with xx=%lf in [ax=%lf:bx=%lf] \n", axs, xxs, fx,fb, fa, xx, ax, bx);
1.203 brouard 2567: #endif
2568: }
1.224 brouard 2569: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2570: #endif
2571:
1.191 brouard 2572: #ifdef DEBUGLINMIN
2573: printf("\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
1.202 brouard 2574: fprintf(ficlog,"\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
1.191 brouard 2575: #endif
1.224 brouard 2576: #ifdef LINMINORIGINAL
2577: #else
1.317 brouard 2578: if(fb == fx){ /* Flat function in the direction */
2579: xmin=xx;
1.224 brouard 2580: *flat=1;
1.317 brouard 2581: }else{
1.224 brouard 2582: *flat=0;
2583: #endif
2584: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2585: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2586: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2587: /* fmin = f(p[j] + xmin * xi[j]) */
2588: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2589: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2590: #ifdef DEBUG
1.224 brouard 2591: printf("retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
2592: fprintf(ficlog,"retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
2593: #endif
2594: #ifdef LINMINORIGINAL
2595: #else
2596: }
1.126 brouard 2597: #endif
1.191 brouard 2598: #ifdef DEBUGLINMIN
2599: printf("linmin end ");
1.202 brouard 2600: fprintf(ficlog,"linmin end ");
1.191 brouard 2601: #endif
1.126 brouard 2602: for (j=1;j<=n;j++) {
1.203 brouard 2603: #ifdef LINMINORIGINAL
2604: xi[j] *= xmin;
2605: #else
2606: #ifdef DEBUGLINMIN
2607: if(xxs <1.0)
2608: printf(" before xi[%d]=%12.8f", j,xi[j]);
2609: #endif
2610: xi[j] *= xmin*xxs; /* xi rescaled by xmin and number of loops: if xmin=-1.237 and xi=(1,0,...,0) xi=(-1.237,0,...,0) */
2611: #ifdef DEBUGLINMIN
2612: if(xxs <1.0)
2613: printf(" after xi[%d]=%12.8f, xmin=%12.8f, ax=%12.8f, xx=%12.8f, bx=%12.8f, xxs=%12.8f", j,xi[j], xmin, ax, xx, bx,xxs );
2614: #endif
2615: #endif
1.187 brouard 2616: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2617: }
1.191 brouard 2618: #ifdef DEBUGLINMIN
1.203 brouard 2619: printf("\n");
1.191 brouard 2620: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2621: fprintf(ficlog,"Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.191 brouard 2622: for (j=1;j<=n;j++) {
1.202 brouard 2623: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2624: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2625: if(j % ncovmodel == 0){
1.191 brouard 2626: printf("\n");
1.202 brouard 2627: fprintf(ficlog,"\n");
2628: }
1.191 brouard 2629: }
1.203 brouard 2630: #else
1.191 brouard 2631: #endif
1.126 brouard 2632: free_vector(xicom,1,n);
2633: free_vector(pcom,1,n);
2634: }
2635:
1.359 brouard 2636: /**** praxis gegen ****/
2637:
2638: /* This has been tested by Visual C from Microsoft and works */
2639: /* meaning tha valgrind could be wrong */
2640: /*********************************************************************/
2641: /* f u n c t i o n p r a x i s */
2642: /* */
2643: /* praxis is a general purpose routine for the minimization of a */
2644: /* function in several variables. the algorithm used is a modifi- */
2645: /* cation of conjugate gradient search method by powell. the changes */
2646: /* are due to r.p. brent, who gives an algol-w program, which served */
2647: /* as a basis for this function. */
2648: /* */
2649: /* references: */
2650: /* - powell, m.j.d., 1964. an efficient method for finding */
2651: /* the minimum of a function in several variables without */
2652: /* calculating derivatives, computer journal, 7, 155-162 */
2653: /* - brent, r.p., 1973. algorithms for minimization without */
2654: /* derivatives, prentice hall, englewood cliffs. */
2655: /* */
2656: /* problems, suggestions or improvements are always wellcome */
2657: /* karl gegenfurtner 07/08/87 */
2658: /* c - version */
2659: /*********************************************************************/
2660: /* */
2661: /* usage: min = praxis(tol, macheps, h, n, prin, x, func) */
2662: /* macheps has been suppressed because it is replaced by DBL_EPSILON */
2663: /* and if it was an argument of praxis (as it is in original brent) */
2664: /* it should be declared external */
2665: /* usage: min = praxis(tol, h, n, prin, x, func) */
2666: /* was min = praxis(fun, x, n); */
2667: /* */
2668: /* fun the function to be minimized. fun is called from */
2669: /* praxis with x and n as arguments */
2670: /* x a double array containing the initial guesses for */
2671: /* the minimum, which will contain the solution on */
2672: /* return */
2673: /* n an integer specifying the number of unknown */
2674: /* parameters */
2675: /* min praxis returns the least calculated value of fun */
2676: /* */
2677: /* some additional global variables control some more aspects of */
2678: /* the inner workings of praxis. setting them is optional, they */
2679: /* are all set to some reasonable default values given below. */
2680: /* */
2681: /* prin controls the printed output from the routine. */
2682: /* 0 -> no output */
2683: /* 1 -> print only starting and final values */
2684: /* 2 -> detailed map of the minimization process */
2685: /* 3 -> print also eigenvalues and vectors of the */
2686: /* search directions */
2687: /* the default value is 1 */
2688: /* tol is the tolerance allowed for the precision of the */
2689: /* solution. praxis returns if the criterion */
2690: /* 2 * ||x[k]-x[k-1]|| <= sqrt(macheps) * ||x[k]|| + tol */
2691: /* is fulfilled more than ktm times. */
2692: /* the default value depends on the machine precision */
2693: /* ktm see just above. default is 1, and a value of 4 leads */
2694: /* to a very(!) cautious stopping criterion. */
2695: /* h0 or step is a steplength parameter and should be set equal */
2696: /* to the expected distance from the solution. */
2697: /* exceptionally small or large values of step lead to */
2698: /* slower convergence on the first few iterations */
2699: /* the default value for step is 1.0 */
2700: /* scbd is a scaling parameter. 1.0 is the default and */
2701: /* indicates no scaling. if the scales for the different */
2702: /* parameters are very different, scbd should be set to */
2703: /* a value of about 10.0. */
2704: /* illc should be set to true (1) if the problem is known to */
2705: /* be ill-conditioned. the default is false (0). this */
2706: /* variable is automatically set, when praxis finds */
2707: /* the problem to be ill-conditioned during iterations. */
2708: /* maxfun is the maximum number of calls to fun allowed. praxis */
2709: /* will return after maxfun calls to fun even when the */
2710: /* minimum is not yet found. the default value of 0 */
2711: /* indicates no limit on the number of calls. */
2712: /* this return condition is only checked every n */
2713: /* iterations. */
2714: /* */
2715: /*********************************************************************/
2716:
2717: #include <math.h>
2718: #include <stdio.h>
2719: #include <stdlib.h>
2720: #include <float.h> /* for DBL_EPSILON */
2721: /* #include "machine.h" */
2722:
2723:
2724: /* extern void minfit(int n, double eps, double tol, double **ab, double q[]); */
2725: /* extern void minfit(int n, double eps, double tol, double ab[N][N], double q[]); */
2726: /* control parameters */
2727: /* control parameters */
2728: #define SQREPSILON 1.0e-19
2729: /* #define EPSILON 1.0e-8 */ /* in main */
2730:
2731: double tol = SQREPSILON,
2732: scbd = 1.0,
2733: step = 1.0;
2734: int ktm = 1,
2735: /* prin = 2, */
2736: maxfun = 0,
2737: illc = 0;
2738:
2739: /* some global variables */
2740: static int i, j, k, k2, nl, nf, kl, kt;
2741: /* static double s; */
2742: double sl, dn, dmin,
2743: fx, f1, lds, ldt, sf, df,
2744: qf1, qd0, qd1, qa, qb, qc,
2745: m2, m4, small_windows, vsmall, large,
2746: vlarge, ldfac, t2;
2747: /* static double d[N], y[N], z[N], */
2748: /* q0[N], q1[N], v[N][N]; */
2749:
2750: static double *d, *y, *z;
2751: static double *q0, *q1, **v;
2752: double *tflin; /* used in flin: return (*fun)(tflin, n); */
2753: double *e; /* used in minfit, don't konw how to free memory and thus made global */
2754: /* static double s, sl, dn, dmin, */
2755: /* fx, f1, lds, ldt, sf, df, */
2756: /* qf1, qd0, qd1, qa, qb, qc, */
2757: /* m2, m4, small, vsmall, large, */
2758: /* vlarge, ldfac, t2; */
2759: /* static double d[N], y[N], z[N], */
2760: /* q0[N], q1[N], v[N][N]; */
2761:
2762: /* these will be set by praxis to point to it's arguments */
2763: static int prin; /* added */
2764: static int n;
2765: static double *x;
2766: static double (*fun)();
2767: /* static double (*fun)(double *x, int n); */
2768:
2769: /* these will be set by praxis to the global control parameters */
2770: /* static double h, macheps, t; */
2771: extern double macheps;
2772: static double h;
2773: static double t;
2774:
2775: static double
2776: drandom() /* return random no between 0 and 1 */
2777: {
2778: return (double)(rand()%(8192*2))/(double)(8192*2);
2779: }
2780:
2781: static void sort() /* d and v in descending order */
2782: {
2783: int k, i, j;
2784: double s;
2785:
2786: for (i=1; i<=n-1; i++) {
2787: k = i; s = d[i];
2788: for (j=i+1; j<=n; j++) {
2789: if (d[j] > s) {
2790: k = j;
2791: s = d[j];
2792: }
2793: }
2794: if (k > i) {
2795: d[k] = d[i];
2796: d[i] = s;
2797: for (j=1; j<=n; j++) {
2798: s = v[j][i];
2799: v[j][i] = v[j][k];
2800: v[j][k] = s;
2801: }
2802: }
2803: }
2804: }
2805:
2806: double randbrent ( int *naught )
2807: {
2808: double ran1, ran3[127], half;
2809: int ran2, q, r, i, j;
2810: int init=0; /* false */
2811: double rr;
2812: /* REAL*8 RAN1,RAN3(127),HALF */
2813:
2814: /* INTEGER RAN2,Q,R */
2815: /* LOGICAL INIT */
2816: /* DATA INIT/.FALSE./ */
2817: /* IF (INIT) GO TO 3 */
2818: if(!init){
2819: /* R = MOD(NAUGHT,8190) + 1 *//* 1804289383 rand () */
2820: r = *naught % 8190 + 1;/* printf(" naught r %d %d",*naught,r); */
2821: ran2=127;
2822: for(i=ran2; i>0; i--){
2823: /* RAN2 = 128 */
2824: /* DO 2 I=1,127 */
2825: ran2 = ran2-1;
2826: /* RAN2 = RAN2 - 1 */
2827: ran1 = -pow(2.0,55);
2828: /* RAN1 = -2.D0**55 */
2829: /* DO 1 J=1,7 */
2830: for(j=1; j<=7;j++){
2831: /* R = MOD(1756*R,8191) */
2832: r = (1756*r) % 8191;/* printf(" i=%d (1756*r)%8191=%d",j,r); */
2833: q=r/32;
2834: /* Q = R/32 */
2835: /* 1 RAN1 = (RAN1 + Q)*(1.0D0/256) */
2836: ran1 =(ran1+q)*(1.0/256);
2837: }
2838: /* 2 RAN3(RAN2) = RAN1 */
2839: ran3[ran2] = ran1; /* printf(" ran2=%d ran1=%.7g \n",ran2,ran1); */
2840: }
2841: /* INIT = .TRUE. */
2842: init=1;
2843: /* 3 IF (RAN2.EQ.1) RAN2 = 128 */
2844: }
2845: if(ran2 == 0) ran2 = 126;
2846: else ran2 = ran2 -1;
2847: /* RAN2 = RAN2 - 1 */
2848: /* RAN1 = RAN1 + RAN3(RAN2) */
2849: ran1 = ran1 + ran3[ran2];/* printf("BIS ran2=%d ran1=%.7g \n",ran2,ran1); */
2850: half= 0.5;
2851: /* HALF = .5D0 */
2852: /* IF (RAN1.GE.0.D0) HALF = -HALF */
2853: if(ran1 >= 0.) half =-half;
2854: ran1 = ran1 +half;
2855: ran3[ran2] = ran1;
2856: rr= ran1+0.5;
2857: /* RAN1 = RAN1 + HALF */
2858: /* RAN3(RAN2) = RAN1 */
2859: /* RANDOM = RAN1 + .5D0 */
2860: /* r = ( ( double ) ( *seed ) ) * 4.656612875E-10; */
2861: return rr;
2862: }
2863: static void matprint(char *s, double **v, int m, int n)
2864: /* char *s; */
2865: /* double v[N][N]; */
2866: {
2867: #define INCX 8
2868: int i;
2869:
2870: int i2hi;
2871: int ihi;
2872: int ilo;
2873: int i2lo;
2874: int jlo=1;
2875: int j;
2876: int j2hi;
2877: int jhi;
2878: int j2lo;
2879: ilo=1;
2880: ihi=n;
2881: jlo=1;
2882: jhi=n;
2883:
2884: printf ("\n" );
2885: printf ("%s\n", s );
2886: for ( j2lo = jlo; j2lo <= jhi; j2lo = j2lo + INCX )
2887: {
2888: j2hi = j2lo + INCX - 1;
2889: if ( n < j2hi )
2890: {
2891: j2hi = n;
2892: }
2893: if ( jhi < j2hi )
2894: {
2895: j2hi = jhi;
2896: }
2897:
2898: /* fprintf ( ficlog, "\n" ); */
2899: printf ("\n" );
2900: /*
2901: For each column J in the current range...
2902:
2903: Write the header.
2904: */
2905: /* fprintf ( ficlog, " Col: "); */
2906: printf ("Col:");
2907: for ( j = j2lo; j <= j2hi; j++ )
2908: {
2909: /* fprintf ( ficlog, " %7d ", j - 1 ); */
2910: /* printf (" %9d ", j - 1 ); */
2911: printf (" %9d ", j );
2912: }
2913: /* fprintf ( ficlog, "\n" ); */
2914: /* fprintf ( ficlog, " Row\n" ); */
2915: /* fprintf ( ficlog, "\n" ); */
2916: printf ("\n" );
2917: printf (" Row\n" );
2918: printf ("\n" );
2919: /*
2920: Determine the range of the rows in this strip.
2921: */
2922: if ( 1 < ilo ){
2923: i2lo = ilo;
2924: }else{
2925: i2lo = 1;
2926: }
2927: if ( m < ihi ){
2928: i2hi = m;
2929: }else{
2930: i2hi = ihi;
2931: }
2932:
2933: for ( i = i2lo; i <= i2hi; i++ ){
2934: /*
2935: Print out (up to) 5 entries in row I, that lie in the current strip.
2936: */
2937: /* fprintf ( ficlog, "%5d:", i - 1 ); */
2938: /* printf ("%5d:", i - 1 ); */
2939: printf ("%5d:", i );
2940: for ( j = j2lo; j <= j2hi; j++ )
2941: {
2942: /* fprintf ( ficlog, " %14g", a[i-1+(j-1)*m] ); */
2943: /* printf ("%14.7g ", a[i-1+(j-1)*m] ); */
2944: /* printf("%14.7f ", v[i-1][j-1]); */
2945: printf("%14.7f ", v[i][j]);
2946: /* fprintf ( stdout, " %14g", a[i-1+(j-1)*m] ); */
2947: }
2948: /* fprintf ( ficlog, "\n" ); */
2949: printf ("\n" );
2950: }
2951: }
2952:
2953: /* printf("%s\n", s); */
2954: /* for (k=0; k<n; k++) { */
2955: /* for (i=0; i<n; i++) { */
2956: /* /\* printf("%20.10e ", v[k][i]); *\/ */
2957: /* } */
2958: /* printf("\n"); */
2959: /* } */
2960: #undef INCX
2961: }
2962:
2963: void vecprint(char *s, double *x, int n)
2964: /* char *s; */
2965: /* double x[N]; */
2966: {
2967: int i=0;
2968:
2969: printf(" %s", s);
2970: /* for (i=0; i<n; i++) */
2971: for (i=1; i<=n; i++)
2972: printf (" %14.7g", x[i] );
2973: /* printf(" %8d: %14g\n", i, x[i]); */
2974: printf ("\n" );
2975: }
2976:
2977: static void print() /* print a line of traces */
2978: {
2979:
2980:
2981: printf("\n");
2982: /* printf("... chi square reduced to ... %20.10e\n", fx); */
2983: /* printf("... after %u function calls ...\n", nf); */
2984: /* printf("... including %u linear searches ...\n", nl); */
2985: printf("%10d %10d%14.7g",nl, nf, fx);
2986: vecprint("... current values of x ...", x, n);
2987: }
2988: /* static void print2(int n, double *x, int prin, double fx, int nf, int nl) */ /* print a line of traces */
2989: static void print2() /* print a line of traces */
2990: {
2991: int i; double fmin=0.;
2992:
2993: /* printf("\n"); */
2994: /* printf("... chi square reduced to ... %20.10e\n", fx); */
2995: /* printf("... after %u function calls ...\n", nf); */
2996: /* printf("... including %u linear searches ...\n", nl); */
2997: /* printf("%10d %10d%14.7g",nl, nf, fx); */
2998: printf ( "\n" );
2999: printf ( " Linear searches %d", nl );
3000: /* printf ( " Linear searches %d\n", nl ); */
3001: /* printf ( " Function evaluations %d\n", nf ); */
3002: /* printf ( " Function value FX = %g\n", fx ); */
3003: printf ( " Function evaluations %d", nf );
3004: printf ( " Function value FX = %.12lf\n", fx );
3005: #ifdef DEBUGPRAX
3006: printf("n=%d prin=%d\n",n,prin);
3007: #endif
3008: if(fx <= fmin) printf(" UNDEFINED "); else printf("%14.7g",log(fx-fmin));
3009: if ( n <= 4 || 2 < prin )
3010: {
3011: /* for(i=1;i<=n;i++)printf("%14.7g",x[i-1]); */
3012: for(i=1;i<=n;i++)printf("%14.7g",x[i]);
3013: /* r8vec_print ( n, x, " X:" ); */
3014: }
3015: printf("\n");
3016: }
3017:
3018:
3019: /* #ifdef MSDOS */
3020: /* static double tflin[N]; */
3021: /* #endif */
3022:
3023: static double flin(double l, int j)
3024: /* double l; */
3025: {
3026: int i;
3027: /* #ifndef MSDOS */
3028: /* double tflin[N]; */
3029: /* #endif */
3030: /* double *tflin; */ /* Be careful to put tflin on a vector n */
3031:
3032: /* j is used from 0 to n-1 and can be -1 for parabolic search */
3033:
3034: /* if (j != -1) { /\* linear search *\/ */
3035: if (j > 0) { /* linear search */
3036: /* for (i=0; i<n; i++){ */
3037: for (i=1; i<=n; i++){
3038: tflin[i] = x[i] + l *v[i][j];
3039: #ifdef DEBUGPRAX
3040: /* printf(" flin i=%14d t=%14.7f x=%14.7f l=%14.7f v[%d,%d]=%14.7f nf=%14d\n",i+1, tflin[i],x[i],l,i,j,v[i][j],nf); */
3041: printf(" flin i=%14d t=%14.7f x=%14.7f l=%14.7f v[%d,%d]=%14.7f nf=%14d\n",i, tflin[i],x[i],l,i,j,v[i][j],nf);
3042: #endif
3043: }
3044: }
3045: else { /* search along parabolic space curve */
3046: qa = l*(l-qd1)/(qd0*(qd0+qd1));
3047: qb = (l+qd0)*(qd1-l)/(qd0*qd1);
3048: qc = l*(l+qd0)/(qd1*(qd0+qd1));
3049: #ifdef DEBUGPRAX
3050: printf(" search along a parabolic space curve. j=%14d nf=%14d l=%14.7f qd0=%14.7f qd1=%14.7f\n",j,nf,l,qd0,qd1);
3051: #endif
3052: /* for (i=0; i<n; i++){ */
3053: for (i=1; i<=n; i++){
3054: tflin[i] = qa*q0[i]+qb*x[i]+qc*q1[i];
3055: #ifdef DEBUGPRAX
3056: /* printf(" parabole i=%14d t(i)=%14.7f q0=%14.7f x=%14.7f q1=%14.7f\n",i+1,tflin[i],q0[i],x[i],q1[i]); */
3057: printf(" parabole i=%14d t(i)=%14.7e q0=%14.7e x=%14.7e q1=%14.7e\n",i,tflin[i],q0[i],x[i],q1[i]);
3058: #endif
3059: }
3060: }
3061: nf++;
3062:
3063: #ifdef NR_SHIFT
3064: return (*fun)((tflin-1), n);
3065: #else
3066: /* return (*fun)(tflin, n);*/
3067: return (*fun)(tflin);
3068: #endif
3069: }
3070:
3071: void minny(int j, int nits, double *d2, double *x1, double f1, int fk)
3072: /* double *d2, *x1, f1; */
3073: {
3074: /* here j is from 0 to n-1 and can be -1 for parabolic search */
3075: /* MINIMIZES F FROM X IN THE DIRECTION V(*,J) */
3076: /* UNLESS J<1, WHEN A QUADRATIC SEARCH IS DONE */
3077: /* IN THE PLANE DEFINED BY Q0, Q1 AND X. */
3078: /* D2 AN APPROXIMATION TO HALF F'' (OR ZERO), */
3079: /* X1 AN ESTIMATE OF DISTANCE TO MINIMUM, */
3080: /* RETURNED AS THE DISTANCE FOUND. */
3081: /* IF FK = TRUE THEN F1 IS FLIN(X1), OTHERWISE */
3082: /* X1 AND F1 ARE IGNORED ON ENTRY UNLESS FINAL */
3083: /* FX > F1. NITS CONTROLS THE NUMBER OF TIMES */
3084: /* AN ATTEMPT IS MADE TO HALVE THE INTERVAL. */
3085: /* SIDE EFFECTS: USES AND ALTERS X, FX, NF, NL. */
3086: /* IF J < 1 USES VARIABLES Q... . */
3087: /* USES H, N, T, M2, M4, LDT, DMIN, MACHEPS; */
3088: int k, i, dz;
3089: double x2, xm, f0, f2, fm, d1, t2, sf1, sx1;
3090: double s;
3091: double macheps;
3092: macheps=pow(16.0,-13.0);
3093: sf1 = f1; sx1 = *x1;
3094: k = 0; xm = 0.0; fm = f0 = fx; dz = *d2 < macheps;
3095: /* h=1.0;*/ /* To be revised */
3096: #ifdef DEBUGPRAX
3097: /* printf("min macheps=%14g h=%14g step=%14g t=%14g fx=%14g\n",macheps,h, step,t, fx); */
3098: /* Where is fx coming from */
3099: printf(" min macheps=%14g h=%14g t=%14g fx=%.9lf dirj=%d\n",macheps, h, t, fx, j);
3100: matprint(" min vectors:",v,n,n);
3101: #endif
3102: /* find step size */
3103: s = 0.;
3104: /* for (i=0; i<n; i++) s += x[i]*x[i]; */
3105: for (i=1; i<=n; i++) s += x[i]*x[i];
3106: s = sqrt(s);
3107: if (dz)
3108: t2 = m4*sqrt(fabs(fx)/dmin + s*ldt) + m2*ldt;
3109: else
3110: t2 = m4*sqrt(fabs(fx)/(*d2) + s*ldt) + m2*ldt;
3111: s = s*m4 + t;
3112: if (dz && t2 > s) t2 = s;
3113: if (t2 < small_windows) t2 = small_windows;
3114: if (t2 > 0.01*h) t2 = 0.01 * h;
3115: if (fk && f1 <= fm) {
3116: xm = *x1;
3117: fm = f1;
3118: }
3119: #ifdef DEBUGPRAX
3120: printf(" additional flin X1=%14.7f t2=%14.7f *f1=%14.7f fm=%14.7f fk=%d\n",*x1,t2,f1,fm,fk);
3121: #endif
3122: if (!fk || fabs(*x1) < t2) {
3123: *x1 = (*x1 >= 0 ? t2 : -t2);
3124: /* *x1 = (*x1 > 0 ? t2 : -t2); */ /* kind of error */
3125: #ifdef DEBUGPRAX
3126: printf(" additional flin X1=%16.10e dirj=%d fk=%d\n",*x1, j, fk);
3127: #endif
3128: f1 = flin(*x1, j);
3129: #ifdef DEBUGPRAX
3130: printf(" after flin f1=%18.12e dirj=%d fk=%d\n",f1, j,fk);
3131: #endif
3132: }
3133: if (f1 <= fm) {
3134: xm = *x1;
3135: fm = f1;
3136: }
3137: L0: /*L0 loop or next */
3138: /*
3139: Evaluate FLIN at another point and estimate the second derivative.
3140: */
3141: if (dz) {
3142: x2 = (f0 < f1 ? -(*x1) : 2*(*x1));
3143: #ifdef DEBUGPRAX
3144: printf(" additional second flin x2=%14.8e x1=%14.8e f0=%14.8e f1=%18.12e dirj=%d\n",x2,*x1,f0,f1,j);
3145: #endif
3146: f2 = flin(x2, j);
3147: #ifdef DEBUGPRAX
3148: printf(" additional second flin x2=%16.10e x1=%16.10e f1=%18.12e f0=%18.10e f2=%18.10e fm=%18.10e\n",x2, *x1, f1,f0,f2,fm);
3149: #endif
3150: if (f2 <= fm) {
3151: xm = x2;
3152: fm = f2;
3153: }
3154: /* d2 is the curvature or double difference f1 doesn't seem to be accurately computed */
3155: *d2 = (x2*(f1-f0) - (*x1)*(f2-f0))/((*x1)*x2*((*x1)-x2));
3156: #ifdef DEBUGPRAX
3157: double d11,d12;
3158: d11=(f1-f0)/(*x1);d12=(f2-f0)/x2;
3159: printf(" d11=%18.12e d12=%18.12e d11-d12=%18.12e x1-x2=%18.12e (d11-d12)/(x2-(*x1))=%18.12e\n", d11 ,d12, d11-d12, x2-(*x1), (d11-d12)/(x2-(*x1)));
3160: printf(" original computing f1=%18.12e *d2=%16.10e f0=%18.12e f1-f0=%16.10e f2-f0=%16.10e\n",f1,*d2,f0,f1-f0, f2-f0);
3161: double ff1=7.783920622852e+04;
3162: double f1mf0=9.0344736236e-05;
3163: *d2 = (f1mf0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2);
3164: /* *d2 = (ff1-f0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2); */
3165: printf(" simpliff computing *d2=%16.10e f1mf0=%18.12e,f1=f0+f1mf0=%18.12e\n",*d2,f1mf0,f0+f1mf0);
3166: *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2);
3167: printf(" overlifi computing *d2=%16.10e\n",*d2);
3168: #endif
3169: *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2);
3170: }
3171: #ifdef DEBUGPRAX
3172: printf(" additional second flin xm=%14.8e fm=%14.8e *d2=%14.8e\n",xm, fm,*d2);
3173: #endif
3174: /*
3175: Estimate the first derivative at 0.
3176: */
3177: d1 = (f1-f0)/(*x1) - *x1**d2; dz = 1;
3178: /*
3179: Predict the minimum.
3180: */
3181: if (*d2 <= small_windows) {
3182: x2 = (d1 < 0 ? h : -h);
3183: }
3184: else {
3185: x2 = - 0.5*d1/(*d2);
3186: }
3187: #ifdef DEBUGPRAX
3188: printf(" AT d1=%14.8e d2=%14.8e small=%14.8e dz=%d x1=%14.8e x2=%14.8e\n",d1,*d2,small_windows,dz,*x1,x2);
3189: #endif
3190: if (fabs(x2) > h)
3191: x2 = (x2 > 0 ? h : -h);
3192: L1: /* L1 or try loop */
3193: #ifdef DEBUGPRAX
3194: printf(" AT predicted minimum flin x2=%14.8e x1=%14.8e K=%14d NITS=%14d dirj=%d\n",x2,*x1,k,nits,j);
3195: #endif
3196: f2 = flin(x2, j); /* x[i]+x2*v[i][j] */
3197: #ifdef DEBUGPRAX
3198: printf(" after flin f0=%14.8e f1=%14.8e f2=%14.8e fm=%14.8e\n",f0,f1,f2, fm);
3199: #endif
3200: if ((k < nits) && (f2 > f0)) {
3201: #ifdef DEBUGPRAX
3202: printf(" NO SUCCESS SO TRY AGAIN;\n");
3203: #endif
3204: k++;
3205: if ((f0 < f1) && (*x1*x2 > 0.0))
3206: goto L0; /* or next */
3207: x2 *= 0.5;
3208: goto L1;
3209: }
3210: nl++;
3211: #ifdef DEBUGPRAX
3212: printf(" bebeBE end of min x1=%14.8e x2=%14.8e f1=%14.8e f2=%14.8e f0=%14.8e fm=%14.8e d2=%14.8e\n",*x1, x2, f1, f2, f0, fm, *d2);
3213: #endif
3214: if (f2 > fm) x2 = xm; else fm = f2;
3215: if (fabs(x2*(x2-*x1)) > small_windows) {
3216: *d2 = (x2*(f1-f0) - *x1*(fm-f0))/(*x1*x2*(*x1-x2));
3217: }
3218: else {
3219: if (k > 0) *d2 = 0;
3220: }
3221: #ifdef DEBUGPRAX
3222: printf(" bebe end of min x1=%14.8e fx=%14.8e d2=%14.8e\n",*x1, fx, *d2);
3223: #endif
3224: if (*d2 <= small_windows) *d2 = small_windows;
3225: *x1 = x2; fx = fm;
3226: if (sf1 < fx) {
3227: fx = sf1;
3228: *x1 = sx1;
3229: }
3230: /*
3231: Update X for linear search.
3232: */
3233: #ifdef DEBUGPRAX
3234: printf(" end of min x1=%14.8e fx=%14.8e d2=%14.8e\n",*x1, fx, *d2);
3235: #endif
3236:
3237: /* if (j != -1) */
3238: /* for (i=0; i<n; i++) */
3239: /* x[i] += (*x1)*v[i][j]; */
3240: if (j > 0)
3241: for (i=1; i<=n; i++)
3242: x[i] += (*x1)*v[i][j];
3243: }
3244:
3245: void quad() /* look for a minimum along the curve q0, q1, q2 */
3246: {
3247: int i;
3248: double l, s;
3249:
3250: s = fx; fx = qf1; qf1 = s; qd1 = 0.0;
3251: /* for (i=0; i<n; i++) { */
3252: for (i=1; i<=n; i++) {
3253: s = x[i]; l = q1[i]; x[i] = l; q1[i] = s;
3254: qd1 = qd1 + (s-l)*(s-l);
3255: }
3256: s = 0.0; qd1 = sqrt(qd1); l = qd1;
3257: #ifdef DEBUGPRAX
3258: printf(" QUAD after sqrt qd1=%14.8e \n",qd1);
3259: #endif
3260:
3261: if (qd0>0.0 && qd1>0.0 &&nl>=3*n*n) {
3262: #ifdef DEBUGPRAX
3263: printf(" QUAD before min value=%14.8e \n",qf1);
3264: #endif
3265: /* min(-1, 2, &s, &l, qf1, 1); */
3266: minny(0, 2, &s, &l, qf1, 1);
3267: qa = l*(l-qd1)/(qd0*(qd0+qd1));
3268: qb = (l+qd0)*(qd1-l)/(qd0*qd1);
3269: qc = l*(l+qd0)/(qd1*(qd0+qd1));
3270: }
3271: else {
3272: fx = qf1; qa = qb = 0.0; qc = 1.0;
3273: }
3274: #ifdef DEBUGPRAX
3275: printf("after eventual min qd0=%14.8e qd1=%14.8e nl=%d\n",qd0, qd1,nl);
3276: #endif
3277: qd0 = qd1;
3278: /* for (i=0; i<n; i++) { */
3279: for (i=1; i<=n; i++) {
3280: s = q0[i]; q0[i] = x[i];
3281: x[i] = qa*s + qb*x[i] + qc*q1[i];
3282: }
3283: #ifdef DEBUGQUAD
3284: vecprint ( " X after QUAD:" , x, n );
3285: #endif
3286: }
3287:
3288: /* void minfit(int n, double eps, double tol, double ab[N][N], double q[]) */
3289: void minfit(int n, double eps, double tol, double **ab, double q[])
3290: /* int n; */
3291: /* double eps, tol, ab[N][N], q[N]; */
3292: {
3293: int l, kt, l2, i, j, k;
3294: double c, f, g, h, s, x, y, z;
3295: /* double eps; */
3296: /* #ifndef MSDOS */
3297: /* double e[N]; /\* plenty of stack on a vax *\/ */
3298: /* #endif */
3299: /* double *e; */
3300: /* e=vector(0,n-1); /\* should be freed somewhere but gotos *\/ */
3301:
3302: /* householder's reduction to bidiagonal form */
3303:
3304: if(n==1){
3305: /* q[1-1]=ab[1-1][1-1]; */
3306: /* ab[1-1][1-1]=1.0; */
3307: q[1]=ab[1][1];
3308: ab[1][1]=1.0;
3309: return; /* added from hardt */
3310: }
3311: /* eps=macheps; */ /* added */
3312: x = g = 0.0;
3313: #ifdef DEBUGPRAX
3314: matprint (" HOUSE holder:", ab, n, n);
3315: #endif
3316:
3317: /* for (i=0; i<n; i++) { /\* FOR I := 1 UNTIL N DO *\/ */
3318: for (i=1; i<=n; i++) { /* FOR I := 1 UNTIL N DO */
3319: e[i] = g; s = 0.0; l = i+1;
3320: /* for (j=i; j<n; j++) /\* FOR J := I UNTIL N DO S := S*AB(J,I)**2; *\/ /\* not correct *\/ */
3321: for (j=i; j<=n; j++) /* FOR J := I UNTIL N DO S := S*AB(J,I)**2; */ /* not correct */
3322: s += ab[j][i] * ab[j][i];
3323: #ifdef DEBUGPRAXFIN
3324: printf("i=%d s=%d %.7g tol=%.7g",i,s,tol);
3325: #endif
3326: if (s < tol) {
3327: g = 0.0;
3328: }
3329: else {
3330: /* f = ab[i][i]; */
3331: f = ab[i][i];
3332: if (f < 0.0)
3333: g = sqrt(s);
3334: else
3335: g = -sqrt(s);
3336: /* h = f*g - s; ab[i][i] = f - g; */
3337: h = f*g - s; ab[i][i] = f - g;
3338: /* for (j=l; j<n; j++) { */ /* FOR J := L UNTIL N DO */ /* wrong */
3339: for (j=l; j<=n; j++) {
3340: f = 0.0;
3341: /* for (k=i; k<n; k++) /\* FOR K := I UNTIL N DO *\/ /\* wrong *\/ */
3342: for (k=i; k<=n; k++) /* FOR K := I UNTIL N DO */
3343: /* f += ab[k][i] * ab[k][j]; */
3344: f += ab[k][i] * ab[k][j];
3345: f /= h;
3346: for (k=i; k<=n; k++) /* FOR K := I UNTIL N DO */
3347: /* for (k=i; k<n; k++)/\* FOR K := I UNTIL N DO *\/ /\* wrong *\/ */
3348: ab[k][j] += f * ab[k][i];
3349: /* ab[k][j] += f * ab[k][i]; */
3350: #ifdef DEBUGPRAX
3351: printf("Holder J=%d F=%.7g",j,f);
3352: #endif
3353: }
3354: } /* end s */
3355: /* q[i] = g; s = 0.0; */
3356: q[i] = g; s = 0.0;
3357: #ifdef DEBUGPRAX
3358: printf(" I Q=%d %.7g",i,q[i]);
3359: #endif
3360:
3361: /* if (i < n) */
3362: /* if (i <= n) /\* I is always lower or equal to n wasn't in golub reinsch*\/ */
3363: /* for (j=l; j<n; j++) */
3364: for (j=l; j<=n; j++)
3365: s += ab[i][j] * ab[i][j];
3366: /* s += ab[i][j] * ab[i][j]; */
3367: if (s < tol) {
3368: g = 0.0;
3369: }
3370: else {
3371: if(i<n)
3372: /* f = ab[i][i+1]; */ /* Brent golub overflow */
3373: f = ab[i][i+1];
3374: if (f < 0.0)
3375: g = sqrt(s);
3376: else
3377: g = - sqrt(s);
3378: h = f*g - s;
3379: /* h = f*g - s; ab[i][i+1] = f - g; */ /* Overflow for i=n Error in Golub too but not Burkardt*/
3380: /* for (j=l; j<n; j++) */
3381: /* e[j] = ab[i][j]/h; */
3382: if(i<n){
3383: ab[i][i+1] = f - g;
3384: for (j=l; j<=n; j++)
3385: e[j] = ab[i][j]/h;
3386: /* for (j=l; j<n; j++) { */
3387: for (j=l; j<=n; j++) {
3388: s = 0.0;
3389: /* for (k=l; k<n; k++) s += ab[j][k]*ab[i][k]; */
3390: for (k=l; k<=n; k++) s += ab[j][k]*ab[i][k];
3391: /* for (k=l; k<n; k++) ab[j][k] += s * e[k]; */
3392: for (k=l; k<=n; k++) ab[j][k] += s * e[k];
3393: } /* END J */
3394: } /* END i <n */
3395: } /* end s */
3396: /* y = fabs(q[i]) + fabs(e[i]); */
3397: y = fabs(q[i]) + fabs(e[i]);
3398: if (y > x) x = y;
3399: #ifdef DEBUGPRAX
3400: printf(" I Y=%d %.7g",i,y);
3401: #endif
3402: #ifdef DEBUGPRAX
3403: printf(" i=%d e(i) %.7g",i,e[i]);
3404: #endif
3405: } /* end i */
3406: /*
3407: Accumulation of right hand transformations */
3408: /* for (i=n-1; i >= 0; i--) { */ /* FOR I := N STEP -1 UNTIL 1 DO */
3409: /* We should avoid the overflow in Golub */
3410: /* ab[n-1][n-1] = 1.0; */
3411: /* g = e[n-1]; */
3412: ab[n][n] = 1.0;
3413: g = e[n];
3414: l = n;
3415:
3416: /* for (i=n; i >= 1; i--) { */
3417: for (i=n-1; i >= 1; i--) { /* n-1 loops, different from brent and golub*/
3418: if (g != 0.0) {
3419: /* h = ab[i-1][i]*g; */
3420: h = ab[i][i+1]*g;
3421: for (j=l; j<=n; j++) ab[j][i] = ab[i][j] / h;
3422: for (j=l; j<=n; j++) {
3423: /* h = ab[i][i+1]*g; */
3424: /* for (j=l; j<n; j++) ab[j][i] = ab[i][j] / h; */
3425: /* for (j=l; j<n; j++) { */
3426: s = 0.0;
3427: /* for (k=l; k<n; k++) s += ab[i][k] * ab[k][j]; */
3428: /* for (k=l; k<n; k++) ab[k][j] += s * ab[k][i]; */
3429: for (k=l; k<=n; k++) s += ab[i][k] * ab[k][j];
3430: for (k=l; k<=n; k++) ab[k][j] += s * ab[k][i];
3431: }/* END J */
3432: }/* END G */
3433: /* for (j=l; j<n; j++) */
3434: /* ab[i][j] = ab[j][i] = 0.0; */
3435: /* ab[i][i] = 1.0; g = e[i]; l = i; */
3436: for (j=l; j<=n; j++)
3437: ab[i][j] = ab[j][i] = 0.0;
3438: ab[i][i] = 1.0; g = e[i]; l = i;
3439: }/* END I */
3440: #ifdef DEBUGPRAX
3441: matprint (" HOUSE accumulation:",ab,n, n );
3442: #endif
3443:
3444: /* diagonalization to bidiagonal form */
3445: eps *= x;
3446: /* for (k=n-1; k>= 0; k--) { */
3447: for (k=n; k>= 1; k--) {
3448: kt = 0;
3449: TestFsplitting:
3450: #ifdef DEBUGPRAX
3451: printf(" TestFsplitting: k=%d kt=%d\n",k,kt);
3452: /* for(i=1;i<=n;i++)printf(" e(%d)=%.14f",i,e[i]);printf("\n"); */
3453: #endif
3454: kt = kt+1;
3455: /* TestFsplitting: */
3456: /* if (++kt > 30) { */
3457: if (kt > 30) {
3458: e[k] = 0.0;
3459: fprintf(stderr, "\n+++ MINFIT - Fatal error\n");
3460: fprintf ( stderr, " The QR algorithm failed to converge.\n" );
3461: }
3462: /* for (l2=k; l2>=0; l2--) { */
3463: for (l2=k; l2>=1; l2--) {
3464: l = l2;
3465: #ifdef DEBUGPRAX
3466: printf(" l e(l)< eps %d %.7g %.7g ",l,e[l], eps);
3467: #endif
3468: /* if (fabs(e[l]) <= eps) */
3469: if (fabs(e[l]) <= eps)
3470: goto TestFconvergence;
3471: /* if (fabs(q[l-1]) <= eps)*/ /* missing if ( 1 < l ){ *//* printf(" q(l-1)< eps %d %.7g %.7g ",l-1,q[l-2], eps); */
3472: if (fabs(q[l-1]) <= eps)
3473: break; /* goto Cancellation; */
3474: }
3475: Cancellation:
3476: #ifdef DEBUGPRAX
3477: printf(" Cancellation:\n");
3478: #endif
3479: c = 0.0; s = 1.0;
3480: for (i=l; i<=k; i++) {
3481: f = s * e[i]; e[i] *= c;
3482: /* f = s * e[i]; e[i] *= c; */
3483: if (fabs(f) <= eps)
3484: goto TestFconvergence;
3485: /* g = q[i]; */
3486: g = q[i];
3487: if (fabs(f) < fabs(g)) {
3488: double fg = f/g;
3489: h = fabs(g)*sqrt(1.0+fg*fg);
3490: }
3491: else {
3492: double gf = g/f;
3493: h = (f!=0.0 ? fabs(f)*sqrt(1.0+gf*gf) : 0.0);
3494: }
3495: /* COMMENT: THE ABOVE REPLACES Q(I):=H:=LONGSQRT(G*G+F*F) */
3496: /* WHICH MAY GIVE INCORRECT RESULTS IF THE */
3497: /* SQUARES UNDERFLOW OR IF F = G = 0; */
3498:
3499: /* q[i] = h; */
3500: q[i] = h;
3501: if (h == 0.0) { h = 1.0; g = 1.0; }
3502: c = g/h; s = -f/h;
3503: }
3504: TestFconvergence:
3505: #ifdef DEBUGPRAX
3506: printf(" TestFconvergence: l=%d k=%d\n",l,k);
3507: #endif
3508: /* z = q[k]; */
3509: z = q[k];
3510: if (l == k)
3511: goto Convergence;
3512: /* shift from bottom 2x2 minor */
3513: /* x = q[l]; y = q[k-l]; g = e[k-1]; h = e[k]; */ /* Error */
3514: x = q[l]; y = q[k-1]; g = e[k-1]; h = e[k];
3515: f = ((y-z)*(y+z) + (g-h)*(g+h)) / (2.0*h*y);
3516: g = sqrt(f*f+1.0);
3517: if (f <= 0.0)
3518: f = ((x-z)*(x+z) + h*(y/(f-g)-h))/x;
3519: else
3520: f = ((x-z)*(x+z) + h*(y/(f+g)-h))/x;
3521: /* next qr transformation */
3522: s = c = 1.0;
3523: for (i=l+1; i<=k; i++) {
3524: #ifdef DEBUGPRAXQR
3525: printf(" Before Mid TestFconvergence: l+1=%d i=%d k=%d h=%.6e e(i)=%14.8f e(i-1)=%14.8f\n",l+1,i,k, h, e[i],e[i-1]);
3526: #endif
3527: /* g = e[i]; y = q[i]; h = s*g; g *= c; */
3528: g = e[i]; y = q[i]; h = s*g; g *= c;
3529: if (fabs(f) < fabs(h)) {
3530: double fh = f/h;
3531: z = fabs(h) * sqrt(1.0 + fh*fh);
3532: }
3533: else {
3534: double hf = h/f;
3535: z = (f!=0.0 ? fabs(f)*sqrt(1.0+hf*hf) : 0.0);
3536: }
3537: /* e[i-1] = z; */
3538: e[i-1] = z;
3539: #ifdef DEBUGPRAXQR
3540: printf(" Mid TestFconvergence: l+1=%d i=%d k=%d h=%.6e e(i)=%14.8f e(i-1)=%14.8f\n",l+1,i,k, h, e[i],e[i-1]);
3541: #endif
3542: if (z == 0.0)
3543: f = z = 1.0;
3544: c = f/z; s = h/z;
3545: f = x*c + g*s; g = - x*s + g*c; h = y*s;
3546: y *= c;
3547: /* for (j=0; j<n; j++) { */
3548: /* x = ab[j][i-1]; z = ab[j][i]; */
3549: /* ab[j][i-1] = x*c + z*s; */
3550: /* ab[j][i] = - x*s + z*c; */
3551: /* } */
3552: for (j=1; j<=n; j++) {
3553: x = ab[j][i-1]; z = ab[j][i];
3554: ab[j][i-1] = x*c + z*s;
3555: ab[j][i] = - x*s + z*c;
3556: }
3557: if (fabs(f) < fabs(h)) {
3558: double fh = f/h;
3559: z = fabs(h) * sqrt(1.0 + fh*fh);
3560: }
3561: else {
3562: double hf = h/f;
3563: z = (f!=0.0 ? fabs(f)*sqrt(1.0+hf*hf) : 0.0);
3564: }
3565: #ifdef DEBUGPRAXQR
3566: printf(" qr transformation z f h=%.7g %.7g %.7g i=%d k=%d\n",z,f,h, i, k);
3567: #endif
3568: q[i-1] = z;
3569: if (z == 0.0)
3570: z = f = 1.0;
3571: c = f/z; s = h/z;
3572: f = c*g + s*y; /* f can be very small */
3573: x = - s*g + c*y;
3574: }
3575: /* e[l] = 0.0; e[k] = f; q[k] = x; */
3576: e[l] = 0.0; e[k] = f; q[k] = x;
3577: #ifdef DEBUGPRAXQR
3578: printf(" aftermid loop l=%d k=%d e(l)=%7g e(k)=%.7g q(k)=%.7g x=%.7g\n",l,k,e[l],e[k],q[k],x);
3579: #endif
3580: goto TestFsplitting;
3581: Convergence:
3582: #ifdef DEBUGPRAX
3583: printf(" Convergence:\n");
3584: #endif
3585: if (z < 0.0) {
3586: /* q[k] = - z; */
3587: /* for (j=0; j<n; j++) ab[j][k] = - ab[j][k]; */
3588: q[k] = - z;
3589: for (j=1; j<=n; j++) ab[j][k] = - ab[j][k];
3590: }/* END Z */
3591: }/* END K */
3592: } /* END MINFIT */
3593:
3594:
3595: double praxis(double tol, double macheps, double h0, int _n, int _prin, double *_x, double (*_fun)(double *_x))
3596: /* double praxis(double tol, double macheps, double h0, int _n, int _prin, double *_x, double (*_fun)(double *_x, int _n)) */
3597: /* double praxis(double (*_fun)(), double _x[], int _n) */
3598: /* double (*_fun)(); */
3599: /* double _x[N]; */
3600: /* double (*_fun)(); */
3601: /* double _x[N]; */
3602: {
3603: /* init global extern variables and parameters */
3604: /* double *d, *y, *z, */
3605: /* *q0, *q1, **v; */
3606: /* double *tflin; /\* used in flin: return (*fun)(tflin, n); *\/ */
3607: /* double *e; /\* used in minfit, don't konw how to free memory and thus made global *\/ */
3608:
3609:
3610: int seed; /* added */
3611: int biter=0;
3612: double r;
3613: double randbrent( int (*));
3614: double s, sf;
3615:
3616: h = h0; /* step; */
3617: t = tol;
3618: scbd = 1.0;
3619: illc = 0;
3620: ktm = 1;
3621:
3622: macheps = DBL_EPSILON;
3623: /* prin=4; */
3624: #ifdef DEBUGPRAX
3625: printf("Praxis macheps=%14g h=%14g step=%14g tol=%14g\n",macheps,h, h0,tol);
3626: #endif
3627: n = _n;
3628: x = _x;
3629: prin = _prin;
3630: fun = _fun;
3631: d=vector(1, n);
3632: y=vector(1, n);
3633: z=vector(1, n);
3634: q0=vector(1, n);
3635: q1=vector(1, n);
3636: e=vector(1, n);
3637: tflin=vector(1, n);
3638: v=matrix(1, n, 1, n);
3639: for(i=1;i<=n;i++){d[i]=y[i]=z[i]=q0[0]=e[i]=tflin[i]=0.;}
3640: small_windows = (macheps) * (macheps); vsmall = small_windows*small_windows;
3641: large = 1.0/small_windows; vlarge = 1.0/vsmall;
3642: m2 = sqrt(macheps); m4 = sqrt(m2);
3643: seed = 123456789; /* added */
3644: ldfac = (illc ? 0.1 : 0.01);
3645: for(i=1;i<=n;i++) z[i]=0.; /* Was missing in Gegenfurtner as well as Brent's algol or fortran */
3646: nl = kt = 0; nf = 1;
3647: #ifdef NR_SHIFT
3648: fx = (*fun)((x-1), n);
3649: #else
3650: fx = (*fun)(x);
3651: #endif
3652: qf1 = fx;
3653: t2 = small_windows + fabs(t); t = t2; dmin = small_windows;
3654: #ifdef DEBUGPRAX
3655: printf("praxis2 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3656: #endif
3657: if (h < 100.0*t) h = 100.0*t;
3658: #ifdef DEBUGPRAX
3659: printf("praxis3 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3660: #endif
3661: ldt = h;
3662: /* for (i=0; i<n; i++) for (j=0; j<n; j++) */
3663: for (i=1; i<=n; i++) for (j=1; j<=n; j++)
3664: v[i][j] = (i == j ? 1.0 : 0.0);
3665: d[1] = 0.0; qd0 = 0.0;
3666: /* for (i=0; i<n; i++) q1[i] = x[i]; */
3667: for (i=1; i<=n; i++) q1[i] = x[i];
3668: if (prin > 1) {
3669: printf("\n------------- enter function praxis -----------\n");
3670: printf("... current parameter settings ...\n");
3671: printf("... scaling ... %20.10e\n", scbd);
3672: printf("... tol ... %20.10e\n", t);
3673: printf("... maxstep ... %20.10e\n", h);
3674: printf("... illc ... %20u\n", illc);
3675: printf("... ktm ... %20u\n", ktm);
3676: printf("... maxfun ... %20u\n", maxfun);
3677: }
3678: if (prin) print2();
3679:
3680: mloop:
3681: biter++; /* Added to count the loops */
3682: /* sf = d[0]; */
3683: /* s = d[0] = 0.0; */
3684: printf("\n Big iteration %d \n",biter);
3685: fprintf(ficlog,"\n Big iteration %d \n",biter);
3686: sf = d[1];
3687: s = d[1] = 0.0;
3688:
3689: /* minimize along first direction V(*,1) */
3690: #ifdef DEBUGPRAX
3691: printf(" Minimize along the first direction V(*,1). illc=%d\n",illc);
3692: /* fprintf(ficlog," Minimize along the first direction V(*,1).\n"); */
3693: #endif
3694: #ifdef DEBUGPRAX2
3695: printf("praxis4 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3696: #endif
3697: /* min(0, 2, &d[0], &s, fx, 0); /\* mac heps not global *\/ */
3698: minny(1, 2, &d[1], &s, fx, 0); /* mac heps not global */
3699: #ifdef DEBUGPRAX
3700: printf("praxis5 macheps=%14g h=%14g looks at sign of s=%14g fx=%14g\n",macheps,h, s,fx);
3701: #endif
3702: if (s <= 0.0)
3703: /* for (i=0; i < n; i++) */
3704: for (i=1; i <= n; i++)
3705: v[i][1] = -v[i][1];
3706: /* if ((sf <= (0.9 * d[0])) || ((0.9 * sf) >= d[0])) */
3707: if ((sf <= (0.9 * d[1])) || ((0.9 * sf) >= d[1]))
3708: /* for (i=1; i<n; i++) */
3709: for (i=2; i<=n; i++)
3710: d[i] = 0.0;
3711: /* for (k=1; k<n; k++) { */
3712: for (k=2; k<=n; k++) {
3713: /*
3714: The inner loop starts here.
3715: */
3716: #ifdef DEBUGPRAX
3717: printf(" The inner loop here from k=%d to n=%d.\n",k,n);
3718: /* fprintf(ficlog," The inner loop here from k=%d to n=%d.\n",k,n); */
3719: #endif
3720: /* for (i=0; i<n; i++) */
3721: for (i=1; i<=n; i++)
3722: y[i] = x[i];
3723: sf = fx;
3724: #ifdef DEBUGPRAX
3725: printf(" illc=%d and kt=%d and ktm=%d\n", illc, kt, ktm);
3726: #endif
3727: illc = illc || (kt > 0);
3728: next:
3729: kl = k;
3730: df = 0.0;
3731: if (illc) { /* random step to get off resolution valley */
3732: #ifdef DEBUGPRAX
3733: printf(" A random step follows, to avoid resolution valleys.\n");
3734: matprint(" before rand, vectors:",v,n,n);
3735: #endif
3736: for (i=1; i<=n; i++) {
3737: #ifdef NOBRENTRAND
3738: r = drandom();
3739: #else
3740: seed=i;
3741: /* seed=i+1; */
3742: #ifdef DEBUGRAND
3743: printf(" Random seed=%d, brent i=%d",seed,i); /* YYYY i=5 j=1 vji= -0.0001170073 */
3744: #endif
3745: r = randbrent ( &seed );
3746: #endif
3747: #ifdef DEBUGRAND
3748: printf(" Random r=%.7g \n",r);
3749: #endif
3750: z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (r - 0.5);
3751: /* z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (drandom() - 0.5); */
3752:
3753: s = z[i];
3754: for (j=1; j <= n; j++)
3755: x[j] += s * v[j][i];
3756: }
3757: #ifdef DEBUGRAND
3758: matprint(" after rand, vectors:",v,n,n);
3759: #endif
3760: #ifdef NR_SHIFT
3761: fx = (*fun)((x-1), n);
3762: #else
3763: fx = (*fun)(x, n);
3764: #endif
3765: /* fx = (*func) ( (x-1) ); *//* This for func which is computed from x[1] and not from x[0] xm1=(x-1)*/
3766: nf++;
3767: }
3768: /* minimize along non-conjugate directions */
3769: #ifdef DEBUGPRAX
3770: printf(" Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n);
3771: /* fprintf(ficlog," Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n); */
3772: #endif
3773: /* for (k2=k; k2<n; k2++) { /\* Be careful here k2 <=n ? *\/ */
3774: for (k2=k; k2<=n; k2++) { /* Be careful here k2 <=n ? */
3775: sl = fx;
3776: s = 0.0;
3777: #ifdef DEBUGPRAX
3778: printf(" Minimize along the 'NON-CONJUGATE' true direction k2=%14d fx=%14.7f\n",k2, fx);
3779: matprint(" before min vectors:",v,n,n);
3780: #endif
3781: /* min(k2, 2, &d[k2], &s, fx, 0); */
3782: /* jsearch=k2-1; */
3783: /* min(jsearch, 2, &d[jsearch], &s, fx, 0); */
3784: minny(k2, 2, &d[k2], &s, fx, 0);
3785: #ifdef DEBUGPRAX
3786: printf(" . D(%d)=%14.7f d[k2]=%14.7f z[k2]=%14.7f illc=%14d fx=%14.7f\n",k2,d[k2],d[k2],z[k2],illc,fx);
3787: #endif
3788: if (illc) {
3789: /* double szk = s + z[k2]; */
3790: /* s = d[k2] * szk*szk; */
3791: double szk = s + z[k2];
3792: s = d[k2] * szk*szk;
3793: }
3794: else
3795: s = sl - fx;
3796: /* if (df < s) { */
3797: if (df <= s) {
3798: df = s;
3799: kl = k2;
3800: #ifdef DEBUGPRAX
3801: printf(" df=%.7g and choose kl=%d \n",df,kl); /* UUUU */
3802: #endif
3803: }
3804: } /* end loop k2 */
3805: /*
3806: If there was not much improvement on the first try, set
3807: ILLC = true and start the inner loop again.
3808: */
3809: #ifdef DEBUGPRAX
3810: printf(" If there was not much improvement on the first try, set ILLC = true and start the inner loop again. illc=%d\n",illc);
3811: /* fprintf(ficlog," If there was not much improvement on the first try, set ILLC = true and start the inner loop again.\n"); */
3812: #endif
3813: if (!illc && (df < fabs(100.0 * (macheps) * fx))) {
3814: #ifdef DEBUGPRAX
3815: printf("\n NO SUCCESS because DF is small, starts inner loop with same K(=%d), fabs( 100.0 * machep(=%.10e) * fx(=%.9e) )=%.9e > df(=%.9e) break illc=%d\n", k, macheps, fx, fabs ( 100.0 * macheps * fx ), df, illc);
3816: #endif
3817: illc = 1;
3818: goto next;
3819: }
3820: #ifdef DEBUGPRAX
3821: printf("\n SUCCESS, BREAKS inner loop K(=%d) because DF is big, fabs( 100.0 * machep(=%.10e) * fx(=%.9e) )=%.9e <= df(=%.9e) break illc=%d\n", k, macheps, fx, fabs ( 100.0 * macheps * fx ), df, illc);
3822: #endif
3823:
3824: /* if ((k == 1) && (prin > 1)){ /\* be careful k=2 *\/ */
3825: if ((k == 2) && (prin > 1)){ /* be careful k=2 */
3826: #ifdef DEBUGPRAX
3827: printf(" NEW D The second difference array d:\n" );
3828: /* fprintf(ficlog, " NEW D The second difference array d:\n" ); */
3829: #endif
3830: vecprint(" NEW D The second difference array d:",d,n);
3831: }
3832: /* minimize along conjugate directions */
3833: /*
3834: Minimize along the "conjugate" directions V(*,1),...,V(*,K-1).
3835: */
3836: #ifdef DEBUGPRAX
3837: printf("Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1);
3838: /* fprintf(ficlog,"Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1); */
3839: #endif
3840: /* for (k2=0; k2<=k-1; k2++) { */
3841: for (k2=1; k2<=k-1; k2++) {
3842: s = 0.0;
3843: /* min(k2-1, 2, &d[k2-1], &s, fx, 0); */
3844: minny(k2, 2, &d[k2], &s, fx, 0);
3845: }
3846: f1 = fx;
3847: fx = sf;
3848: lds = 0.0;
3849: /* for (i=0; i<n; i++) { */
3850: for (i=1; i<=n; i++) {
3851: sl = x[i];
3852: x[i] = y[i];
3853: y[i] = sl - y[i];
3854: sl = y[i];
3855: lds = lds + sl*sl;
3856: }
3857: lds = sqrt(lds);
3858: #ifdef DEBUGPRAX
3859: printf("Minimization done 'conjugate', shifted all points, computed lds=%.8f\n",lds);
3860: #endif
3861: /*
3862: Discard direction V(*,kl).
3863:
3864: If no random step was taken, V(*,KL) is the "non-conjugate"
3865: direction along which the greatest improvement was made.
3866: */
3867: if (lds > small_windows) {
3868: #ifdef DEBUGPRAX
3869: printf("lds big enough to throw direction V(*,kl=%d). If no random step was taken, V(*,KL) is the 'non-conjugate' direction along which the greatest improvement was made.\n",kl);
3870: matprint(" before shift new conjugate vectors:",v,n,n);
3871: #endif
3872: for (i=kl-1; i>=k; i--) {
3873: /* for (j=0; j < n; j++) */
3874: for (j=1; j <= n; j++)
3875: /* v[j][i+1] = v[j][i]; */ /* This is v[j][i+1]=v[j][i] i=kl-1 to k */
3876: v[j][i+1] = v[j][i]; /* This is v[j][i+1]=v[j][i] i=kl-1 to k */
3877: /* v[j][i+1] = v[j][i]; */
3878: /* d[i+1] = d[i];*/ /* last is d[k+1]= d[k] */
3879: d[i+1] = d[i]; /* last is d[k]= d[k-1] */
3880: }
3881: #ifdef DEBUGPRAX
3882: matprint(" after shift new conjugate vectors:",v,n,n);
3883: #endif /* d[k] = 0.0; */
3884: d[k] = 0.0;
3885: for (i=1; i <= n; i++)
3886: v[i][k] = y[i] / lds;
3887: /* v[i][k] = y[i] / lds; */
3888: #ifdef DEBUGPRAX
3889: printf("Minimize along the new 'conjugate' direction V(*,k=%d), which is the normalized vector: (new x) - (old x). d2=%14.7g lds=%.10f\n",k,d[k],lds);
3890: /* fprintf(ficlog,"Minimize along the new 'conjugate' direction V(*,k=%d), which is the normalized vector: (new x) - (old x).\n",k); */
3891: matprint(" before min new conjugate vectors:",v,n,n);
3892: #endif
3893: /* min(k-1, 4, &d[k-1], &lds, f1, 1); */
3894: minny(k, 4, &d[k], &lds, f1, 1);
3895: #ifdef DEBUGPRAX
3896: printf(" after min d(k)=%d %.7g lds=%14f\n",k,d[k],lds);
3897: matprint(" after min vectors:",v,n,n);
3898: #endif
3899: if (lds <= 0.0) {
3900: lds = -lds;
3901: #ifdef DEBUGPRAX
3902: printf(" lds changed sign lds=%.14f k=%d\n",lds,k);
3903: #endif
3904: /* for (i=0; i<n; i++) */
3905: /* v[i][k] = -v[i][k]; */
3906: for (i=1; i<=n; i++)
3907: v[i][k] = -v[i][k];
3908: }
3909: }
3910: ldt = ldfac * ldt;
3911: if (ldt < lds)
3912: ldt = lds;
3913: if (prin > 0){
3914: #ifdef DEBUGPRAX
3915: printf(" k=%d",k);
3916: /* fprintf(ficlog," k=%d",k); */
3917: #endif
3918: print2();/* n, x, prin, fx, nf, nl ); */
3919: }
3920: t2 = 0.0;
3921: /* for (i=0; i<n; i++) */
3922: for (i=1; i<=n; i++)
3923: t2 += x[i]*x[i];
3924: t2 = m2 * sqrt(t2) + t;
3925: /*
3926: See whether the length of the step taken since starting the
3927: inner loop exceeds half the tolerance.
3928: */
3929: #ifdef DEBUGPRAX
3930: printf("See if step length exceeds half the tolerance.\n"); /* ZZZZZ */
3931: /* fprintf(ficlog,"See if step length exceeds half the tolerance.\n"); */
3932: #endif
3933: if (ldt > (0.5 * t2))
3934: kt = 0;
3935: else
3936: kt++;
3937: #ifdef DEBUGPRAX
3938: printf("if kt=%d >? ktm=%d gotoL2 loop\n",kt,ktm);
3939: #endif
3940: if (kt > ktm){
3941: if ( 0 < prin ){
3942: /* printf("\nr8vec_print\n X:\n"); */
3943: /* fprintf(ficlog,"\nr8vec_print\n X:\n"); */
3944: vecprint ("END X:", x, n );
3945: }
3946: goto fret;
3947: }
3948: #ifdef DEBUGPRAX
3949: matprint(" end of L2 loop vectors:",v,n,n);
3950: #endif
3951:
3952: }
3953: /* printf("The inner loop ends here.\n"); */
3954: /* fprintf(ficlog,"The inner loop ends here.\n"); */
3955: /*
3956: The inner loop ends here.
3957:
3958: Try quadratic extrapolation in case we are in a curved valley.
3959: */
3960: #ifdef DEBUGPRAX
3961: printf("Try QUAD ratic extrapolation in case we are in a curved valley.\n");
3962: #endif
3963: /* try quadratic extrapolation in case */
3964: /* we are stuck in a curved valley */
3965: quad();
3966: dn = 0.0;
3967: /* for (i=0; i<n; i++) { */
3968: for (i=1; i<=n; i++) {
3969: d[i] = 1.0 / sqrt(d[i]);
3970: if (dn < d[i])
3971: dn = d[i];
3972: }
3973: if (prin > 2)
3974: matprint(" NEW DIRECTIONS vectors:",v,n,n);
3975: /* for (j=0; j<n; j++) { */
3976: for (j=1; j<=n; j++) {
3977: s = d[j] / dn;
3978: /* for (i=0; i < n; i++) */
3979: for (i=1; i <= n; i++)
3980: v[i][j] *= s;
3981: }
3982:
3983: if (scbd > 1.0) { /* scale axis to reduce condition number */
3984: #ifdef DEBUGPRAX
3985: printf("Scale the axes to try to reduce the condition number.\n");
3986: #endif
3987: /* fprintf(ficlog,"Scale the axes to try to reduce the condition number.\n"); */
3988: s = vlarge;
3989: /* for (i=0; i<n; i++) { */
3990: for (i=1; i<=n; i++) {
3991: sl = 0.0;
3992: /* for (j=0; j < n; j++) */
3993: for (j=1; j <= n; j++)
3994: sl += v[i][j]*v[i][j];
3995: z[i] = sqrt(sl);
3996: if (z[i] < m4)
3997: z[i] = m4;
3998: if (s > z[i])
3999: s = z[i];
4000: }
4001: /* for (i=0; i<n; i++) { */
4002: for (i=1; i<=n; i++) {
4003: sl = s / z[i];
4004: z[i] = 1.0 / sl;
4005: if (z[i] > scbd) {
4006: sl = 1.0 / scbd;
4007: z[i] = scbd;
4008: }
4009: }
4010: }
4011: for (i=1; i<=n; i++)
4012: /* for (j=0; j<=i-1; j++) { */
4013: /* for (j=1; j<=i; j++) { */
4014: for (j=1; j<=i-1; j++) {
4015: s = v[i][j];
4016: v[i][j] = v[j][i];
4017: v[j][i] = s;
4018: }
4019: #ifdef DEBUGPRAX
4020: printf(" Calculate a new set of orthogonal directions before repeating the main loop.\n Transpose V for MINFIT:...\n");
4021: #endif
4022: /*
4023: MINFIT finds the singular value decomposition of V.
4024:
4025: This gives the principal values and principal directions of the
4026: approximating quadratic form without squaring the condition number.
4027: */
4028: #ifdef DEBUGPRAX
4029: printf(" MINFIT finds the singular value decomposition of V. \n This gives the principal values and principal directions of the\n approximating quadratic form without squaring the condition number...\n");
4030: #endif
4031:
4032: minfit(n, macheps, vsmall, v, d);
4033: /* for(i=0; i<n;i++)printf(" %14.7g",d[i]); */
4034: /* v is overwritten with R. */
4035: /*
4036: Unscale the axes.
4037: */
4038: if (scbd > 1.0) {
4039: #ifdef DEBUGPRAX
4040: printf(" Unscale the axes.\n");
4041: #endif
4042: /* for (i=0; i<n; i++) { */
4043: for (i=1; i<=n; i++) {
4044: s = z[i];
4045: /* for (j=0; j<n; j++) */
4046: for (j=1; j<=n; j++)
4047: v[i][j] *= s;
4048: }
4049: /* for (i=0; i<n; i++) { */
4050: for (i=1; i<=n; i++) {
4051: s = 0.0;
4052: /* for (j=0; j<n; j++) */
4053: for (j=1; j<=n; j++)
4054: s += v[j][i]*v[j][i];
4055: s = sqrt(s);
4056: d[i] *= s;
4057: s = 1.0 / s;
4058: /* for (j=0; j<n; j++) */
4059: for (j=1; j<=n; j++)
4060: v[j][i] *= s;
4061: }
4062: }
4063: /* for (i=0; i<n; i++) { */
4064: double dni; /* added for compatibility with buckhardt but not brent */
4065: for (i=1; i<=n; i++) {
4066: dni=dn*d[i]; /* added for compatibility with buckhardt but not brent */
4067: if ((dn * d[i]) > large)
4068: d[i] = vsmall;
4069: else if ((dn * d[i]) < small_windows)
4070: d[i] = vlarge;
4071: else
4072: d[i] = 1.0 / dni / dni; /* added for compatibility with buckhardt but not brent */
4073: /* d[i] = pow(dn * d[i],-2.0); */
4074: }
4075: #ifdef DEBUGPRAX
4076: vecprint ("\n Before sort Eigenvalues of a:",d,n );
4077: #endif
4078:
4079: sort(); /* the new eigenvalues and eigenvectors */
4080: #ifdef DEBUGPRAX
4081: vecprint( " After sort the eigenvalues ....\n", d, n);
4082: matprint( " After sort the eigenvectors....\n", v, n,n);
4083: #endif
4084: #ifdef DEBUGPRAX
4085: printf(" Determine the smallest eigenvalue.\n");
4086: #endif
4087: /* dmin = d[n-1]; */
4088: dmin = d[n];
4089: if (dmin < small_windows)
4090: dmin = small_windows;
4091: /*
4092: The ratio of the smallest to largest eigenvalue determines whether
4093: the system is ill conditioned.
4094: */
4095:
4096: /* illc = (m2 * d[0]) > dmin; */
4097: illc = (m2 * d[1]) > dmin;
4098: #ifdef DEBUGPRAX
4099: printf(" The ratio of the smallest to largest eigenvalue determines whether\n the system is ill conditioned=%d . dmin=%.10lf < m2=%.10lf * d[1]=%.10lf \n",illc, dmin,m2, d[1]);
4100: #endif
4101:
4102: if ((prin > 2) && (scbd > 1.0))
4103: vecprint("\n The scale factors:",z,n);
4104: if (prin > 2)
4105: vecprint(" Principal values (EIGEN VALUES OF A) of the quadratic form:",d,n);
4106: if (prin > 2)
4107: matprint(" The principal axes (EIGEN VECTORS OF A:",v,n, n);
4108:
4109: if ((maxfun > 0) && (nf > maxfun)) {
4110: if (prin)
4111: printf("\n... maximum number of function calls reached ...\n");
4112: goto fret;
4113: }
4114: #ifdef DEBUGPRAX
4115: printf("Goto main loop\n");
4116: #endif
4117: goto mloop; /* back to main loop */
4118:
4119: fret:
4120: if (prin > 0) {
4121: vecprint("\n X:", x, n);
4122: /* printf("\n... ChiSq reduced to %20.10e ...\n", fx); */
4123: /* printf("... after %20u function calls.\n", nf); */
4124: }
4125: free_vector(d, 1, n);
4126: free_vector(y, 1, n);
4127: free_vector(z, 1, n);
4128: free_vector(q0, 1, n);
4129: free_vector(q1, 1, n);
4130: free_matrix(v, 1, n, 1, n);
4131: /* double *d, *y, *z, */
4132: /* *q0, *q1, **v; */
4133: free_vector(tflin, 1, n);
4134: /* double *tflin; /\* used in flin: return (*fun)(tflin, n); *\/ */
4135: free_vector(e, 1, n);
4136: /* double *e; /\* used in minfit, don't konw how to free memory and thus made global *\/ */
4137:
4138: return(fx);
4139: }
4140:
4141: /* end praxis gegen */
1.126 brouard 4142:
4143: /*************** powell ************************/
1.162 brouard 4144: /*
1.317 brouard 4145: Minimization of a function func of n variables. Input consists in an initial starting point
4146: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
4147: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
4148: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 4149: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
4150: function value at p , and iter is the number of iterations taken. The routine linmin is used.
4151: */
1.224 brouard 4152: #ifdef LINMINORIGINAL
4153: #else
4154: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 4155: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 4156: #endif
1.126 brouard 4157: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
4158: double (*func)(double []))
4159: {
1.224 brouard 4160: #ifdef LINMINORIGINAL
4161: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 4162: double (*func)(double []));
1.224 brouard 4163: #else
1.241 brouard 4164: void linmin(double p[], double xi[], int n, double *fret,
4165: double (*func)(double []),int *flat);
1.224 brouard 4166: #endif
1.239 brouard 4167: int i,ibig,j,jk,k;
1.126 brouard 4168: double del,t,*pt,*ptt,*xit;
1.181 brouard 4169: double directest;
1.126 brouard 4170: double fp,fptt;
4171: double *xits;
4172: int niterf, itmp;
1.349 brouard 4173: int Bigter=0, nBigterf=1;
4174:
1.126 brouard 4175: pt=vector(1,n);
4176: ptt=vector(1,n);
4177: xit=vector(1,n);
4178: xits=vector(1,n);
4179: *fret=(*func)(p);
4180: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 4181: rcurr_time = time(NULL);
4182: fp=(*fret); /* Initialisation */
1.126 brouard 4183: for (*iter=1;;++(*iter)) {
4184: ibig=0;
4185: del=0.0;
1.157 brouard 4186: rlast_time=rcurr_time;
1.349 brouard 4187: rlast_btime=rcurr_time;
1.157 brouard 4188: /* (void) gettimeofday(&curr_time,&tzp); */
4189: rcurr_time = time(NULL);
4190: curr_time = *localtime(&rcurr_time);
1.337 brouard 4191: /* printf("\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); */
4192: /* fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); */
1.359 brouard 4193: /* Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /\* Big iteration, i.e on ncovmodel cycle *\/ */
4194: Bigter=(*iter - (*iter-1) % n)/n +1; /* Big iteration, i.e on ncovmodel cycle */
1.349 brouard 4195: printf("\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
4196: fprintf(ficlog,"\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
4197: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 4198: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 4199: for (i=1;i<=n;i++) {
1.126 brouard 4200: fprintf(ficrespow," %.12lf", p[i]);
4201: }
1.239 brouard 4202: fprintf(ficrespow,"\n");fflush(ficrespow);
4203: printf("\n#model= 1 + age ");
4204: fprintf(ficlog,"\n#model= 1 + age ");
4205: if(nagesqr==1){
1.241 brouard 4206: printf(" + age*age ");
4207: fprintf(ficlog," + age*age ");
1.239 brouard 4208: }
4209: for(j=1;j <=ncovmodel-2;j++){
4210: if(Typevar[j]==0) {
4211: printf(" + V%d ",Tvar[j]);
4212: fprintf(ficlog," + V%d ",Tvar[j]);
4213: }else if(Typevar[j]==1) {
4214: printf(" + V%d*age ",Tvar[j]);
4215: fprintf(ficlog," + V%d*age ",Tvar[j]);
4216: }else if(Typevar[j]==2) {
4217: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
4218: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 4219: }else if(Typevar[j]==3) {
4220: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
4221: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 4222: }
4223: }
1.126 brouard 4224: printf("\n");
1.239 brouard 4225: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
4226: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 4227: fprintf(ficlog,"\n");
1.239 brouard 4228: for(i=1,jk=1; i <=nlstate; i++){
4229: for(k=1; k <=(nlstate+ndeath); k++){
4230: if (k != i) {
4231: printf("%d%d ",i,k);
4232: fprintf(ficlog,"%d%d ",i,k);
4233: for(j=1; j <=ncovmodel; j++){
4234: printf("%12.7f ",p[jk]);
4235: fprintf(ficlog,"%12.7f ",p[jk]);
4236: jk++;
4237: }
4238: printf("\n");
4239: fprintf(ficlog,"\n");
4240: }
4241: }
4242: }
1.241 brouard 4243: if(*iter <=3 && *iter >1){
1.157 brouard 4244: tml = *localtime(&rcurr_time);
4245: strcpy(strcurr,asctime(&tml));
4246: rforecast_time=rcurr_time;
1.126 brouard 4247: itmp = strlen(strcurr);
4248: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 4249: strcurr[itmp-1]='\0';
1.162 brouard 4250: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 4251: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 4252: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
4253: niterf=nBigterf*ncovmodel;
4254: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 4255: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
4256: forecast_time = *localtime(&rforecast_time);
4257: strcpy(strfor,asctime(&forecast_time));
4258: itmp = strlen(strfor);
4259: if(strfor[itmp-1]=='\n')
4260: strfor[itmp-1]='\0';
1.349 brouard 4261: printf(" - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
4262: fprintf(ficlog," - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 4263: }
4264: }
1.359 brouard 4265: for (i=1;i<=n;i++) { /* For each direction i, maximisation after loading directions */
4266: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales. xi is not changed but one dim xit */
4267:
4268: fptt=(*fret); /* Computes likelihood for parameters xit */
1.126 brouard 4269: #ifdef DEBUG
1.203 brouard 4270: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
4271: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 4272: #endif
1.203 brouard 4273: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 4274: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 4275: #ifdef LINMINORIGINAL
1.359 brouard 4276: linmin(p,xit,n,fret,func); /* New point i minimizing in direction xit, i has coordinates p[j].*/
1.357 brouard 4277: /* xit[j] gives the n coordinates of direction i as input.*/
4278: /* *fret gives the maximum value on direction xit */
1.224 brouard 4279: #else
4280: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.359 brouard 4281: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.224 brouard 4282: #endif
1.359 brouard 4283: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 4284: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.359 brouard 4285: /* because that direction will be replaced unless the gain del is small */
4286: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
4287: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
4288: /* with the new direction. */
4289: del=fabs(fptt-(*fret));
4290: ibig=i;
1.126 brouard 4291: }
4292: #ifdef DEBUG
4293: printf("%d %.12e",i,(*fret));
4294: fprintf(ficlog,"%d %.12e",i,(*fret));
4295: for (j=1;j<=n;j++) {
1.359 brouard 4296: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
4297: printf(" x(%d)=%.12e",j,xit[j]);
4298: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 4299: }
4300: for(j=1;j<=n;j++) {
1.359 brouard 4301: printf(" p(%d)=%.12e",j,p[j]);
4302: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 4303: }
4304: printf("\n");
4305: fprintf(ficlog,"\n");
4306: #endif
1.187 brouard 4307: } /* end loop on each direction i */
1.357 brouard 4308: /* Convergence test will use last linmin estimation (fret) and compare to former iteration (fp) */
1.188 brouard 4309: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.359 brouard 4310: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 4311: for(j=1;j<=n;j++) {
4312: if(flatdir[j] >0){
4313: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
4314: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 4315: }
1.319 brouard 4316: /* printf("\n"); */
4317: /* fprintf(ficlog,"\n"); */
4318: }
1.243 brouard 4319: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
4320: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 4321: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
4322: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
4323: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
4324: /* decreased of more than 3.84 */
4325: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
4326: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
4327: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 4328:
1.188 brouard 4329: /* Starting the program with initial values given by a former maximization will simply change */
4330: /* the scales of the directions and the directions, because the are reset to canonical directions */
4331: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
4332: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 4333: #ifdef DEBUG
4334: int k[2],l;
4335: k[0]=1;
4336: k[1]=-1;
4337: printf("Max: %.12e",(*func)(p));
4338: fprintf(ficlog,"Max: %.12e",(*func)(p));
4339: for (j=1;j<=n;j++) {
4340: printf(" %.12e",p[j]);
4341: fprintf(ficlog," %.12e",p[j]);
4342: }
4343: printf("\n");
4344: fprintf(ficlog,"\n");
4345: for(l=0;l<=1;l++) {
4346: for (j=1;j<=n;j++) {
4347: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
4348: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
4349: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
4350: }
4351: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
4352: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
4353: }
4354: #endif
4355:
4356: free_vector(xit,1,n);
4357: free_vector(xits,1,n);
4358: free_vector(ptt,1,n);
4359: free_vector(pt,1,n);
4360: return;
1.192 brouard 4361: } /* enough precision */
1.240 brouard 4362: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.359 brouard 4363: for (j=1;j<=n;j++) { /* Computes the extrapolated point and value f3, P_0 + 2 (P_n-P_0)=2Pn-P0 and xit is direction Pn-P0 */
1.126 brouard 4364: ptt[j]=2.0*p[j]-pt[j];
1.359 brouard 4365: xit[j]=p[j]-pt[j]; /* Coordinate j of last direction xi_n=P_n-P_0 */
4366: #ifdef DEBUG
4367: printf("\n %d xit=%12.7g p=%12.7g pt=%12.7g ",j,xit[j],p[j],pt[j]);
4368: #endif
4369: pt[j]=p[j]; /* New P0 is Pn */
4370: }
4371: #ifdef DEBUG
4372: printf("\n");
4373: #endif
1.181 brouard 4374: fptt=(*func)(ptt); /* f_3 */
1.359 brouard 4375: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in directions until some iterations are done */
1.224 brouard 4376: if (*iter <=4) {
1.225 brouard 4377: #else
4378: #endif
1.224 brouard 4379: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 4380: #else
1.161 brouard 4381: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 4382: #endif
1.162 brouard 4383: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 4384: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 4385: /* Let f"(x2) be the 2nd derivative equal everywhere. */
4386: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
4387: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 4388: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
4389: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
4390: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 4391: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 4392: /* Even if f3 <f1, directest can be negative and t >0 */
4393: /* mu² and del² are equal when f3=f1 */
1.359 brouard 4394: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
4395: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
4396: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
4397: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 4398: #ifdef NRCORIGINAL
4399: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
4400: #else
4401: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del); /* Intel compiler doesn't work on one line; bug reported */
1.161 brouard 4402: t= t- del*SQR(fp-fptt);
1.183 brouard 4403: #endif
1.202 brouard 4404: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 4405: #ifdef DEBUG
1.181 brouard 4406: printf("t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
4407: fprintf(ficlog,"t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
1.161 brouard 4408: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
4409: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
4410: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
4411: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
4412: printf("tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
4413: fprintf(ficlog, "tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
4414: #endif
1.183 brouard 4415: #ifdef POWELLORIGINAL
4416: if (t < 0.0) { /* Then we use it for new direction */
1.361 ! brouard 4417: #else /* Not POWELLOriginal but Brouard's */
1.182 brouard 4418: if (directest*t < 0.0) { /* Contradiction between both tests */
1.359 brouard 4419: printf("directest= %.12lf (if <0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt,del);
1.192 brouard 4420: printf("f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
1.224 brouard 4421: fprintf(ficlog,"directest= %.12lf (if directest<0 or t<0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt, del);
1.192 brouard 4422: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
4423: }
1.361 ! brouard 4424: if (directest < 0.0) { /* Then we use (P0, Pn) for new direction Xi_n or Xi_iBig */
1.181 brouard 4425: #endif
1.191 brouard 4426: #ifdef DEBUGLINMIN
1.234 brouard 4427: printf("Before linmin in direction P%d-P0\n",n);
4428: for (j=1;j<=n;j++) {
4429: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4430: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4431: if(j % ncovmodel == 0){
4432: printf("\n");
4433: fprintf(ficlog,"\n");
4434: }
4435: }
1.224 brouard 4436: #endif
4437: #ifdef LINMINORIGINAL
1.234 brouard 4438: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 4439: #else
1.234 brouard 4440: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
4441: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 4442: #endif
1.234 brouard 4443:
1.191 brouard 4444: #ifdef DEBUGLINMIN
1.234 brouard 4445: for (j=1;j<=n;j++) {
4446: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4447: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4448: if(j % ncovmodel == 0){
4449: printf("\n");
4450: fprintf(ficlog,"\n");
4451: }
4452: }
1.224 brouard 4453: #endif
1.234 brouard 4454: for (j=1;j<=n;j++) {
4455: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
4456: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
4457: }
1.361 ! brouard 4458:
! 4459: /* #else */
! 4460: /* for (i=1;i<=n-1;i++) { */
! 4461: /* for (j=1;j<=n;j++) { */
! 4462: /* xi[j][i]=xi[j][i+1]; /\* Standard method of conjugate directions, not Powell who changes the nth direction by p0 pn . *\/ */
! 4463: /* } */
! 4464: /* } */
! 4465: /* for (j=1;j<=n;j++) { */
! 4466: /* xi[j][n]=xit[j]; /\* and this nth direction by the by the average p_0 p_n *\/ */
! 4467: /* } */
! 4468: /* /\* for (j=1;j<=n-1;j++) { *\/ */
! 4469: /* /\* xi[j][1]=xi[j][j+1]; /\\* Standard method of conjugate directions *\\/ *\/ */
! 4470: /* /\* xi[j][n]=xit[j]; /\\* and this nth direction by the by the average p_0 p_n *\\/ *\/ */
! 4471: /* /\* } *\/ */
! 4472: /* #endif */
1.224 brouard 4473: #ifdef LINMINORIGINAL
4474: #else
1.234 brouard 4475: for (j=1, flatd=0;j<=n;j++) {
4476: if(flatdir[j]>0)
4477: flatd++;
4478: }
4479: if(flatd >0){
1.255 brouard 4480: printf("%d flat directions: ",flatd);
4481: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 4482: for (j=1;j<=n;j++) {
4483: if(flatdir[j]>0){
4484: printf("%d ",j);
4485: fprintf(ficlog,"%d ",j);
4486: }
4487: }
4488: printf("\n");
4489: fprintf(ficlog,"\n");
1.319 brouard 4490: #ifdef FLATSUP
4491: free_vector(xit,1,n);
4492: free_vector(xits,1,n);
4493: free_vector(ptt,1,n);
4494: free_vector(pt,1,n);
4495: return;
4496: #endif
1.361 ! brouard 4497: } /* endif(flatd >0) */
! 4498: #endif /* LINMINORIGINAL */
1.234 brouard 4499: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
4500: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
4501:
1.126 brouard 4502: #ifdef DEBUG
1.234 brouard 4503: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
4504: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
4505: for(j=1;j<=n;j++){
4506: printf(" %lf",xit[j]);
4507: fprintf(ficlog," %lf",xit[j]);
4508: }
4509: printf("\n");
4510: fprintf(ficlog,"\n");
1.126 brouard 4511: #endif
1.192 brouard 4512: } /* end of t or directest negative */
1.359 brouard 4513: printf(" Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n);
4514: fprintf(ficlog," Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n);
1.224 brouard 4515: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 4516: #else
1.234 brouard 4517: } /* end if (fptt < fp) */
1.192 brouard 4518: #endif
1.225 brouard 4519: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 4520: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 4521: #else
1.224 brouard 4522: #endif
1.234 brouard 4523: } /* loop iteration */
1.126 brouard 4524: }
1.234 brouard 4525:
1.126 brouard 4526: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 4527:
1.235 brouard 4528: double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int *ncvyear, int ij, int nres)
1.234 brouard 4529: {
1.338 brouard 4530: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 4531: * (and selected quantitative values in nres)
4532: * by left multiplying the unit
4533: * matrix by transitions matrix until convergence is reached with precision ftolpl
4534: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
4535: * Wx is row vector: population in state 1, population in state 2, population dead
4536: * or prevalence in state 1, prevalence in state 2, 0
4537: * newm is the matrix after multiplications, its rows are identical at a factor.
4538: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
4539: * Output is prlim.
4540: * Initial matrix pimij
4541: */
1.206 brouard 4542: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
4543: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
4544: /* 0, 0 , 1} */
4545: /*
4546: * and after some iteration: */
4547: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
4548: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
4549: /* 0, 0 , 1} */
4550: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
4551: /* {0.51571254859325999, 0.4842874514067399, */
4552: /* 0.51326036147820708, 0.48673963852179264} */
4553: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 4554:
1.332 brouard 4555: int i, ii,j,k, k1;
1.209 brouard 4556: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 4557: /* double **matprod2(); */ /* test */
1.218 brouard 4558: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 4559: double **newm;
1.209 brouard 4560: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 4561: int ncvloop=0;
1.288 brouard 4562: int first=0;
1.169 brouard 4563:
1.209 brouard 4564: min=vector(1,nlstate);
4565: max=vector(1,nlstate);
4566: meandiff=vector(1,nlstate);
4567:
1.218 brouard 4568: /* Starting with matrix unity */
1.126 brouard 4569: for (ii=1;ii<=nlstate+ndeath;ii++)
4570: for (j=1;j<=nlstate+ndeath;j++){
4571: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4572: }
1.169 brouard 4573:
4574: cov[1]=1.;
4575:
4576: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 4577: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 4578: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 4579: ncvloop++;
1.126 brouard 4580: newm=savm;
4581: /* Covariates have to be included here again */
1.138 brouard 4582: cov[2]=agefin;
1.319 brouard 4583: if(nagesqr==1){
4584: cov[3]= agefin*agefin;
4585: }
1.332 brouard 4586: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
4587: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
4588: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 4589: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 4590: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
4591: }else{
4592: cov[2+nagesqr+k1]=precov[nres][k1];
4593: }
4594: }/* End of loop on model equation */
4595:
4596: /* Start of old code (replaced by a loop on position in the model equation */
4597: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
4598: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
4599: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
4600: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
4601: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
4602: /* * k 1 2 3 4 5 6 7 8 */
4603: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
4604: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
4605: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
4606: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
4607: /* *nsd=3 (1) (2) (3) */
4608: /* *TvarsD[nsd] [1]=2 1 3 */
4609: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
4610: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
4611: /* *Tage[] [1]=1 [2]=2 [3]=3 */
4612: /* *Tvard[] [1][1]=1 [2][1]=1 */
4613: /* * [1][2]=3 [2][2]=2 */
4614: /* *Tprod[](=k) [1]=1 [2]=8 */
4615: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
4616: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
4617: /* *TvarsDpType */
4618: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
4619: /* * nsd=1 (1) (2) */
4620: /* *TvarsD[nsd] 3 2 */
4621: /* *TnsdVar (3)=1 (2)=2 */
4622: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
4623: /* *Tage[] [1]=2 [2]= 3 */
4624: /* *\/ */
4625: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
4626: /* /\* printf("prevalim Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
4627: /* } */
4628: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
4629: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
4630: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
4631: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
4632: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
4633: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
4634: /* /\* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
4635: /* } */
4636: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
4637: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
4638: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
4639: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
4640: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
4641: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
4642: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
4643: /* } */
4644: /* /\* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
4645: /* } */
4646: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
4647: /* /\* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); *\/ */
4648: /* if(Dummy[Tvard[k][1]]==0){ */
4649: /* if(Dummy[Tvard[k][2]]==0){ */
4650: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
4651: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
4652: /* }else{ */
4653: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
4654: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
4655: /* } */
4656: /* }else{ */
4657: /* if(Dummy[Tvard[k][2]]==0){ */
4658: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
4659: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
4660: /* }else{ */
4661: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
4662: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
4663: /* } */
4664: /* } */
4665: /* } /\* End product without age *\/ */
4666: /* ENd of old code */
1.138 brouard 4667: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
4668: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
4669: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 4670: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4671: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 4672: /* age and covariate values of ij are in 'cov' */
1.142 brouard 4673: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 4674:
1.126 brouard 4675: savm=oldm;
4676: oldm=newm;
1.209 brouard 4677:
4678: for(j=1; j<=nlstate; j++){
4679: max[j]=0.;
4680: min[j]=1.;
4681: }
4682: for(i=1;i<=nlstate;i++){
4683: sumnew=0;
4684: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
4685: for(j=1; j<=nlstate; j++){
4686: prlim[i][j]= newm[i][j]/(1-sumnew);
4687: max[j]=FMAX(max[j],prlim[i][j]);
4688: min[j]=FMIN(min[j],prlim[i][j]);
4689: }
4690: }
4691:
1.126 brouard 4692: maxmax=0.;
1.209 brouard 4693: for(j=1; j<=nlstate; j++){
4694: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
4695: maxmax=FMAX(maxmax,meandiff[j]);
4696: /* printf(" age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, j, meandiff[j],(int)agefin, j, max[j], j, min[j],maxmax); */
1.169 brouard 4697: } /* j loop */
1.203 brouard 4698: *ncvyear= (int)age- (int)agefin;
1.208 brouard 4699: /* printf("maxmax=%lf maxmin=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, maxmin, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.126 brouard 4700: if(maxmax < ftolpl){
1.209 brouard 4701: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
4702: free_vector(min,1,nlstate);
4703: free_vector(max,1,nlstate);
4704: free_vector(meandiff,1,nlstate);
1.126 brouard 4705: return prlim;
4706: }
1.288 brouard 4707: } /* agefin loop */
1.208 brouard 4708: /* After some age loop it doesn't converge */
1.288 brouard 4709: if(!first){
4710: first=1;
4711: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d). Others in log file only...\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
1.317 brouard 4712: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
4713: }else if (first >=1 && first <10){
4714: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
4715: first++;
4716: }else if (first ==10){
4717: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
4718: printf("Warning: the stable prevalence dit not converge. This warning came too often, IMaCh will stop notifying, even in its log file. Look at the graphs to appreciate the non convergence.\n");
4719: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
4720: first++;
1.288 brouard 4721: }
4722:
1.359 brouard 4723: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl,
4724: * (int)age, (int)delaymax, (int)agefin, ncvloop,
4725: * (int)age-(int)agefin); */
1.209 brouard 4726: free_vector(min,1,nlstate);
4727: free_vector(max,1,nlstate);
4728: free_vector(meandiff,1,nlstate);
1.208 brouard 4729:
1.169 brouard 4730: return prlim; /* should not reach here */
1.126 brouard 4731: }
4732:
1.217 brouard 4733:
4734: /**** Back Prevalence limit (stable or period prevalence) ****************/
4735:
1.218 brouard 4736: /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ageminpar, double agemaxpar, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
4737: /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
1.242 brouard 4738: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 4739: {
1.264 brouard 4740: /* Computes the prevalence limit in each live state at age x and for covariate combination ij (<=2**cptcoveff) by left multiplying the unit
1.217 brouard 4741: matrix by transitions matrix until convergence is reached with precision ftolpl */
4742: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
4743: /* Wx is row vector: population in state 1, population in state 2, population dead */
4744: /* or prevalence in state 1, prevalence in state 2, 0 */
4745: /* newm is the matrix after multiplications, its rows are identical at a factor */
4746: /* Initial matrix pimij */
4747: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
4748: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
4749: /* 0, 0 , 1} */
4750: /*
4751: * and after some iteration: */
4752: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
4753: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
4754: /* 0, 0 , 1} */
4755: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
4756: /* {0.51571254859325999, 0.4842874514067399, */
4757: /* 0.51326036147820708, 0.48673963852179264} */
4758: /* If we start from prlim again, prlim tends to a constant matrix */
4759:
1.359 brouard 4760: int i, ii,j, k1;
1.247 brouard 4761: int first=0;
1.217 brouard 4762: double *min, *max, *meandiff, maxmax,sumnew=0.;
4763: /* double **matprod2(); */ /* test */
4764: double **out, cov[NCOVMAX+1], **bmij();
4765: double **newm;
1.218 brouard 4766: double **dnewm, **doldm, **dsavm; /* for use */
4767: double **oldm, **savm; /* for use */
4768:
1.217 brouard 4769: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
4770: int ncvloop=0;
4771:
4772: min=vector(1,nlstate);
4773: max=vector(1,nlstate);
4774: meandiff=vector(1,nlstate);
4775:
1.266 brouard 4776: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
4777: oldm=oldms; savm=savms;
4778:
4779: /* Starting with matrix unity */
4780: for (ii=1;ii<=nlstate+ndeath;ii++)
4781: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 4782: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4783: }
4784:
4785: cov[1]=1.;
4786:
4787: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
4788: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 4789: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 4790: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
4791: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 4792: ncvloop++;
1.218 brouard 4793: newm=savm; /* oldm should be kept from previous iteration or unity at start */
4794: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 4795: /* Covariates have to be included here again */
4796: cov[2]=agefin;
1.319 brouard 4797: if(nagesqr==1){
1.217 brouard 4798: cov[3]= agefin*agefin;;
1.319 brouard 4799: }
1.332 brouard 4800: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 4801: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 4802: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 4803: }else{
1.332 brouard 4804: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 4805: }
1.332 brouard 4806: }/* End of loop on model equation */
4807:
4808: /* Old code */
4809:
4810: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
4811: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
4812: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
4813: /* /\* printf("bprevalim Dummy agefin=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agefin,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
4814: /* } */
4815: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
4816: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
4817: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
4818: /* /\* /\\* printf("prevalim ij=%d k=%d Tvar[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, Tvar[k],nbcode[Tvar[k]][codtabm(ij,Tvar[k])],cov[2+k], ij, k, codtabm(ij,Tvar[k])]); *\\/ *\/ */
4819: /* /\* } *\/ */
4820: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
4821: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
4822: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
4823: /* /\* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
4824: /* } */
4825: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
4826: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
4827: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
4828: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
4829: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
4830: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
4831: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
4832: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
4833: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
4834: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
4835: /* } */
4836: /* /\* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
4837: /* } */
4838: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
4839: /* /\* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); *\/ */
4840: /* if(Dummy[Tvard[k][1]]==0){ */
4841: /* if(Dummy[Tvard[k][2]]==0){ */
4842: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
4843: /* }else{ */
4844: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
4845: /* } */
4846: /* }else{ */
4847: /* if(Dummy[Tvard[k][2]]==0){ */
4848: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
4849: /* }else{ */
4850: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
4851: /* } */
4852: /* } */
4853: /* } */
1.217 brouard 4854:
4855: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
4856: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
4857: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
4858: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4859: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 4860: /* ij should be linked to the correct index of cov */
4861: /* age and covariate values ij are in 'cov', but we need to pass
4862: * ij for the observed prevalence at age and status and covariate
4863: * number: prevacurrent[(int)agefin][ii][ij]
4864: */
4865: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, ageminpar, agemaxpar, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
4866: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
4867: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */
1.268 brouard 4868: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 4869: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
4870: /* for(i=1; i<=nlstate+ndeath; i++) { */
4871: /* printf("%d newm= ",i); */
4872: /* for(j=1;j<=nlstate+ndeath;j++) { */
4873: /* printf("%f ",newm[i][j]); */
4874: /* } */
4875: /* printf("oldm * "); */
4876: /* for(j=1;j<=nlstate+ndeath;j++) { */
4877: /* printf("%f ",oldm[i][j]); */
4878: /* } */
1.268 brouard 4879: /* printf(" bmmij "); */
1.266 brouard 4880: /* for(j=1;j<=nlstate+ndeath;j++) { */
4881: /* printf("%f ",pmmij[i][j]); */
4882: /* } */
4883: /* printf("\n"); */
4884: /* } */
4885: /* } */
1.217 brouard 4886: savm=oldm;
4887: oldm=newm;
1.266 brouard 4888:
1.217 brouard 4889: for(j=1; j<=nlstate; j++){
4890: max[j]=0.;
4891: min[j]=1.;
4892: }
4893: for(j=1; j<=nlstate; j++){
4894: for(i=1;i<=nlstate;i++){
1.234 brouard 4895: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
4896: bprlim[i][j]= newm[i][j];
4897: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
4898: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 4899: }
4900: }
1.218 brouard 4901:
1.217 brouard 4902: maxmax=0.;
4903: for(i=1; i<=nlstate; i++){
1.318 brouard 4904: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 4905: maxmax=FMAX(maxmax,meandiff[i]);
4906: /* printf("Back age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, i, meandiff[i],(int)agefin, i, max[i], i, min[i],maxmax); */
1.268 brouard 4907: } /* i loop */
1.217 brouard 4908: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 4909: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 4910: if(maxmax < ftolpl){
1.220 brouard 4911: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 4912: free_vector(min,1,nlstate);
4913: free_vector(max,1,nlstate);
4914: free_vector(meandiff,1,nlstate);
4915: return bprlim;
4916: }
1.288 brouard 4917: } /* agefin loop */
1.217 brouard 4918: /* After some age loop it doesn't converge */
1.288 brouard 4919: if(!first){
1.247 brouard 4920: first=1;
4921: printf("Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. Others in log file only...\n\
4922: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
4923: }
4924: fprintf(ficlog,"Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\
1.217 brouard 4925: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
4926: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */
4927: free_vector(min,1,nlstate);
4928: free_vector(max,1,nlstate);
4929: free_vector(meandiff,1,nlstate);
4930:
4931: return bprlim; /* should not reach here */
4932: }
4933:
1.126 brouard 4934: /*************** transition probabilities ***************/
4935:
4936: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
4937: {
1.138 brouard 4938: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 4939: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 4940: model to the ncovmodel covariates (including constant and age).
4941: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
4942: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
4943: ncth covariate in the global vector x is given by the formula:
4944: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
4945: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
4946: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
4947: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 4948: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 4949: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 4950: Sum on j ps[i][j] should equal to 1.
1.138 brouard 4951: */
4952: double s1, lnpijopii;
1.126 brouard 4953: /*double t34;*/
1.164 brouard 4954: int i,j, nc, ii, jj;
1.126 brouard 4955:
1.223 brouard 4956: for(i=1; i<= nlstate; i++){
4957: for(j=1; j<i;j++){
4958: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
4959: /*lnpijopii += param[i][j][nc]*cov[nc];*/
4960: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
4961: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
4962: }
4963: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 4964: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 4965: }
4966: for(j=i+1; j<=nlstate+ndeath;j++){
4967: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
4968: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
4969: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
4970: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
4971: }
4972: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 4973: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 4974: }
4975: }
1.218 brouard 4976:
1.223 brouard 4977: for(i=1; i<= nlstate; i++){
4978: s1=0;
4979: for(j=1; j<i; j++){
1.339 brouard 4980: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 4981: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
4982: }
4983: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 4984: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 4985: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
4986: }
4987: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
4988: ps[i][i]=1./(s1+1.);
4989: /* Computing other pijs */
4990: for(j=1; j<i; j++)
1.325 brouard 4991: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 4992: for(j=i+1; j<=nlstate+ndeath; j++)
4993: ps[i][j]= exp(ps[i][j])*ps[i][i];
4994: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
4995: } /* end i */
1.218 brouard 4996:
1.223 brouard 4997: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
4998: for(jj=1; jj<= nlstate+ndeath; jj++){
4999: ps[ii][jj]=0;
5000: ps[ii][ii]=1;
5001: }
5002: }
1.294 brouard 5003:
5004:
1.223 brouard 5005: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
5006: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
5007: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
5008: /* } */
5009: /* printf("\n "); */
5010: /* } */
5011: /* printf("\n ");printf("%lf ",cov[2]);*/
5012: /*
5013: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 5014: goto end;*/
1.266 brouard 5015: return ps; /* Pointer is unchanged since its call */
1.126 brouard 5016: }
5017:
1.218 brouard 5018: /*************** backward transition probabilities ***************/
5019:
5020: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ageminpar, double agemaxpar, double ***dnewm, double **doldm, double **dsavm, int ij ) */
5021: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
5022: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
5023: {
1.302 brouard 5024: /* Computes the backward probability at age agefin, cov[2], and covariate combination 'ij'. In fact cov is already filled and x too.
1.266 brouard 5025: * Call to pmij(cov and x), call to cross prevalence, sums and inverses, left multiply, and returns in **ps as well as **bmij.
1.222 brouard 5026: */
1.359 brouard 5027: int ii, j;
1.222 brouard 5028:
1.359 brouard 5029: double **pmij();
1.222 brouard 5030: double sumnew=0.;
1.218 brouard 5031: double agefin;
1.292 brouard 5032: double k3=0.; /* constant of the w_x diagonal matrix (in order for B to sum to 1 even for death state) */
1.222 brouard 5033: double **dnewm, **dsavm, **doldm;
5034: double **bbmij;
5035:
1.218 brouard 5036: doldm=ddoldms; /* global pointers */
1.222 brouard 5037: dnewm=ddnewms;
5038: dsavm=ddsavms;
1.318 brouard 5039:
5040: /* Debug */
5041: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 5042: agefin=cov[2];
1.268 brouard 5043: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 5044: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 5045: the observed prevalence (with this covariate ij) at beginning of transition */
5046: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 5047:
5048: /* P_x */
1.325 brouard 5049: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 5050: /* outputs pmmij which is a stochastic matrix in row */
5051:
5052: /* Diag(w_x) */
1.292 brouard 5053: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 5054: sumnew=0.;
1.269 brouard 5055: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 5056: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 5057: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 5058: sumnew+=prevacurrent[(int)agefin][ii][ij];
5059: }
5060: if(sumnew >0.01){ /* At least some value in the prevalence */
5061: for (ii=1;ii<=nlstate+ndeath;ii++){
5062: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 5063: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 5064: }
5065: }else{
5066: for (ii=1;ii<=nlstate+ndeath;ii++){
5067: for (j=1;j<=nlstate+ndeath;j++)
5068: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
5069: }
5070: /* if(sumnew <0.9){ */
5071: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
5072: /* } */
5073: }
5074: k3=0.0; /* We put the last diagonal to 0 */
5075: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
5076: doldm[ii][ii]= k3;
5077: }
5078: /* End doldm, At the end doldm is diag[(w_i)] */
5079:
1.292 brouard 5080: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
5081: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 5082:
1.292 brouard 5083: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 5084: /* w1 p11 + w2 p21 only on live states N1./N..*N11/N1. + N2./N..*N21/N2.=(N11+N21)/N..=N.1/N.. */
1.222 brouard 5085: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 5086: sumnew=0.;
1.222 brouard 5087: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 5088: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 5089: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 5090: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 5091: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 5092: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 5093: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 5094: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 5095: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 5096: /* }else */
1.268 brouard 5097: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
5098: } /*End ii */
5099: } /* End j, At the end dsavm is diag[1/(w_1p1i+w_2 p2i)] for ALL states even if the sum is only for live states */
5100:
1.292 brouard 5101: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 5102: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 5103: /* end bmij */
1.266 brouard 5104: return ps; /*pointer is unchanged */
1.218 brouard 5105: }
1.217 brouard 5106: /*************** transition probabilities ***************/
5107:
1.218 brouard 5108: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 5109: {
5110: /* According to parameters values stored in x and the covariate's values stored in cov,
5111: computes the probability to be observed in state j being in state i by appying the
5112: model to the ncovmodel covariates (including constant and age).
5113: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
5114: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
5115: ncth covariate in the global vector x is given by the formula:
5116: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
5117: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
5118: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
5119: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
5120: Outputs ps[i][j] the probability to be observed in j being in j according to
5121: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
5122: */
5123: double s1, lnpijopii;
5124: /*double t34;*/
5125: int i,j, nc, ii, jj;
5126:
1.234 brouard 5127: for(i=1; i<= nlstate; i++){
5128: for(j=1; j<i;j++){
5129: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
5130: /*lnpijopii += param[i][j][nc]*cov[nc];*/
5131: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
5132: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
5133: }
5134: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
5135: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
5136: }
5137: for(j=i+1; j<=nlstate+ndeath;j++){
5138: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
5139: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
5140: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
5141: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
5142: }
5143: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
5144: }
5145: }
5146:
5147: for(i=1; i<= nlstate; i++){
5148: s1=0;
5149: for(j=1; j<i; j++){
5150: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5151: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
5152: }
5153: for(j=i+1; j<=nlstate+ndeath; j++){
5154: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5155: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
5156: }
5157: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
5158: ps[i][i]=1./(s1+1.);
5159: /* Computing other pijs */
5160: for(j=1; j<i; j++)
5161: ps[i][j]= exp(ps[i][j])*ps[i][i];
5162: for(j=i+1; j<=nlstate+ndeath; j++)
5163: ps[i][j]= exp(ps[i][j])*ps[i][i];
5164: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
5165: } /* end i */
5166:
5167: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
5168: for(jj=1; jj<= nlstate+ndeath; jj++){
5169: ps[ii][jj]=0;
5170: ps[ii][ii]=1;
5171: }
5172: }
1.296 brouard 5173: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 5174: for(jj=1; jj<= nlstate+ndeath; jj++){
5175: s1=0.;
5176: for(ii=1; ii<= nlstate+ndeath; ii++){
5177: s1+=ps[ii][jj];
5178: }
5179: for(ii=1; ii<= nlstate; ii++){
5180: ps[ii][jj]=ps[ii][jj]/s1;
5181: }
5182: }
5183: /* Transposition */
5184: for(jj=1; jj<= nlstate+ndeath; jj++){
5185: for(ii=jj; ii<= nlstate+ndeath; ii++){
5186: s1=ps[ii][jj];
5187: ps[ii][jj]=ps[jj][ii];
5188: ps[jj][ii]=s1;
5189: }
5190: }
5191: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
5192: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
5193: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
5194: /* } */
5195: /* printf("\n "); */
5196: /* } */
5197: /* printf("\n ");printf("%lf ",cov[2]);*/
5198: /*
5199: for(i=1; i<= npar; i++) printf("%f ",x[i]);
5200: goto end;*/
5201: return ps;
1.217 brouard 5202: }
5203:
5204:
1.126 brouard 5205: /**************** Product of 2 matrices ******************/
5206:
1.145 brouard 5207: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 5208: {
5209: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
5210: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
5211: /* in, b, out are matrice of pointers which should have been initialized
5212: before: only the contents of out is modified. The function returns
5213: a pointer to pointers identical to out */
1.145 brouard 5214: int i, j, k;
1.126 brouard 5215: for(i=nrl; i<= nrh; i++)
1.145 brouard 5216: for(k=ncolol; k<=ncoloh; k++){
5217: out[i][k]=0.;
5218: for(j=ncl; j<=nch; j++)
5219: out[i][k] +=in[i][j]*b[j][k];
5220: }
1.126 brouard 5221: return out;
5222: }
5223:
5224:
5225: /************* Higher Matrix Product ***************/
5226:
1.235 brouard 5227: double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm, int ij, int nres )
1.126 brouard 5228: {
1.336 brouard 5229: /* Already optimized with precov.
5230: Computes the transition matrix starting at age 'age' and dummies values in each resultline (loop on ij to find the corresponding combination) to over
1.126 brouard 5231: 'nhstepm*hstepm*stepm' months (i.e. until
5232: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
5233: nhstepm*hstepm matrices.
5234: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
5235: (typically every 2 years instead of every month which is too big
5236: for the memory).
5237: Model is determined by parameters x and covariates have to be
5238: included manually here.
5239:
5240: */
5241:
1.359 brouard 5242: int i, j, d, h, k1;
1.131 brouard 5243: double **out, cov[NCOVMAX+1];
1.126 brouard 5244: double **newm;
1.187 brouard 5245: double agexact;
1.359 brouard 5246: /*double agebegin, ageend;*/
1.126 brouard 5247:
5248: /* Hstepm could be zero and should return the unit matrix */
5249: for (i=1;i<=nlstate+ndeath;i++)
5250: for (j=1;j<=nlstate+ndeath;j++){
5251: oldm[i][j]=(i==j ? 1.0 : 0.0);
5252: po[i][j][0]=(i==j ? 1.0 : 0.0);
5253: }
5254: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
5255: for(h=1; h <=nhstepm; h++){
5256: for(d=1; d <=hstepm; d++){
5257: newm=savm;
5258: /* Covariates have to be included here again */
5259: cov[1]=1.;
1.214 brouard 5260: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 5261: cov[2]=agexact;
1.319 brouard 5262: if(nagesqr==1){
1.227 brouard 5263: cov[3]= agexact*agexact;
1.319 brouard 5264: }
1.330 brouard 5265: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
5266: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
5267: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 5268: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 5269: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
5270: }else{
5271: cov[2+nagesqr+k1]=precov[nres][k1];
5272: }
5273: }/* End of loop on model equation */
5274: /* Old code */
5275: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
5276: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
5277: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
5278: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
5279: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
5280: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
5281: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
5282: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
5283: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
5284: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
5285: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
5286: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
5287: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
5288: /* /\* printf("hpxij Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,TnsdVar[TvarsD[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,TnsdVar[TvarsD[k]])); *\/ */
5289: /* printf("hpxij Dummy combi=%d k1=%d Tvar[%d]=V%d cov[2+%d+%d]=%lf resultmodel[nres][%d]=%d nres/nresult=%d/%d \n",ij,k1,k1, Tvar[k1],nagesqr,k1,cov[2+nagesqr+k1],k1,resultmodel[nres][k1],nres,nresult); */
5290: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5291: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
5292: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
5293: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
5294: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
5295: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
5296: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
5297: /* printf("hPxij Quantitative k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
5298: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5299: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
5300: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
5301: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
5302: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
5303: /* printf("DhPxij Dummy with age k1=%d Tvar[%d]=%d TinvDoQresult[nres=%d][%d]=%.f age=%.2f,cov[2+%d+%d]=%.3f\n",k1,k1,Tvar[k1],nres,TinvDoQresult[nres][Tvar[k1]],cov[2],nagesqr,k1,cov[2+nagesqr+k1]); */
5304: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
5305:
5306: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
5307: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
5308: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
5309: /* /\* *\/ */
1.330 brouard 5310: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
5311: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
5312: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 5313: /* /\*cptcovage=2 1 2 *\/ */
5314: /* /\*Tage[k]= 5 8 *\/ */
5315: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
5316: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
5317: /* printf("QhPxij Quant with age k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
5318: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
5319: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
5320: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
5321: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
5322: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
5323: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
5324: /* /\* printf("hPxij Age combi=%d k=%d cptcovage=%d Tage[%d]=%d Tvar[Tage[%d]]=V%d nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]]])]=%d nres=%d\n",ij,k,cptcovage,k,Tage[k],k,Tvar[Tage[k]], nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]])],nres); *\/ */
5325: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
5326: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
5327: /* /\* } *\/ */
5328: /* /\* printf("hPxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
5329: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
5330: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
5331: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
5332: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
5333: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
5334: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
5335: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
5336: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
5337: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 5338:
1.332 brouard 5339: /* /\* printf("hPxij Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]=%d nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]=%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2],nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])],nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]); *\/ */
5340: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
5341: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
5342: /* printf("hPxij Prod ij=%d k1=%d cov[2+%d+%d]=%.5f Tvard[%d][1]=V%d * Tvard[%d][2]=V%d ; TinvDoQresult[nres][Tvardk[k1][1]]=%.4f * TinvDoQresult[nres][Tvardk[k1][1]]=%.4f\n",ij,k1,nagesqr,k1,cov[2+nagesqr+k1],k1,Tvardk[k1][1], k1,Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][1]], TinvDoQresult[nres][Tvardk[k1][2]]); */
5343: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5344:
5345: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
5346: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
5347: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
5348: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
5349: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])]; *\/ */
5350: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
5351: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
5352: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
5353: /* /\* } *\/ */
5354: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
5355: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
5356: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
5357: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
5358: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
5359: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
5360: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
5361: /* /\* } *\/ */
5362: /* /\* }/\\*end of products quantitative *\\/ *\/ */
5363: /* }/\*end of products *\/ */
5364: /* } /\* End of loop on model equation *\/ */
1.235 brouard 5365: /* for (k=1; k<=cptcovn;k++) */
5366: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
5367: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
5368: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
5369: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
5370: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 5371:
5372:
1.126 brouard 5373: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
5374: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 5375: /* right multiplication of oldm by the current matrix */
1.126 brouard 5376: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
5377: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 5378: /* if((int)age == 70){ */
5379: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
5380: /* for(i=1; i<=nlstate+ndeath; i++) { */
5381: /* printf("%d pmmij ",i); */
5382: /* for(j=1;j<=nlstate+ndeath;j++) { */
5383: /* printf("%f ",pmmij[i][j]); */
5384: /* } */
5385: /* printf(" oldm "); */
5386: /* for(j=1;j<=nlstate+ndeath;j++) { */
5387: /* printf("%f ",oldm[i][j]); */
5388: /* } */
5389: /* printf("\n"); */
5390: /* } */
5391: /* } */
1.126 brouard 5392: savm=oldm;
5393: oldm=newm;
5394: }
5395: for(i=1; i<=nlstate+ndeath; i++)
5396: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 5397: po[i][j][h]=newm[i][j];
5398: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 5399: }
1.128 brouard 5400: /*printf("h=%d ",h);*/
1.126 brouard 5401: } /* end h */
1.267 brouard 5402: /* printf("\n H=%d \n",h); */
1.126 brouard 5403: return po;
5404: }
5405:
1.217 brouard 5406: /************* Higher Back Matrix Product ***************/
1.218 brouard 5407: /* double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, int ij ) */
1.267 brouard 5408: double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, int ij, int nres )
1.217 brouard 5409: {
1.332 brouard 5410: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
5411: computes the transition matrix starting at age 'age' over
1.217 brouard 5412: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 5413: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
5414: nhstepm*hstepm matrices.
5415: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
5416: (typically every 2 years instead of every month which is too big
1.217 brouard 5417: for the memory).
1.218 brouard 5418: Model is determined by parameters x and covariates have to be
1.266 brouard 5419: included manually here. Then we use a call to bmij(x and cov)
5420: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 5421: */
1.217 brouard 5422:
1.359 brouard 5423: int i, j, d, h, k1;
1.266 brouard 5424: double **out, cov[NCOVMAX+1], **bmij();
5425: double **newm, ***newmm;
1.217 brouard 5426: double agexact;
1.359 brouard 5427: /*double agebegin, ageend;*/
1.222 brouard 5428: double **oldm, **savm;
1.217 brouard 5429:
1.266 brouard 5430: newmm=po; /* To be saved */
5431: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 5432: /* Hstepm could be zero and should return the unit matrix */
5433: for (i=1;i<=nlstate+ndeath;i++)
5434: for (j=1;j<=nlstate+ndeath;j++){
5435: oldm[i][j]=(i==j ? 1.0 : 0.0);
5436: po[i][j][0]=(i==j ? 1.0 : 0.0);
5437: }
5438: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
5439: for(h=1; h <=nhstepm; h++){
5440: for(d=1; d <=hstepm; d++){
5441: newm=savm;
5442: /* Covariates have to be included here again */
5443: cov[1]=1.;
1.271 brouard 5444: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 5445: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 5446: /* Debug */
5447: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 5448: cov[2]=agexact;
1.332 brouard 5449: if(nagesqr==1){
1.222 brouard 5450: cov[3]= agexact*agexact;
1.332 brouard 5451: }
5452: /** New code */
5453: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 5454: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 5455: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 5456: }else{
1.332 brouard 5457: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 5458: }
1.332 brouard 5459: }/* End of loop on model equation */
5460: /** End of new code */
5461: /** This was old code */
5462: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
5463: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
5464: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
5465: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
5466: /* /\* printf("hbxij Dummy agexact=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agexact,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
5467: /* } */
5468: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
5469: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
5470: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
5471: /* /\* printf("hPxij Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
5472: /* } */
5473: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
5474: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
5475: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
5476: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
5477: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
5478: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
5479: /* } */
5480: /* /\* printf("hBxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
5481: /* } */
5482: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
5483: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
5484: /* if(Dummy[Tvard[k][1]]==0){ */
5485: /* if(Dummy[Tvard[k][2]]==0){ */
5486: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
5487: /* }else{ */
5488: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
5489: /* } */
5490: /* }else{ */
5491: /* if(Dummy[Tvard[k][2]]==0){ */
5492: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
5493: /* }else{ */
5494: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
5495: /* } */
5496: /* } */
5497: /* } */
5498: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
5499: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
5500: /** End of old code */
5501:
1.218 brouard 5502: /* Careful transposed matrix */
1.266 brouard 5503: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 5504: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 5505: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 5506: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 5507: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 5508: /* if((int)age == 70){ */
5509: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
5510: /* for(i=1; i<=nlstate+ndeath; i++) { */
5511: /* printf("%d pmmij ",i); */
5512: /* for(j=1;j<=nlstate+ndeath;j++) { */
5513: /* printf("%f ",pmmij[i][j]); */
5514: /* } */
5515: /* printf(" oldm "); */
5516: /* for(j=1;j<=nlstate+ndeath;j++) { */
5517: /* printf("%f ",oldm[i][j]); */
5518: /* } */
5519: /* printf("\n"); */
5520: /* } */
5521: /* } */
5522: savm=oldm;
5523: oldm=newm;
5524: }
5525: for(i=1; i<=nlstate+ndeath; i++)
5526: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 5527: po[i][j][h]=newm[i][j];
1.268 brouard 5528: /* if(h==nhstepm) */
5529: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 5530: }
1.268 brouard 5531: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 5532: } /* end h */
1.268 brouard 5533: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 5534: return po;
5535: }
5536:
5537:
1.162 brouard 5538: #ifdef NLOPT
5539: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
5540: double fret;
5541: double *xt;
5542: int j;
5543: myfunc_data *d2 = (myfunc_data *) pd;
5544: /* xt = (p1-1); */
5545: xt=vector(1,n);
5546: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
5547:
5548: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
5549: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
5550: printf("Function = %.12lf ",fret);
5551: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
5552: printf("\n");
5553: free_vector(xt,1,n);
5554: return fret;
5555: }
5556: #endif
1.126 brouard 5557:
5558: /*************** log-likelihood *************/
5559: double func( double *x)
5560: {
1.336 brouard 5561: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 5562: int ioffset=0;
1.339 brouard 5563: int ipos=0,iposold=0,ncovv=0;
5564:
1.340 brouard 5565: double cotvarv, cotvarvold;
1.226 brouard 5566: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
5567: double **out;
5568: double lli; /* Individual log likelihood */
5569: int s1, s2;
1.228 brouard 5570: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
1.336 brouard 5571:
1.226 brouard 5572: double bbh, survp;
5573: double agexact;
1.336 brouard 5574: double agebegin, ageend;
1.226 brouard 5575: /*extern weight */
5576: /* We are differentiating ll according to initial status */
5577: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
5578: /*for(i=1;i<imx;i++)
5579: printf(" %d\n",s[4][i]);
5580: */
1.162 brouard 5581:
1.226 brouard 5582: ++countcallfunc;
1.162 brouard 5583:
1.226 brouard 5584: cov[1]=1.;
1.126 brouard 5585:
1.226 brouard 5586: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 5587: ioffset=0;
1.226 brouard 5588: if(mle==1){
5589: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5590: /* Computes the values of the ncovmodel covariates of the model
5591: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
5592: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
5593: to be observed in j being in i according to the model.
5594: */
1.243 brouard 5595: ioffset=2+nagesqr ;
1.233 brouard 5596: /* Fixed */
1.345 brouard 5597: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 5598: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
5599: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
5600: /* TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 5601: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 5602: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/
1.319 brouard 5603: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 5604: }
1.226 brouard 5605: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 5606: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 5607: has been calculated etc */
5608: /* For an individual i, wav[i] gives the number of effective waves */
5609: /* We compute the contribution to Likelihood of each effective transition
5610: mw[mi][i] is real wave of the mi th effectve wave */
5611: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
5612: s2=s[mw[mi+1][i]][i];
1.341 brouard 5613: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i] because now is moved after nvocol+nqv
1.226 brouard 5614: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
5615: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
5616: */
1.336 brouard 5617: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
5618: /* Wave varying (but not age varying) */
1.339 brouard 5619: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates in the model (single and product but no age )"V5+V4+V3+V4*V3+V5*age+V1*age+V1" +TvarVind 1,2,3,4(V4*V3) Tvar[1]@7{5, 4, 3, 6, 5, 1, 1 ; 6 because the created covar is after V5 and is 6, minus 1+1, 3,2,1,4 positions in cotvar*\/ */
5620: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
5621: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
5622: /* } */
1.340 brouard 5623: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
5624: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
5625: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 5626: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 5627: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 5628: }else{ /* fixed covariate */
1.345 brouard 5629: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
1.340 brouard 5630: }
1.339 brouard 5631: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 5632: cotvarvold=cotvarv;
5633: }else{ /* A second product */
5634: cotvarv=cotvarv*cotvarvold;
1.339 brouard 5635: }
5636: iposold=ipos;
1.340 brouard 5637: cov[ioffset+ipos]=cotvarv;
1.234 brouard 5638: }
1.339 brouard 5639: /* for products of time varying to be done */
1.234 brouard 5640: for (ii=1;ii<=nlstate+ndeath;ii++)
5641: for (j=1;j<=nlstate+ndeath;j++){
5642: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5643: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5644: }
1.336 brouard 5645:
5646: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
5647: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
1.234 brouard 5648: for(d=0; d<dh[mi][i]; d++){
5649: newm=savm;
5650: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5651: cov[2]=agexact;
5652: if(nagesqr==1)
5653: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 5654: /* for (kk=1; kk<=cptcovage;kk++) { */
5655: /* if(!FixedV[Tvar[Tage[kk]]]) */
5656: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
5657: /* else */
5658: /* cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
5659: /* } */
5660: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
5661: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
5662: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
5663: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
5664: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
5665: }else{ /* fixed covariate */
5666: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
5667: }
5668: if(ipos!=iposold){ /* Not a product or first of a product */
5669: cotvarvold=cotvarv;
5670: }else{ /* A second product */
5671: cotvarv=cotvarv*cotvarvold;
5672: }
5673: iposold=ipos;
5674: cov[ioffset+ipos]=cotvarv*agexact;
5675: /* For products */
1.234 brouard 5676: }
1.349 brouard 5677:
1.234 brouard 5678: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5679: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5680: savm=oldm;
5681: oldm=newm;
5682: } /* end mult */
5683:
5684: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
5685: /* But now since version 0.9 we anticipate for bias at large stepm.
5686: * If stepm is larger than one month (smallest stepm) and if the exact delay
5687: * (in months) between two waves is not a multiple of stepm, we rounded to
5688: * the nearest (and in case of equal distance, to the lowest) interval but now
5689: * we keep into memory the bias bh[mi][i] and also the previous matrix product
5690: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
5691: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 5692: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
5693: * -stepm/2 to stepm/2 .
5694: * For stepm=1 the results are the same as for previous versions of Imach.
5695: * For stepm > 1 the results are less biased than in previous versions.
5696: */
1.234 brouard 5697: s1=s[mw[mi][i]][i];
5698: s2=s[mw[mi+1][i]][i];
5699: bbh=(double)bh[mi][i]/(double)stepm;
5700: /* bias bh is positive if real duration
5701: * is higher than the multiple of stepm and negative otherwise.
5702: */
5703: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
5704: if( s2 > nlstate){
5705: /* i.e. if s2 is a death state and if the date of death is known
5706: then the contribution to the likelihood is the probability to
5707: die between last step unit time and current step unit time,
5708: which is also equal to probability to die before dh
5709: minus probability to die before dh-stepm .
5710: In version up to 0.92 likelihood was computed
5711: as if date of death was unknown. Death was treated as any other
5712: health state: the date of the interview describes the actual state
5713: and not the date of a change in health state. The former idea was
5714: to consider that at each interview the state was recorded
5715: (healthy, disable or death) and IMaCh was corrected; but when we
5716: introduced the exact date of death then we should have modified
5717: the contribution of an exact death to the likelihood. This new
5718: contribution is smaller and very dependent of the step unit
5719: stepm. It is no more the probability to die between last interview
5720: and month of death but the probability to survive from last
5721: interview up to one month before death multiplied by the
5722: probability to die within a month. Thanks to Chris
5723: Jackson for correcting this bug. Former versions increased
5724: mortality artificially. The bad side is that we add another loop
5725: which slows down the processing. The difference can be up to 10%
5726: lower mortality.
5727: */
5728: /* If, at the beginning of the maximization mostly, the
5729: cumulative probability or probability to be dead is
5730: constant (ie = 1) over time d, the difference is equal to
5731: 0. out[s1][3] = savm[s1][3]: probability, being at state
5732: s1 at precedent wave, to be dead a month before current
5733: wave is equal to probability, being at state s1 at
5734: precedent wave, to be dead at mont of the current
5735: wave. Then the observed probability (that this person died)
5736: is null according to current estimated parameter. In fact,
5737: it should be very low but not zero otherwise the log go to
5738: infinity.
5739: */
1.183 brouard 5740: /* #ifdef INFINITYORIGINAL */
5741: /* lli=log(out[s1][s2] - savm[s1][s2]); */
5742: /* #else */
5743: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
5744: /* lli=log(mytinydouble); */
5745: /* else */
5746: /* lli=log(out[s1][s2] - savm[s1][s2]); */
5747: /* #endif */
1.226 brouard 5748: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 5749:
1.226 brouard 5750: } else if ( s2==-1 ) { /* alive */
5751: for (j=1,survp=0. ; j<=nlstate; j++)
5752: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
5753: /*survp += out[s1][j]; */
5754: lli= log(survp);
5755: }
1.336 brouard 5756: /* else if (s2==-4) { */
5757: /* for (j=3,survp=0. ; j<=nlstate; j++) */
5758: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
5759: /* lli= log(survp); */
5760: /* } */
5761: /* else if (s2==-5) { */
5762: /* for (j=1,survp=0. ; j<=2; j++) */
5763: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
5764: /* lli= log(survp); */
5765: /* } */
1.226 brouard 5766: else{
5767: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
5768: /* lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2]));*/ /* linear interpolation */
5769: }
5770: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
5771: /*if(lli ==000.0)*/
1.340 brouard 5772: /* printf("num[i], i=%d, bbh= %f lli=%f savm=%f out=%f %d\n",bbh,lli,savm[s1][s2], out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]],i); */
1.226 brouard 5773: ipmx +=1;
5774: sw += weight[i];
5775: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5776: /* if (lli < log(mytinydouble)){ */
5777: /* printf("Close to inf lli = %.10lf < %.10lf i= %d mi= %d, s[%d][i]=%d s1=%d s2=%d\n", lli,log(mytinydouble), i, mi,mw[mi][i], s[mw[mi][i]][i], s1,s2); */
5778: /* fprintf(ficlog,"Close to inf lli = %.10lf i= %d mi= %d, s[mw[mi][i]][i]=%d\n", lli, i, mi,s[mw[mi][i]][i]); */
5779: /* } */
5780: } /* end of wave */
5781: } /* end of individual */
5782: } else if(mle==2){
5783: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 5784: ioffset=2+nagesqr ;
5785: for (k=1; k<=ncovf;k++)
5786: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 5787: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 5788: for(k=1; k <= ncovv ; k++){
1.341 brouard 5789: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.319 brouard 5790: }
1.226 brouard 5791: for (ii=1;ii<=nlstate+ndeath;ii++)
5792: for (j=1;j<=nlstate+ndeath;j++){
5793: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5794: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5795: }
5796: for(d=0; d<=dh[mi][i]; d++){
5797: newm=savm;
5798: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5799: cov[2]=agexact;
5800: if(nagesqr==1)
5801: cov[3]= agexact*agexact;
5802: for (kk=1; kk<=cptcovage;kk++) {
5803: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
5804: }
5805: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5806: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5807: savm=oldm;
5808: oldm=newm;
5809: } /* end mult */
5810:
5811: s1=s[mw[mi][i]][i];
5812: s2=s[mw[mi+1][i]][i];
5813: bbh=(double)bh[mi][i]/(double)stepm;
5814: lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2])); /* linear interpolation */
5815: ipmx +=1;
5816: sw += weight[i];
5817: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5818: } /* end of wave */
5819: } /* end of individual */
5820: } else if(mle==3){ /* exponential inter-extrapolation */
5821: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5822: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5823: for(mi=1; mi<= wav[i]-1; mi++){
5824: for (ii=1;ii<=nlstate+ndeath;ii++)
5825: for (j=1;j<=nlstate+ndeath;j++){
5826: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5827: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5828: }
5829: for(d=0; d<dh[mi][i]; d++){
5830: newm=savm;
5831: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5832: cov[2]=agexact;
5833: if(nagesqr==1)
5834: cov[3]= agexact*agexact;
5835: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 5836: if(!FixedV[Tvar[Tage[kk]]])
5837: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
5838: else
1.341 brouard 5839: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.226 brouard 5840: }
5841: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5842: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5843: savm=oldm;
5844: oldm=newm;
5845: } /* end mult */
5846:
5847: s1=s[mw[mi][i]][i];
5848: s2=s[mw[mi+1][i]][i];
5849: bbh=(double)bh[mi][i]/(double)stepm;
5850: lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */
5851: ipmx +=1;
5852: sw += weight[i];
5853: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5854: } /* end of wave */
5855: } /* end of individual */
5856: }else if (mle==4){ /* ml=4 no inter-extrapolation */
5857: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5858: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5859: for(mi=1; mi<= wav[i]-1; mi++){
5860: for (ii=1;ii<=nlstate+ndeath;ii++)
5861: for (j=1;j<=nlstate+ndeath;j++){
5862: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5863: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5864: }
5865: for(d=0; d<dh[mi][i]; d++){
5866: newm=savm;
5867: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5868: cov[2]=agexact;
5869: if(nagesqr==1)
5870: cov[3]= agexact*agexact;
5871: for (kk=1; kk<=cptcovage;kk++) {
5872: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
5873: }
1.126 brouard 5874:
1.226 brouard 5875: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5876: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5877: savm=oldm;
5878: oldm=newm;
5879: } /* end mult */
5880:
5881: s1=s[mw[mi][i]][i];
5882: s2=s[mw[mi+1][i]][i];
5883: if( s2 > nlstate){
5884: lli=log(out[s1][s2] - savm[s1][s2]);
5885: } else if ( s2==-1 ) { /* alive */
5886: for (j=1,survp=0. ; j<=nlstate; j++)
5887: survp += out[s1][j];
5888: lli= log(survp);
5889: }else{
5890: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
5891: }
5892: ipmx +=1;
5893: sw += weight[i];
5894: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 5895: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.226 brouard 5896: } /* end of wave */
5897: } /* end of individual */
5898: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
5899: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5900: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5901: for(mi=1; mi<= wav[i]-1; mi++){
5902: for (ii=1;ii<=nlstate+ndeath;ii++)
5903: for (j=1;j<=nlstate+ndeath;j++){
5904: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5905: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5906: }
5907: for(d=0; d<dh[mi][i]; d++){
5908: newm=savm;
5909: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5910: cov[2]=agexact;
5911: if(nagesqr==1)
5912: cov[3]= agexact*agexact;
5913: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 5914: if(!FixedV[Tvar[Tage[kk]]])
5915: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
5916: else
1.341 brouard 5917: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.226 brouard 5918: }
1.126 brouard 5919:
1.226 brouard 5920: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5921: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5922: savm=oldm;
5923: oldm=newm;
5924: } /* end mult */
5925:
5926: s1=s[mw[mi][i]][i];
5927: s2=s[mw[mi+1][i]][i];
5928: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
5929: ipmx +=1;
5930: sw += weight[i];
5931: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5932: /*printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]);*/
5933: } /* end of wave */
5934: } /* end of individual */
5935: } /* End of if */
5936: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
5937: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
5938: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
5939: return -l;
1.126 brouard 5940: }
5941:
5942: /*************** log-likelihood *************/
5943: double funcone( double *x)
5944: {
1.228 brouard 5945: /* Same as func but slower because of a lot of printf and if */
1.359 brouard 5946: int i, ii, j, k, mi, d, kv=0, kf=0;
1.228 brouard 5947: int ioffset=0;
1.339 brouard 5948: int ipos=0,iposold=0,ncovv=0;
5949:
1.340 brouard 5950: double cotvarv, cotvarvold;
1.131 brouard 5951: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 5952: double **out;
5953: double lli; /* Individual log likelihood */
5954: double llt;
5955: int s1, s2;
1.228 brouard 5956: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
5957:
1.126 brouard 5958: double bbh, survp;
1.187 brouard 5959: double agexact;
1.214 brouard 5960: double agebegin, ageend;
1.126 brouard 5961: /*extern weight */
5962: /* We are differentiating ll according to initial status */
5963: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
5964: /*for(i=1;i<imx;i++)
5965: printf(" %d\n",s[4][i]);
5966: */
5967: cov[1]=1.;
5968:
5969: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 5970: ioffset=0;
5971: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 5972: /* Computes the values of the ncovmodel covariates of the model
5973: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
5974: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
5975: to be observed in j being in i according to the model.
5976: */
1.243 brouard 5977: /* ioffset=2+nagesqr+cptcovage; */
5978: ioffset=2+nagesqr;
1.232 brouard 5979: /* Fixed */
1.224 brouard 5980: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 5981: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 5982: for (kf=1; kf<=ncovf;kf++){ /* V2 + V3 + V4 Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 brouard 5983: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
5984: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
5985: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 5986: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
1.232 brouard 5987: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
5988: /* cov[2+6]=covar[Tvar[6]][i]; */
5989: /* cov[2+6]=covar[2][i]; V2 */
5990: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
5991: /* cov[2+7]=covar[Tvar[7]][i]; */
5992: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
5993: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
5994: /* cov[2+9]=covar[Tvar[9]][i]; */
5995: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 5996: }
1.336 brouard 5997: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
5998: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
5999: has been calculated etc */
6000: /* For an individual i, wav[i] gives the number of effective waves */
6001: /* We compute the contribution to Likelihood of each effective transition
6002: mw[mi][i] is real wave of the mi th effectve wave */
6003: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
6004: s2=s[mw[mi+1][i]][i];
1.341 brouard 6005: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 6006: */
6007: /* This part may be useless now because everythin should be in covar */
1.232 brouard 6008: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
6009: /* cov[++ioffset]=coqvar[TvarFQ[k]][i];/\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V2 and V1*V2 is fixed (k=6 and 7?)*\/ */
6010: /* } */
1.231 brouard 6011: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
6012: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
6013: /* } */
1.225 brouard 6014:
1.233 brouard 6015:
6016: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 6017: /* Wave varying (but not age varying) *//* V1+V3+age*V1+age*V3+V1*V3 with V4 tv and V5 tvq k= 1 to 5 and extra at V(5+1)=6 for V1*V3 */
6018: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
6019: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
6020: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
6021: /* } */
6022:
6023: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
6024: /* model V1+V3+age*V1+age*V3+V1*V3 */
6025: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
6026: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
6027: /* We need the position of the time varying or product in the model */
6028: /* TvarVVind={2,5,5}, for V3 at position 2 and then the product V1*V3 is decomposed into V1 and V3 but at same position 5 */
6029: /* TvarVV gives the variable name */
1.340 brouard 6030: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
6031: * k= 1 2 3 4 5 6 7 8 9
6032: * varying 1 2 3 4 5
6033: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 6034: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 6035: * TvarVVind 2 3 7 7 8 8 9 9
6036: * TvarFind[k] 1 0 0 0 0 0 0 0 0
6037: */
1.345 brouard 6038: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 6039: * V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[(v6*V2)6]=9
1.345 brouard 6040: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 6041: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6042: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
6043: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
6044: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6045: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6046: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6047: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6048: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6049: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6050: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6051: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6052: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6053: * kmodel 1 2 3 4 5 6 7 8 9 10 11
6054: * 12 13 14 15 16
6055: * 17 18 19 20 21
6056: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
6057: * 2 3 4 6 7
6058: * 9 11 12 13 14
6059: * cptcovage=5+5 total of covariates with age
6060: * Tage[cptcovage] age*V2=12 13 14 15 16
6061: *1 17 18 19 20 21 gives the position in model of covariates associated with age
6062: *3 Tage[cptcovage] age*V3*V2=6
6063: *3 age*V2=12 13 14 15 16
6064: *3 age*V6*V3=18 19 20 21
6065: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
6066: * Tvar[17]age*V6*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6067: * 2 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6068: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
6069: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6070: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
6071: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
6072: * 3 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6073: * Tvar= {2, 3, 4, 6, 7,
6074: * 9, 10, 11, 12, 13, 14,
6075: * Tvar[12]=2, 3, 4, 6, 7,
6076: * Tvar[17]=9, 11, 12, 13, 14}
6077: * Typevar[1]@21 = {0, 0, 0, 0, 0,
6078: * 2, 2, 2, 2, 2, 2,
6079: * 3 3, 2, 2, 2, 2, 2,
6080: * 1, 1, 1, 1, 1,
6081: * 3, 3, 3, 3, 3}
6082: * 3 2, 3, 3, 3, 3}
6083: * p Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6} Id of the prod at position k in the model
6084: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
6085: * 3 Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6}
6086: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
6087: * cptcovprod=11 (6+5)
6088: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
6089: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
6090: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
6091: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
6092: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
6093: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
6094: * cptcovdageprod=5 for gnuplot printing
6095: * cptcovprodvage=6
6096: * ncova=15 1 2 3 4 5
6097: * 6 7 8 9 10 11 12 13 14 15
6098: * TvarA 2 3 4 6 7
6099: * 6 2 6 7 7 3 6 4 7 4
6100: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 6101: * ncovf 1 2 3
1.349 brouard 6102: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6103: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
6104: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
6105: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
6106: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6107: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
6108: * 3 1 2 3 4 5 6 7 8 9 10 11 12
6109: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
6110: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
6111: * 3 cptcovprodvage=6
6112: * 3 ncovta=15 +age*V3*V2+age*V2+agev3+ageV4 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6113: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
6114: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.354 brouard 6115: *?TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
1.349 brouard 6116: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
6117: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6118: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
6119: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
6120: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
6121: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
6122: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
6123: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 6124: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 6125: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
6126: * 2, 3, 4, 6, 7,
6127: * 6, 8, 9, 10, 11}
1.345 brouard 6128: * TvarFind[itv] 0 0 0
6129: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
1.354 brouard 6130: *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0
1.345 brouard 6131: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
6132: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
6133: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 6134: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 6135: */
6136:
1.349 brouard 6137: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 Time varying covariates (single and extended product but no age) including individual from products, product is computed dynamically */
6138: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, or fixed covariate of a varying product after exploding product Vn*Vm into Vn and then Vm */
1.340 brouard 6139: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 6140: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6141: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
1.354 brouard 6142: /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.345 brouard 6143: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.354 brouard 6144: /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 6145: }else{ /* fixed covariate */
1.345 brouard 6146: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
1.354 brouard 6147: /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.349 brouard 6148: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.354 brouard 6149: /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 6150: }
1.339 brouard 6151: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 6152: cotvarvold=cotvarv;
6153: }else{ /* A second product */
6154: cotvarv=cotvarv*cotvarvold;
1.339 brouard 6155: }
6156: iposold=ipos;
1.340 brouard 6157: cov[ioffset+ipos]=cotvarv;
1.354 brouard 6158: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
1.339 brouard 6159: /* For products */
6160: }
6161: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
6162: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
6163: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
6164: /* /\* 1 2 3 4 5 *\/ */
6165: /* /\*itv 1 *\/ */
6166: /* /\* TvarVInd[1]= 2 *\/ */
6167: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
6168: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
6169: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
6170: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
6171: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
6172: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
6173: /* /\* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][itv][i]=%f\n", i, mi, itv, TvarVDind[itv],cotvar[mw[mi][i]][itv][i]); *\/ */
6174: /* } */
1.232 brouard 6175: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 6176: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
6177: /* /\* printf(" i=%d,mi=%d,iqtv=%d,TmodelInvQind[iqtv]=%d,cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]=%f\n", i, mi, iqtv, TmodelInvQind[iqtv],cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]); *\/ */
6178: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 6179: /* } */
1.126 brouard 6180: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 6181: for (j=1;j<=nlstate+ndeath;j++){
6182: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
6183: savm[ii][j]=(ii==j ? 1.0 : 0.0);
6184: }
1.214 brouard 6185:
6186: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
6187: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
6188: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 6189: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 6190: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
6191: and mw[mi+1][i]. dh depends on stepm.*/
6192: newm=savm;
1.247 brouard 6193: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 6194: cov[2]=agexact;
6195: if(nagesqr==1)
6196: cov[3]= agexact*agexact;
1.349 brouard 6197: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
6198: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
6199: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6200: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6201: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
6202: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6203: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
6204: }else{ /* fixed covariate */
6205: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
6206: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6207: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
6208: }
6209: if(ipos!=iposold){ /* Not a product or first of a product */
6210: cotvarvold=cotvarv;
6211: }else{ /* A second product */
6212: /* printf("DEBUG * \n"); */
6213: cotvarv=cotvarv*cotvarvold;
6214: }
6215: iposold=ipos;
6216: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
6217: cov[ioffset+ipos]=cotvarv*agexact;
6218: /* For products */
1.242 brouard 6219: }
1.349 brouard 6220:
1.242 brouard 6221: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
6222: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
6223: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
6224: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
6225: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
6226: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
6227: savm=oldm;
6228: oldm=newm;
1.126 brouard 6229: } /* end mult */
1.336 brouard 6230: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
6231: /* But now since version 0.9 we anticipate for bias at large stepm.
6232: * If stepm is larger than one month (smallest stepm) and if the exact delay
6233: * (in months) between two waves is not a multiple of stepm, we rounded to
6234: * the nearest (and in case of equal distance, to the lowest) interval but now
6235: * we keep into memory the bias bh[mi][i] and also the previous matrix product
6236: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
6237: * probability in order to take into account the bias as a fraction of the way
6238: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
6239: * -stepm/2 to stepm/2 .
6240: * For stepm=1 the results are the same as for previous versions of Imach.
6241: * For stepm > 1 the results are less biased than in previous versions.
6242: */
1.126 brouard 6243: s1=s[mw[mi][i]][i];
6244: s2=s[mw[mi+1][i]][i];
1.217 brouard 6245: /* if(s2==-1){ */
1.268 brouard 6246: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 6247: /* /\* exit(1); *\/ */
6248: /* } */
1.126 brouard 6249: bbh=(double)bh[mi][i]/(double)stepm;
6250: /* bias is positive if real duration
6251: * is higher than the multiple of stepm and negative otherwise.
6252: */
6253: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 6254: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 6255: } else if ( s2==-1 ) { /* alive */
1.242 brouard 6256: for (j=1,survp=0. ; j<=nlstate; j++)
6257: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
6258: lli= log(survp);
1.126 brouard 6259: }else if (mle==1){
1.242 brouard 6260: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 6261: } else if(mle==2){
1.242 brouard 6262: lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* linear interpolation */
1.126 brouard 6263: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 6264: lli= (savm[s1][s2]>(double)1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */
1.126 brouard 6265: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 6266: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 6267: } else{ /* mle=0 back to 1 */
1.242 brouard 6268: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
6269: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 6270: } /* End of if */
6271: ipmx +=1;
6272: sw += weight[i];
6273: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 6274: /* Printing covariates values for each contribution for checking */
1.343 brouard 6275: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.126 brouard 6276: if(globpr){
1.246 brouard 6277: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 6278: %11.6f %11.6f %11.6f ", \
1.242 brouard 6279: num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw,
1.268 brouard 6280: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 6281: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
6282: /* %11.6f %11.6f %11.6f ", \ */
6283: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
6284: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 6285: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
6286: llt +=ll[k]*gipmx/gsw;
6287: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 6288: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 6289: }
1.343 brouard 6290: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 6291: /* printf(" %10.6f\n", -llt); */
1.342 brouard 6292: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 6293: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
6294: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
6295: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
6296: }
6297: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
6298: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6299: if(ipos!=iposold){ /* Not a product or first of a product */
6300: fprintf(ficresilk," %g",cov[ioffset+ipos]);
6301: /* printf(" %g",cov[ioffset+ipos]); */
6302: }else{
6303: fprintf(ficresilk,"*");
6304: /* printf("*"); */
1.342 brouard 6305: }
1.343 brouard 6306: iposold=ipos;
6307: }
1.349 brouard 6308: /* for (kk=1; kk<=cptcovage;kk++) { */
6309: /* if(!FixedV[Tvar[Tage[kk]]]){ */
6310: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
6311: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
6312: /* }else{ */
6313: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
6314: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
6315: /* } */
6316: /* } */
6317: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
6318: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
6319: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6320: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6321: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
6322: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6323: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
6324: }else{ /* fixed covariate */
6325: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
6326: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6327: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
6328: }
6329: if(ipos!=iposold){ /* Not a product or first of a product */
6330: cotvarvold=cotvarv;
6331: }else{ /* A second product */
6332: /* printf("DEBUG * \n"); */
6333: cotvarv=cotvarv*cotvarvold;
1.342 brouard 6334: }
1.349 brouard 6335: cotvarv=cotvarv*agexact;
6336: fprintf(ficresilk," %g*age",cotvarv);
6337: iposold=ipos;
6338: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
6339: cov[ioffset+ipos]=cotvarv;
6340: /* For products */
1.343 brouard 6341: }
6342: /* printf("\n"); */
1.342 brouard 6343: /* } /\* End debugILK *\/ */
6344: fprintf(ficresilk,"\n");
6345: } /* End if globpr */
1.335 brouard 6346: } /* end of wave */
6347: } /* end of individual */
6348: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 6349: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 6350: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
6351: if(globpr==0){ /* First time we count the contributions and weights */
6352: gipmx=ipmx;
6353: gsw=sw;
6354: }
1.343 brouard 6355: return -l;
1.126 brouard 6356: }
6357:
6358:
6359: /*************** function likelione ***********/
1.292 brouard 6360: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 6361: {
6362: /* This routine should help understanding what is done with
6363: the selection of individuals/waves and
6364: to check the exact contribution to the likelihood.
6365: Plotting could be done.
1.342 brouard 6366: */
6367: void pstamp(FILE *ficres);
1.343 brouard 6368: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 6369:
6370: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 6371: strcpy(fileresilk,"ILK_");
1.202 brouard 6372: strcat(fileresilk,fileresu);
1.126 brouard 6373: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
6374: printf("Problem with resultfile: %s\n", fileresilk);
6375: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
6376: }
1.342 brouard 6377: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 6378: fprintf(ficresilk, "#individual(line's_record) count ageb ageend s1 s2 wave# effective_wave# number_of_matrices_product pij weight weight/gpw -2ln(pij)*weight 0pij_x 0pij_(x-stepm) cumulating_loglikeli_by_health_state(reweighted=-2ll*weightXnumber_of_contribs/sum_of_weights) and_total\n");
6379: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 6380: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
6381: for(k=1; k<=nlstate; k++)
6382: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 6383: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
6384:
6385: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
6386: for(kf=1;kf <= ncovf; kf++){
6387: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
6388: /* printf("V%d",Tvar[TvarFind[kf]]); */
6389: }
6390: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 6391: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 6392: if(ipos!=iposold){ /* Not a product or first of a product */
6393: /* printf(" %d",ipos); */
6394: fprintf(ficresilk," V%d",TvarVV[ncovv]);
6395: }else{
6396: /* printf("*"); */
6397: fprintf(ficresilk,"*");
1.343 brouard 6398: }
1.342 brouard 6399: iposold=ipos;
6400: }
6401: for (kk=1; kk<=cptcovage;kk++) {
6402: if(!FixedV[Tvar[Tage[kk]]]){
6403: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
6404: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
6405: }else{
6406: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
6407: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
6408: }
6409: }
6410: /* } /\* End if debugILK *\/ */
6411: /* printf("\n"); */
6412: fprintf(ficresilk,"\n");
6413: } /* End glogpri */
1.126 brouard 6414:
1.292 brouard 6415: *fretone=(*func)(p);
1.126 brouard 6416: if(*globpri !=0){
6417: fclose(ficresilk);
1.205 brouard 6418: if (mle ==0)
6419: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
6420: else if(mle >=1)
6421: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
6422: fprintf(fichtm," You should at least run with mle >= 1 to get starting values corresponding to the optimized parameters in order to visualize the real contribution of each individual/wave: <a href=\"%s\">%s</a><br>\n",subdirf(fileresilk),subdirf(fileresilk));
1.274 brouard 6423: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 6424:
1.207 brouard 6425: fprintf(fichtm,"<br>- The function drawn is -2Log(L) in Log scale: by state of origin <a href=\"%s-ori.png\">%s-ori.png</a><br> \
1.343 brouard 6426: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 6427: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 6428: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
6429:
6430: for (k=1; k<= nlstate ; k++) {
6431: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Dot's sizes are related to corresponding weight: <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br>\n \
6432: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
6433: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 6434: kvar=Tvar[TvarFind[kf]]; /* variable */
6435: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): ",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]]);
6436: fprintf(fichtm,"<a href=\"%s-p%dj-%d.png\">%s-p%dj-%d.png</a><br>",subdirf2(optionfilefiname,"ILK_"),k,kvar,subdirf2(optionfilefiname,"ILK_"),k,kvar);
6437: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 6438: }
6439: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
6440: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
6441: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
6442: /* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
6443: if(ipos!=iposold){ /* Not a product or first of a product */
6444: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
6445: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
6446: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
6447: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored time varying dummy covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \
6448: <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar);
6449: } /* End only for dummies time varying (single?) */
6450: }else{ /* Useless product */
6451: /* printf("*"); */
6452: /* fprintf(ficresilk,"*"); */
6453: }
6454: iposold=ipos;
6455: } /* For each time varying covariate */
6456: } /* End loop on states */
6457:
6458: /* if(debugILK){ */
6459: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
6460: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
6461: /* for (k=1; k<= nlstate ; k++) { */
6462: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
6463: /* <img src=\"%s-p%dj-%d.png\">",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]); */
6464: /* } */
6465: /* } */
6466: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
6467: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
6468: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
6469: /* /\* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); *\/ */
6470: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
6471: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
6472: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
6473: /* if(Dummy[ipos]==0 && Typevar[ipos]==0){ /\* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) *\/ */
6474: /* for (k=1; k<= nlstate ; k++) { */
6475: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
6476: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
6477: /* } /\* End state *\/ */
6478: /* } /\* End only for dummies time varying (single?) *\/ */
6479: /* }else{ /\* Useless product *\/ */
6480: /* /\* printf("*"); *\/ */
6481: /* /\* fprintf(ficresilk,"*"); *\/ */
6482: /* } */
6483: /* iposold=ipos; */
6484: /* } /\* For each time varying covariate *\/ */
6485: /* }/\* End debugILK *\/ */
1.207 brouard 6486: fflush(fichtm);
1.343 brouard 6487: }/* End globpri */
1.126 brouard 6488: return;
6489: }
6490:
6491:
6492: /*********** Maximum Likelihood Estimation ***************/
6493:
6494: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
6495: {
1.359 brouard 6496: int i,j, jkk=0, iter=0;
1.126 brouard 6497: double **xi;
1.359 brouard 6498: /*double fret;*/
6499: /*double fretone;*/ /* Only one call to likelihood */
1.126 brouard 6500: /* char filerespow[FILENAMELENGTH];*/
1.354 brouard 6501:
1.359 brouard 6502: /*double * p1;*/ /* Shifted parameters from 0 instead of 1 */
1.162 brouard 6503: #ifdef NLOPT
6504: int creturn;
6505: nlopt_opt opt;
6506: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
6507: double *lb;
6508: double minf; /* the minimum objective value, upon return */
1.354 brouard 6509:
1.162 brouard 6510: myfunc_data dinst, *d = &dinst;
6511: #endif
6512:
6513:
1.126 brouard 6514: xi=matrix(1,npar,1,npar);
1.357 brouard 6515: for (i=1;i<=npar;i++) /* Starting with canonical directions j=1,n xi[i=1,n][j] */
1.126 brouard 6516: for (j=1;j<=npar;j++)
6517: xi[i][j]=(i==j ? 1.0 : 0.0);
1.359 brouard 6518: printf("Powell-prax\n"); fprintf(ficlog,"Powell-prax\n");
1.201 brouard 6519: strcpy(filerespow,"POW_");
1.126 brouard 6520: strcat(filerespow,fileres);
6521: if((ficrespow=fopen(filerespow,"w"))==NULL) {
6522: printf("Problem with resultfile: %s\n", filerespow);
6523: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
6524: }
6525: fprintf(ficrespow,"# Powell\n# iter -2*LL");
6526: for (i=1;i<=nlstate;i++)
6527: for(j=1;j<=nlstate+ndeath;j++)
6528: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
6529: fprintf(ficrespow,"\n");
1.162 brouard 6530: #ifdef POWELL
1.319 brouard 6531: #ifdef LINMINORIGINAL
6532: #else /* LINMINORIGINAL */
6533:
6534: flatdir=ivector(1,npar);
6535: for (j=1;j<=npar;j++) flatdir[j]=0;
6536: #endif /*LINMINORIGINAL */
6537:
6538: #ifdef FLATSUP
6539: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
6540: /* reorganizing p by suppressing flat directions */
6541: for(i=1, jk=1; i <=nlstate; i++){
6542: for(k=1; k <=(nlstate+ndeath); k++){
6543: if (k != i) {
6544: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
6545: if(flatdir[jk]==1){
6546: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
6547: }
6548: for(j=1; j <=ncovmodel; j++){
6549: printf("%12.7f ",p[jk]);
6550: jk++;
6551: }
6552: printf("\n");
6553: }
6554: }
6555: }
6556: /* skipping */
6557: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
6558: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
6559: for(k=1; k <=(nlstate+ndeath); k++){
6560: if (k != i) {
6561: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
6562: if(flatdir[jk]==1){
6563: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
6564: for(j=1; j <=ncovmodel; jk++,j++){
6565: printf(" p[%d]=%12.7f",jk, p[jk]);
6566: /*q[jjk]=p[jk];*/
6567: }
6568: }else{
6569: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
6570: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
6571: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
6572: /*q[jjk]=p[jk];*/
6573: }
6574: }
6575: printf("\n");
6576: }
6577: fflush(stdout);
6578: }
6579: }
6580: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
6581: #else /* FLATSUP */
1.359 brouard 6582: /* powell(p,xi,npar,ftol,&iter,&fret,func);*/
6583: /* praxis ( t0, h0, n, prin, x, beale_f ); */
6584: int prin=1;
6585: double h0=0.25;
6586: double macheps;
6587: double fmin;
6588: macheps=pow(16.0,-13.0);
6589: /* #include "praxis.h" */
6590: /* Be careful that praxis start at x[0] and powell start at p[1] */
6591: /* praxis ( ftol, h0, npar, prin, p, func ); */
6592: /* p1= (p+1); */ /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
6593: printf("Praxis Gegenfurtner \n");
6594: fprintf(ficlog, "Praxis Gegenfurtner\n");fflush(ficlog);
6595: /* praxis ( ftol, h0, npar, prin, p1, func ); */
6596: /* fmin = praxis(1.e-5,macheps, h, n, prin, x, func); */
6597: fmin = praxis(ftol,macheps, h0, npar, prin, p, func);
6598: printf("End Praxis\n");
1.319 brouard 6599: #endif /* FLATSUP */
6600:
6601: #ifdef LINMINORIGINAL
6602: #else
6603: free_ivector(flatdir,1,npar);
6604: #endif /* LINMINORIGINAL*/
6605: #endif /* POWELL */
1.126 brouard 6606:
1.162 brouard 6607: #ifdef NLOPT
6608: #ifdef NEWUOA
6609: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
6610: #else
6611: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
6612: #endif
6613: lb=vector(0,npar-1);
6614: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
6615: nlopt_set_lower_bounds(opt, lb);
6616: nlopt_set_initial_step1(opt, 0.1);
6617:
6618: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
6619: d->function = func;
6620: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
6621: nlopt_set_min_objective(opt, myfunc, d);
6622: nlopt_set_xtol_rel(opt, ftol);
6623: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
6624: printf("nlopt failed! %d\n",creturn);
6625: }
6626: else {
6627: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
6628: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
6629: iter=1; /* not equal */
6630: }
6631: nlopt_destroy(opt);
6632: #endif
1.319 brouard 6633: #ifdef FLATSUP
6634: /* npared = npar -flatd/ncovmodel; */
6635: /* xired= matrix(1,npared,1,npared); */
6636: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
6637: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
6638: /* free_matrix(xire,1,npared,1,npared); */
6639: #else /* FLATSUP */
6640: #endif /* FLATSUP */
1.126 brouard 6641: free_matrix(xi,1,npar,1,npar);
6642: fclose(ficrespow);
1.203 brouard 6643: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
6644: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 6645: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 6646:
6647: }
6648:
6649: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 6650: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 6651: {
6652: double **a,**y,*x,pd;
1.203 brouard 6653: /* double **hess; */
1.164 brouard 6654: int i, j;
1.126 brouard 6655: int *indx;
6656:
6657: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 6658: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 6659: void lubksb(double **a, int npar, int *indx, double b[]) ;
6660: void ludcmp(double **a, int npar, int *indx, double *d) ;
6661: double gompertz(double p[]);
1.203 brouard 6662: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 6663:
6664: printf("\nCalculation of the hessian matrix. Wait...\n");
6665: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
6666: for (i=1;i<=npar;i++){
1.203 brouard 6667: printf("%d-",i);fflush(stdout);
6668: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 6669:
6670: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
6671:
6672: /* printf(" %f ",p[i]);
6673: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
6674: }
6675:
6676: for (i=1;i<=npar;i++) {
6677: for (j=1;j<=npar;j++) {
6678: if (j>i) {
1.203 brouard 6679: printf(".%d-%d",i,j);fflush(stdout);
6680: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
6681: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 6682:
6683: hess[j][i]=hess[i][j];
6684: /*printf(" %lf ",hess[i][j]);*/
6685: }
6686: }
6687: }
6688: printf("\n");
6689: fprintf(ficlog,"\n");
6690:
6691: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
6692: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
6693:
6694: a=matrix(1,npar,1,npar);
6695: y=matrix(1,npar,1,npar);
6696: x=vector(1,npar);
6697: indx=ivector(1,npar);
6698: for (i=1;i<=npar;i++)
6699: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
6700: ludcmp(a,npar,indx,&pd);
6701:
6702: for (j=1;j<=npar;j++) {
6703: for (i=1;i<=npar;i++) x[i]=0;
6704: x[j]=1;
6705: lubksb(a,npar,indx,x);
6706: for (i=1;i<=npar;i++){
6707: matcov[i][j]=x[i];
6708: }
6709: }
6710:
6711: printf("\n#Hessian matrix#\n");
6712: fprintf(ficlog,"\n#Hessian matrix#\n");
6713: for (i=1;i<=npar;i++) {
6714: for (j=1;j<=npar;j++) {
1.203 brouard 6715: printf("%.6e ",hess[i][j]);
6716: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 6717: }
6718: printf("\n");
6719: fprintf(ficlog,"\n");
6720: }
6721:
1.203 brouard 6722: /* printf("\n#Covariance matrix#\n"); */
6723: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
6724: /* for (i=1;i<=npar;i++) { */
6725: /* for (j=1;j<=npar;j++) { */
6726: /* printf("%.6e ",matcov[i][j]); */
6727: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
6728: /* } */
6729: /* printf("\n"); */
6730: /* fprintf(ficlog,"\n"); */
6731: /* } */
6732:
1.126 brouard 6733: /* Recompute Inverse */
1.203 brouard 6734: /* for (i=1;i<=npar;i++) */
6735: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
6736: /* ludcmp(a,npar,indx,&pd); */
6737:
6738: /* printf("\n#Hessian matrix recomputed#\n"); */
6739:
6740: /* for (j=1;j<=npar;j++) { */
6741: /* for (i=1;i<=npar;i++) x[i]=0; */
6742: /* x[j]=1; */
6743: /* lubksb(a,npar,indx,x); */
6744: /* for (i=1;i<=npar;i++){ */
6745: /* y[i][j]=x[i]; */
6746: /* printf("%.3e ",y[i][j]); */
6747: /* fprintf(ficlog,"%.3e ",y[i][j]); */
6748: /* } */
6749: /* printf("\n"); */
6750: /* fprintf(ficlog,"\n"); */
6751: /* } */
6752:
6753: /* Verifying the inverse matrix */
6754: #ifdef DEBUGHESS
6755: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 6756:
1.203 brouard 6757: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
6758: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 6759:
6760: for (j=1;j<=npar;j++) {
6761: for (i=1;i<=npar;i++){
1.203 brouard 6762: printf("%.2f ",y[i][j]);
6763: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 6764: }
6765: printf("\n");
6766: fprintf(ficlog,"\n");
6767: }
1.203 brouard 6768: #endif
1.126 brouard 6769:
6770: free_matrix(a,1,npar,1,npar);
6771: free_matrix(y,1,npar,1,npar);
6772: free_vector(x,1,npar);
6773: free_ivector(indx,1,npar);
1.203 brouard 6774: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 6775:
6776:
6777: }
6778:
6779: /*************** hessian matrix ****************/
6780: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 6781: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 6782: int i;
6783: int l=1, lmax=20;
1.203 brouard 6784: double k1,k2, res, fx;
1.132 brouard 6785: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 6786: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
6787: int k=0,kmax=10;
6788: double l1;
6789:
6790: fx=func(x);
6791: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 6792: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 6793: l1=pow(10,l);
6794: delts=delt;
6795: for(k=1 ; k <kmax; k=k+1){
6796: delt = delta*(l1*k);
6797: p2[theta]=x[theta] +delt;
1.145 brouard 6798: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 6799: p2[theta]=x[theta]-delt;
6800: k2=func(p2)-fx;
6801: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 6802: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 6803:
1.203 brouard 6804: #ifdef DEBUGHESSII
1.126 brouard 6805: printf("%d %d k1=%.12e k2=%.12e xk1=%.12e xk2=%.12e delt=%.12e res=%.12e l=%d k=%d,fx=%.12e\n",theta,theta,k1,k2,x[theta]+delt,x[theta]-delt,delt,res, l, k,fx);
6806: fprintf(ficlog,"%d %d k1=%.12e k2=%.12e xk1=%.12e xk2=%.12e delt=%.12e res=%.12e l=%d k=%d,fx=%.12e\n",theta,theta,k1,k2,x[theta]+delt,x[theta]-delt,delt,res, l, k,fx);
6807: #endif
6808: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
6809: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
6810: k=kmax;
6811: }
6812: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 6813: k=kmax; l=lmax*10;
1.126 brouard 6814: }
6815: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
6816: delts=delt;
6817: }
1.203 brouard 6818: } /* End loop k */
1.126 brouard 6819: }
6820: delti[theta]=delts;
6821: return res;
6822:
6823: }
6824:
1.203 brouard 6825: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 6826: {
6827: int i;
1.164 brouard 6828: int l=1, lmax=20;
1.126 brouard 6829: double k1,k2,k3,k4,res,fx;
1.132 brouard 6830: double p2[MAXPARM+1];
1.203 brouard 6831: int k, kmax=1;
6832: double v1, v2, cv12, lc1, lc2;
1.208 brouard 6833:
6834: int firstime=0;
1.203 brouard 6835:
1.126 brouard 6836: fx=func(x);
1.203 brouard 6837: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 6838: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 6839: p2[thetai]=x[thetai]+delti[thetai]*k;
6840: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 6841: k1=func(p2)-fx;
6842:
1.203 brouard 6843: p2[thetai]=x[thetai]+delti[thetai]*k;
6844: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 6845: k2=func(p2)-fx;
6846:
1.203 brouard 6847: p2[thetai]=x[thetai]-delti[thetai]*k;
6848: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 6849: k3=func(p2)-fx;
6850:
1.203 brouard 6851: p2[thetai]=x[thetai]-delti[thetai]*k;
6852: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 6853: k4=func(p2)-fx;
1.203 brouard 6854: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
6855: if(k1*k2*k3*k4 <0.){
1.208 brouard 6856: firstime=1;
1.203 brouard 6857: kmax=kmax+10;
1.208 brouard 6858: }
6859: if(kmax >=10 || firstime ==1){
1.354 brouard 6860: /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */
1.246 brouard 6861: printf("Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol);
6862: fprintf(ficlog,"Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol);
1.203 brouard 6863: printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti*k=%.12e deltj*k=%.12e, xi-de*k=%.12e xj-de*k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
6864: fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti*k=%.12e deltj*k=%.12e, xi-de*k=%.12e xj-de*k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
6865: }
6866: #ifdef DEBUGHESSIJ
6867: v1=hess[thetai][thetai];
6868: v2=hess[thetaj][thetaj];
6869: cv12=res;
6870: /* Computing eigen value of Hessian matrix */
6871: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6872: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6873: if ((lc2 <0) || (lc1 <0) ){
6874: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
6875: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
6876: printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
6877: fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
6878: }
1.126 brouard 6879: #endif
6880: }
6881: return res;
6882: }
6883:
1.203 brouard 6884: /* Not done yet: Was supposed to fix if not exactly at the maximum */
6885: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
6886: /* { */
6887: /* int i; */
6888: /* int l=1, lmax=20; */
6889: /* double k1,k2,k3,k4,res,fx; */
6890: /* double p2[MAXPARM+1]; */
6891: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
6892: /* int k=0,kmax=10; */
6893: /* double l1; */
6894:
6895: /* fx=func(x); */
6896: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
6897: /* l1=pow(10,l); */
6898: /* delts=delt; */
6899: /* for(k=1 ; k <kmax; k=k+1){ */
6900: /* delt = delti*(l1*k); */
6901: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
6902: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
6903: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
6904: /* k1=func(p2)-fx; */
6905:
6906: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
6907: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
6908: /* k2=func(p2)-fx; */
6909:
6910: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
6911: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
6912: /* k3=func(p2)-fx; */
6913:
6914: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
6915: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
6916: /* k4=func(p2)-fx; */
6917: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
6918: /* #ifdef DEBUGHESSIJ */
6919: /* printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4); */
6920: /* fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4); */
6921: /* #endif */
6922: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
6923: /* k=kmax; */
6924: /* } */
6925: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
6926: /* k=kmax; l=lmax*10; */
6927: /* } */
6928: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
6929: /* delts=delt; */
6930: /* } */
6931: /* } /\* End loop k *\/ */
6932: /* } */
6933: /* delti[theta]=delts; */
6934: /* return res; */
6935: /* } */
6936:
6937:
1.126 brouard 6938: /************** Inverse of matrix **************/
6939: void ludcmp(double **a, int n, int *indx, double *d)
6940: {
6941: int i,imax,j,k;
6942: double big,dum,sum,temp;
6943: double *vv;
6944:
6945: vv=vector(1,n);
6946: *d=1.0;
6947: for (i=1;i<=n;i++) {
6948: big=0.0;
6949: for (j=1;j<=n;j++)
6950: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 6951: if (big == 0.0){
6952: printf(" Singular Hessian matrix at row %d:\n",i);
6953: for (j=1;j<=n;j++) {
6954: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
6955: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
6956: }
6957: fflush(ficlog);
6958: fclose(ficlog);
6959: nrerror("Singular matrix in routine ludcmp");
6960: }
1.126 brouard 6961: vv[i]=1.0/big;
6962: }
6963: for (j=1;j<=n;j++) {
6964: for (i=1;i<j;i++) {
6965: sum=a[i][j];
6966: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
6967: a[i][j]=sum;
6968: }
6969: big=0.0;
6970: for (i=j;i<=n;i++) {
6971: sum=a[i][j];
6972: for (k=1;k<j;k++)
6973: sum -= a[i][k]*a[k][j];
6974: a[i][j]=sum;
6975: if ( (dum=vv[i]*fabs(sum)) >= big) {
6976: big=dum;
6977: imax=i;
6978: }
6979: }
6980: if (j != imax) {
6981: for (k=1;k<=n;k++) {
6982: dum=a[imax][k];
6983: a[imax][k]=a[j][k];
6984: a[j][k]=dum;
6985: }
6986: *d = -(*d);
6987: vv[imax]=vv[j];
6988: }
6989: indx[j]=imax;
6990: if (a[j][j] == 0.0) a[j][j]=TINY;
6991: if (j != n) {
6992: dum=1.0/(a[j][j]);
6993: for (i=j+1;i<=n;i++) a[i][j] *= dum;
6994: }
6995: }
6996: free_vector(vv,1,n); /* Doesn't work */
6997: ;
6998: }
6999:
7000: void lubksb(double **a, int n, int *indx, double b[])
7001: {
7002: int i,ii=0,ip,j;
7003: double sum;
7004:
7005: for (i=1;i<=n;i++) {
7006: ip=indx[i];
7007: sum=b[ip];
7008: b[ip]=b[i];
7009: if (ii)
7010: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
7011: else if (sum) ii=i;
7012: b[i]=sum;
7013: }
7014: for (i=n;i>=1;i--) {
7015: sum=b[i];
7016: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
7017: b[i]=sum/a[i][i];
7018: }
7019: }
7020:
7021: void pstamp(FILE *fichier)
7022: {
1.196 brouard 7023: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 7024: }
7025:
1.297 brouard 7026: void date2dmy(double date,double *day, double *month, double *year){
7027: double yp=0., yp1=0., yp2=0.;
7028:
7029: yp1=modf(date,&yp);/* extracts integral of date in yp and
7030: fractional in yp1 */
7031: *year=yp;
7032: yp2=modf((yp1*12),&yp);
7033: *month=yp;
7034: yp1=modf((yp2*30.5),&yp);
7035: *day=yp;
7036: if(*day==0) *day=1;
7037: if(*month==0) *month=1;
7038: }
7039:
1.253 brouard 7040:
7041:
1.126 brouard 7042: /************ Frequencies ********************/
1.251 brouard 7043: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 7044: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
7045: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 7046: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 7047: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 7048: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 7049: int iind=0, iage=0;
7050: int mi; /* Effective wave */
7051: int first;
7052: double ***freq; /* Frequencies */
1.268 brouard 7053: double *x, *y, a=0.,b=0.,r=1., sa=0., sb=0.; /* for regression, y=b+m*x and r is the correlation coefficient */
7054: int no=0, linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb);
1.284 brouard 7055: double *meanq, *stdq, *idq;
1.226 brouard 7056: double **meanqt;
7057: double *pp, **prop, *posprop, *pospropt;
7058: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
7059: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
7060: double agebegin, ageend;
7061:
7062: pp=vector(1,nlstate);
1.251 brouard 7063: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 7064: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
7065: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
7066: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
7067: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 7068: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 7069: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 7070: meanqt=matrix(1,lastpass,1,nqtveff);
7071: strcpy(fileresp,"P_");
7072: strcat(fileresp,fileresu);
7073: /*strcat(fileresphtm,fileresu);*/
7074: if((ficresp=fopen(fileresp,"w"))==NULL) {
7075: printf("Problem with prevalence resultfile: %s\n", fileresp);
7076: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
7077: exit(0);
7078: }
1.240 brouard 7079:
1.226 brouard 7080: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
7081: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
7082: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
7083: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
7084: fflush(ficlog);
7085: exit(70);
7086: }
7087: else{
7088: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 7089: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 7090: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 7091: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
7092: }
1.319 brouard 7093: fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies (weight=%d) and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm, weightopt);
1.240 brouard 7094:
1.226 brouard 7095: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
7096: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
7097: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
7098: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
7099: fflush(ficlog);
7100: exit(70);
1.240 brouard 7101: } else{
1.226 brouard 7102: fprintf(ficresphtmfr,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.319 brouard 7103: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 7104: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 7105: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
7106: }
1.319 brouard 7107: fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>(weight=%d) frequencies of all effective transitions of the model, by age at begin of transition, and covariate value at the begin of transition (if the covariate is a varying covariate) </h4>Unknown status is -1<br/>\n",fileresphtmfr, fileresphtmfr,weightopt);
1.240 brouard 7108:
1.253 brouard 7109: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
7110: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 7111: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 7112: j1=0;
1.126 brouard 7113:
1.227 brouard 7114: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 7115: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 7116: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 7117: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 7118:
7119:
1.226 brouard 7120: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
7121: reference=low_education V1=0,V2=0
7122: med_educ V1=1 V2=0,
7123: high_educ V1=0 V2=1
1.330 brouard 7124: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 7125: */
1.249 brouard 7126: dateintsum=0;
7127: k2cpt=0;
7128:
1.253 brouard 7129: if(cptcoveff == 0 )
1.265 brouard 7130: nl=1; /* Constant and age model only */
1.253 brouard 7131: else
7132: nl=2;
1.265 brouard 7133:
7134: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
7135: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 7136: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 7137: * freq[s1][s2][iage] =0.
7138: * Loop on iind
7139: * ++freq[s1][s2][iage] weighted
7140: * end iind
7141: * if covariate and j!0
7142: * headers Variable on one line
7143: * endif cov j!=0
7144: * header of frequency table by age
7145: * Loop on age
7146: * pp[s1]+=freq[s1][s2][iage] weighted
7147: * pos+=freq[s1][s2][iage] weighted
7148: * Loop on s1 initial state
7149: * fprintf(ficresp
7150: * end s1
7151: * end age
7152: * if j!=0 computes starting values
7153: * end compute starting values
7154: * end j1
7155: * end nl
7156: */
1.253 brouard 7157: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
7158: if(nj==1)
7159: j=0; /* First pass for the constant */
1.265 brouard 7160: else{
1.335 brouard 7161: j=cptcoveff; /* Other passes for the covariate values number of simple covariates in the model V2+V1 =2 (simple dummy fixed or time varying) */
1.265 brouard 7162: }
1.251 brouard 7163: first=1;
1.332 brouard 7164: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all dummy covariates combination of the model, ie excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
1.251 brouard 7165: posproptt=0.;
1.330 brouard 7166: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 7167: scanf("%d", i);*/
7168: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 7169: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 7170: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 7171: freq[i][s2][m]=0;
1.251 brouard 7172:
7173: for (i=1; i<=nlstate; i++) {
1.240 brouard 7174: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 7175: prop[i][m]=0;
7176: posprop[i]=0;
7177: pospropt[i]=0;
7178: }
1.283 brouard 7179: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 7180: idq[z1]=0.;
7181: meanq[z1]=0.;
7182: stdq[z1]=0.;
1.283 brouard 7183: }
7184: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 7185: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 7186: /* meanqt[m][z1]=0.; */
7187: /* } */
7188: /* } */
1.251 brouard 7189: /* dateintsum=0; */
7190: /* k2cpt=0; */
7191:
1.265 brouard 7192: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 7193: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
7194: bool=1;
7195: if(j !=0){
7196: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 7197: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
7198: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 7199: /* if(Tvaraff[z1] ==-20){ */
7200: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
7201: /* }else if(Tvaraff[z1] ==-10){ */
7202: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 7203: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 7204: /* if( iind >=imx-3) printf("Searching error iind=%d Tvaraff[z1]=%d covar[Tvaraff[z1]][iind]=%.f TnsdVar[Tvaraff[z1]]=%d, cptcoveff=%d, cptcovs=%d \n",iind, Tvaraff[z1], covar[Tvaraff[z1]][iind],TnsdVar[Tvaraff[z1]],cptcoveff, cptcovs); */
7205: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 7206: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 7207: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 7208: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 7209: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 7210: /* printf("bool=%d i=%d, z1=%d, Tvaraff[%d]=%d, covar[Tvarff][%d]=%2f, codtabm(%d,%d)=%d, nbcode[Tvaraff][codtabm(%d,%d)=%d, j1=%d\n", */
7211: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
7212: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 7213: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
7214: } /* Onlyf fixed */
7215: } /* end z1 */
1.335 brouard 7216: } /* cptcoveff > 0 */
1.251 brouard 7217: } /* end any */
7218: }/* end j==0 */
1.265 brouard 7219: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 7220: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 7221: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 7222: m=mw[mi][iind];
7223: if(j!=0){
7224: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 7225: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 7226: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 7227: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
7228: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 7229: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality. If covariate's
1.251 brouard 7230: value is -1, we don't select. It differs from the
7231: constant and age model which counts them. */
7232: bool=0; /* not selected */
7233: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 7234: /* i1=Tvaraff[z1]; */
7235: /* i2=TnsdVar[i1]; */
7236: /* i3=nbcode[i1][i2]; */
7237: /* i4=covar[i1][iind]; */
7238: /* if(i4 != i3){ */
7239: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 7240: bool=0;
7241: }
7242: }
7243: }
7244: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
7245: } /* end j==0 */
7246: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 7247: if(bool==1){ /*Selected */
1.251 brouard 7248: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
7249: and mw[mi+1][iind]. dh depends on stepm. */
7250: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
7251: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
7252: if(m >=firstpass && m <=lastpass){
7253: k2=anint[m][iind]+(mint[m][iind]/12.);
7254: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
7255: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
7256: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
7257: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
7258: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
7259: if (m<lastpass) {
7260: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
7261: /* printf(" num=%ld m=%d, iind=%d s1=%d s2=%d agev at m=%d\n", num[iind], m, iind,s[m][iind],s[m+1][iind], (int)agev[m][iind]); */
7262: if(s[m][iind]==-1)
7263: printf(" num=%ld m=%d, iind=%d s1=%d s2=%d agev at m=%d agebegin=%.2f ageend=%.2f, agemed=%d\n", num[iind], m, iind,s[m][iind],s[m+1][iind], (int)agev[m][iind],agebegin, ageend, (int)((agebegin+ageend)/2.));
7264: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
1.311 brouard 7265: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
7266: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 7267: idq[z1]=idq[z1]+weight[iind];
7268: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
7269: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
7270: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 7271: }
1.284 brouard 7272: }
1.251 brouard 7273: /* if((int)agev[m][iind] == 55) */
7274: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
7275: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
7276: freq[s[m][iind]][s[m+1][iind]][iagemax+3] += weight[iind]; /* Total is in iagemax+3 *//* At age of beginning of transition, where status is known */
1.234 brouard 7277: }
1.251 brouard 7278: } /* end if between passes */
7279: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
7280: dateintsum=dateintsum+k2; /* on all covariates ?*/
7281: k2cpt++;
7282: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 7283: }
1.251 brouard 7284: }else{
7285: bool=1;
7286: }/* end bool 2 */
7287: } /* end m */
1.284 brouard 7288: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
7289: /* idq[z1]=idq[z1]+weight[iind]; */
7290: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
7291: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
7292: /* } */
1.251 brouard 7293: } /* end bool */
7294: } /* end iind = 1 to imx */
1.319 brouard 7295: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 7296: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
7297:
7298:
7299: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 7300: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 7301: pstamp(ficresp);
1.335 brouard 7302: if (cptcoveff>0 && j!=0){
1.265 brouard 7303: pstamp(ficresp);
1.251 brouard 7304: printf( "\n#********** Variable ");
7305: fprintf(ficresp, "\n#********** Variable ");
7306: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
7307: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
7308: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 7309: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 7310: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 7311: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7312: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7313: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7314: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7315: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 7316: }else{
1.330 brouard 7317: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7318: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7319: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7320: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7321: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 7322: }
7323: }
7324: printf( "**********\n#");
7325: fprintf(ficresp, "**********\n#");
7326: fprintf(ficresphtm, "**********</h3>\n");
7327: fprintf(ficresphtmfr, "**********</h3>\n");
7328: fprintf(ficlog, "**********\n");
7329: }
1.284 brouard 7330: /*
7331: Printing means of quantitative variables if any
7332: */
7333: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 7334: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 7335: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 7336: if(weightopt==1){
7337: printf(" Weighted mean and standard deviation of");
7338: fprintf(ficlog," Weighted mean and standard deviation of");
7339: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
7340: }
1.311 brouard 7341: /* mu = \frac{w x}{\sum w}
7342: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
7343: */
7344: printf(" fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
7345: fprintf(ficlog," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
7346: fprintf(ficresphtmfr," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)<p>\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
1.284 brouard 7347: }
7348: /* for (z1=1; z1<= nqtveff; z1++) { */
7349: /* for(m=1;m<=lastpass;m++){ */
7350: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
7351: /* } */
7352: /* } */
1.283 brouard 7353:
1.251 brouard 7354: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 7355: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 7356: fprintf(ficresp, " Age");
1.335 brouard 7357: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
7358: printf(" V%d=%d, z1=%d, Tvaraff[z1]=%d, j1=%d, TnsdVar[Tvaraff[%d]]=%d |",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])], z1, Tvaraff[z1], j1,z1,TnsdVar[Tvaraff[z1]]);
7359: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7360: }
1.251 brouard 7361: for(i=1; i<=nlstate;i++) {
1.335 brouard 7362: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 7363: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
7364: }
1.335 brouard 7365: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 7366: fprintf(ficresphtm, "\n");
7367:
7368: /* Header of frequency table by age */
7369: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
7370: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 7371: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 7372: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 7373: if(s2!=0 && m!=0)
7374: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 7375: }
1.226 brouard 7376: }
1.251 brouard 7377: fprintf(ficresphtmfr, "\n");
7378:
7379: /* For each age */
7380: for(iage=iagemin; iage <= iagemax+3; iage++){
7381: fprintf(ficresphtm,"<tr>");
7382: if(iage==iagemax+1){
7383: fprintf(ficlog,"1");
7384: fprintf(ficresphtmfr,"<tr><th>0</th> ");
7385: }else if(iage==iagemax+2){
7386: fprintf(ficlog,"0");
7387: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
7388: }else if(iage==iagemax+3){
7389: fprintf(ficlog,"Total");
7390: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
7391: }else{
1.240 brouard 7392: if(first==1){
1.251 brouard 7393: first=0;
7394: printf("See log file for details...\n");
7395: }
7396: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
7397: fprintf(ficlog,"Age %d", iage);
7398: }
1.265 brouard 7399: for(s1=1; s1 <=nlstate ; s1++){
7400: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
7401: pp[s1] += freq[s1][m][iage];
1.251 brouard 7402: }
1.265 brouard 7403: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 7404: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 7405: pos += freq[s1][m][iage];
7406: if(pp[s1]>=1.e-10){
1.251 brouard 7407: if(first==1){
1.265 brouard 7408: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 7409: }
1.265 brouard 7410: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 7411: }else{
7412: if(first==1)
1.265 brouard 7413: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
7414: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 7415: }
7416: }
7417:
1.265 brouard 7418: for(s1=1; s1 <=nlstate ; s1++){
7419: /* posprop[s1]=0; */
7420: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
7421: pp[s1] += freq[s1][m][iage];
7422: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
7423:
7424: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
7425: pos += pp[s1]; /* pos is the total number of transitions until this age */
7426: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
7427: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
7428: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
7429: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
7430: }
7431:
7432: /* Writing ficresp */
1.335 brouard 7433: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 7434: if( iage <= iagemax){
7435: fprintf(ficresp," %d",iage);
7436: }
7437: }else if( nj==2){
7438: if( iage <= iagemax){
7439: fprintf(ficresp," %d",iage);
1.335 brouard 7440: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 7441: }
1.240 brouard 7442: }
1.265 brouard 7443: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 7444: if(pos>=1.e-5){
1.251 brouard 7445: if(first==1)
1.265 brouard 7446: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
7447: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 7448: }else{
7449: if(first==1)
1.265 brouard 7450: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
7451: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 7452: }
7453: if( iage <= iagemax){
7454: if(pos>=1.e-5){
1.335 brouard 7455: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 7456: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7457: }else if( nj==2){
7458: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7459: }
7460: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7461: /*probs[iage][s1][j1]= pp[s1]/pos;*/
7462: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
7463: } else{
1.335 brouard 7464: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 7465: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 7466: }
1.240 brouard 7467: }
1.265 brouard 7468: pospropt[s1] +=posprop[s1];
7469: } /* end loop s1 */
1.251 brouard 7470: /* pospropt=0.; */
1.265 brouard 7471: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 7472: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 7473: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 7474: if(first==1){
1.265 brouard 7475: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 7476: }
1.265 brouard 7477: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
7478: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 7479: }
1.265 brouard 7480: if(s1!=0 && m!=0)
7481: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 7482: }
1.265 brouard 7483: } /* end loop s1 */
1.251 brouard 7484: posproptt=0.;
1.265 brouard 7485: for(s1=1; s1 <=nlstate; s1++){
7486: posproptt += pospropt[s1];
1.251 brouard 7487: }
7488: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 7489: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 7490: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 7491: if(iage <= iagemax)
7492: fprintf(ficresp,"\n");
1.240 brouard 7493: }
1.251 brouard 7494: if(first==1)
7495: printf("Others in log...\n");
7496: fprintf(ficlog,"\n");
7497: } /* end loop age iage */
1.265 brouard 7498:
1.251 brouard 7499: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 7500: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 7501: if(posproptt < 1.e-5){
1.265 brouard 7502: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 7503: }else{
1.265 brouard 7504: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 7505: }
1.226 brouard 7506: }
1.251 brouard 7507: fprintf(ficresphtm,"</tr>\n");
7508: fprintf(ficresphtm,"</table>\n");
7509: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 7510: if(posproptt < 1.e-5){
1.251 brouard 7511: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
7512: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 7513: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
7514: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 7515: invalidvarcomb[j1]=1;
1.226 brouard 7516: }else{
1.338 brouard 7517: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 7518: invalidvarcomb[j1]=0;
1.226 brouard 7519: }
1.251 brouard 7520: fprintf(ficresphtmfr,"</table>\n");
7521: fprintf(ficlog,"\n");
7522: if(j!=0){
7523: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 7524: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 7525: for(k=1; k <=(nlstate+ndeath); k++){
7526: if (k != i) {
1.265 brouard 7527: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 7528: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 7529: if(j1==1){ /* All dummy covariates to zero */
7530: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
7531: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 7532: printf("%d%d ",i,k);
7533: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 7534: printf("%12.7f ln(%.0f/%.0f)= %f, OR=%f sd=%f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]),freq[i][k][iagemax+3]/freq[i][i][iagemax+3], sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]));
7535: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
7536: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 7537: }
1.253 brouard 7538: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
7539: for(iage=iagemin; iage <= iagemax+3; iage++){
7540: x[iage]= (double)iage;
7541: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 7542: /* printf("i=%d, k=%d, s1=%d, j1=%d, jj=%d, y[%d]=%f\n",i,k,s1,j1,jj, iage, y[iage]); */
1.253 brouard 7543: }
1.268 brouard 7544: /* Some are not finite, but linreg will ignore these ages */
7545: no=0;
1.253 brouard 7546: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 7547: pstart[s1]=b;
7548: pstart[s1-1]=a;
1.252 brouard 7549: }else if( j1!=1 && (j1==2 || (log(j1-1.)/log(2.)-(int)(log(j1-1.)/log(2.))) <0.010) && ( TvarsDind[(int)(log(j1-1.)/log(2.))+1]+2+nagesqr == jj) && Dummy[jj-2-nagesqr]==0){ /* We want only if the position, jj, in model corresponds to unique covariate equal to 1 in j1 combination */
7550: printf("j1=%d, jj=%d, (int)(log(j1-1.)/log(2.))+1=%d, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(int)(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
7551: printf("j1=%d, jj=%d, (log(j1-1.)/log(2.))+1=%f, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
1.265 brouard 7552: pstart[s1]= log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]));
1.252 brouard 7553: printf("%d%d ",i,k);
7554: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 7555: printf("s1=%d,i=%d,k=%d,p[%d]=%12.7f ln((%.0f/%.0f)/(%.0f/%.0f))= %f, OR=%f sd=%f \n",s1,i,k,s1,p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3],freq[i][k][iagemax+4],freq[i][i][iagemax+4], log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4])),(freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]), sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]+1/freq[i][k][iagemax+4]+1/freq[i][i][iagemax+4]));
1.251 brouard 7556: }else{ /* Other cases, like quantitative fixed or varying covariates */
7557: ;
7558: }
7559: /* printf("%12.7f )", param[i][jj][k]); */
7560: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 7561: s1++;
1.251 brouard 7562: } /* end jj */
7563: } /* end k!= i */
7564: } /* end k */
1.265 brouard 7565: } /* end i, s1 */
1.251 brouard 7566: } /* end j !=0 */
7567: } /* end selected combination of covariate j1 */
7568: if(j==0){ /* We can estimate starting values from the occurences in each case */
7569: printf("#Freqsummary: Starting values for the constants:\n");
7570: fprintf(ficlog,"\n");
1.265 brouard 7571: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 7572: for(k=1; k <=(nlstate+ndeath); k++){
7573: if (k != i) {
7574: printf("%d%d ",i,k);
7575: fprintf(ficlog,"%d%d ",i,k);
7576: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 7577: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 7578: if(jj==1){ /* Age has to be done */
1.265 brouard 7579: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
7580: printf("%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
7581: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
1.251 brouard 7582: }
7583: /* printf("%12.7f )", param[i][jj][k]); */
7584: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 7585: s1++;
1.250 brouard 7586: }
1.251 brouard 7587: printf("\n");
7588: fprintf(ficlog,"\n");
1.250 brouard 7589: }
7590: }
1.284 brouard 7591: } /* end of state i */
1.251 brouard 7592: printf("#Freqsummary\n");
7593: fprintf(ficlog,"\n");
1.265 brouard 7594: for(s1=-1; s1 <=nlstate+ndeath; s1++){
7595: for(s2=-1; s2 <=nlstate+ndeath; s2++){
7596: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
7597: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
7598: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
7599: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
7600: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
7601: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 7602: /* } */
7603: }
1.265 brouard 7604: } /* end loop s1 */
1.251 brouard 7605:
7606: printf("\n");
7607: fprintf(ficlog,"\n");
7608: } /* end j=0 */
1.249 brouard 7609: } /* end j */
1.252 brouard 7610:
1.253 brouard 7611: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 7612: for(i=1, jk=1; i <=nlstate; i++){
7613: for(j=1; j <=nlstate+ndeath; j++){
7614: if(j!=i){
7615: /*ca[0]= k+'a'-1;ca[1]='\0';*/
7616: printf("%1d%1d",i,j);
7617: fprintf(ficparo,"%1d%1d",i,j);
7618: for(k=1; k<=ncovmodel;k++){
7619: /* printf(" %lf",param[i][j][k]); */
7620: /* fprintf(ficparo," %lf",param[i][j][k]); */
7621: p[jk]=pstart[jk];
7622: printf(" %f ",pstart[jk]);
7623: fprintf(ficparo," %f ",pstart[jk]);
7624: jk++;
7625: }
7626: printf("\n");
7627: fprintf(ficparo,"\n");
7628: }
7629: }
7630: }
7631: } /* end mle=-2 */
1.226 brouard 7632: dateintmean=dateintsum/k2cpt;
1.296 brouard 7633: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 7634:
1.226 brouard 7635: fclose(ficresp);
7636: fclose(ficresphtm);
7637: fclose(ficresphtmfr);
1.283 brouard 7638: free_vector(idq,1,nqfveff);
1.226 brouard 7639: free_vector(meanq,1,nqfveff);
1.284 brouard 7640: free_vector(stdq,1,nqfveff);
1.226 brouard 7641: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 7642: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
7643: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 7644: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 7645: free_vector(pospropt,1,nlstate);
7646: free_vector(posprop,1,nlstate);
1.251 brouard 7647: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 7648: free_vector(pp,1,nlstate);
7649: /* End of freqsummary */
7650: }
1.126 brouard 7651:
1.268 brouard 7652: /* Simple linear regression */
7653: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
7654:
7655: /* y=a+bx regression */
7656: double sumx = 0.0; /* sum of x */
7657: double sumx2 = 0.0; /* sum of x**2 */
7658: double sumxy = 0.0; /* sum of x * y */
7659: double sumy = 0.0; /* sum of y */
7660: double sumy2 = 0.0; /* sum of y**2 */
7661: double sume2 = 0.0; /* sum of square or residuals */
7662: double yhat;
7663:
7664: double denom=0;
7665: int i;
7666: int ne=*no;
7667:
7668: for ( i=ifi, ne=0;i<=ila;i++) {
7669: if(!isfinite(x[i]) || !isfinite(y[i])){
7670: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
7671: continue;
7672: }
7673: ne=ne+1;
7674: sumx += x[i];
7675: sumx2 += x[i]*x[i];
7676: sumxy += x[i] * y[i];
7677: sumy += y[i];
7678: sumy2 += y[i]*y[i];
7679: denom = (ne * sumx2 - sumx*sumx);
7680: /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
7681: }
7682:
7683: denom = (ne * sumx2 - sumx*sumx);
7684: if (denom == 0) {
7685: // vertical, slope m is infinity
7686: *b = INFINITY;
7687: *a = 0;
7688: if (r) *r = 0;
7689: return 1;
7690: }
7691:
7692: *b = (ne * sumxy - sumx * sumy) / denom;
7693: *a = (sumy * sumx2 - sumx * sumxy) / denom;
7694: if (r!=NULL) {
7695: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
7696: sqrt((sumx2 - sumx*sumx/ne) *
7697: (sumy2 - sumy*sumy/ne));
7698: }
7699: *no=ne;
7700: for ( i=ifi, ne=0;i<=ila;i++) {
7701: if(!isfinite(x[i]) || !isfinite(y[i])){
7702: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
7703: continue;
7704: }
7705: ne=ne+1;
7706: yhat = y[i] - *a -*b* x[i];
7707: sume2 += yhat * yhat ;
7708:
7709: denom = (ne * sumx2 - sumx*sumx);
7710: /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
7711: }
7712: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
7713: *sa= *sb * sqrt(sumx2/ne);
7714:
7715: return 0;
7716: }
7717:
1.126 brouard 7718: /************ Prevalence ********************/
1.227 brouard 7719: void prevalence(double ***probs, double agemin, double agemax, int **s, double **agev, int nlstate, int imx, int *Tvar, int **nbcode, int *ncodemax,double **mint,double **anint, double dateprev1,double dateprev2, int firstpass, int lastpass)
7720: {
7721: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
7722: in each health status at the date of interview (if between dateprev1 and dateprev2).
7723: We still use firstpass and lastpass as another selection.
7724: */
1.126 brouard 7725:
1.227 brouard 7726: int i, m, jk, j1, bool, z1,j, iv;
7727: int mi; /* Effective wave */
7728: int iage;
1.359 brouard 7729: double agebegin; /*, ageend;*/
1.227 brouard 7730:
7731: double **prop;
7732: double posprop;
7733: double y2; /* in fractional years */
7734: int iagemin, iagemax;
7735: int first; /** to stop verbosity which is redirected to log file */
7736:
7737: iagemin= (int) agemin;
7738: iagemax= (int) agemax;
7739: /*pp=vector(1,nlstate);*/
1.251 brouard 7740: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 7741: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
7742: j1=0;
1.222 brouard 7743:
1.227 brouard 7744: /*j=cptcoveff;*/
7745: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 7746:
1.288 brouard 7747: first=0;
1.335 brouard 7748: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 7749: for (i=1; i<=nlstate; i++)
1.251 brouard 7750: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 7751: prop[i][iage]=0.0;
7752: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
7753: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
7754: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
7755:
7756: for (i=1; i<=imx; i++) { /* Each individual */
7757: bool=1;
7758: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
7759: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
7760: m=mw[mi][i];
7761: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
7762: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
7763: for (z1=1; z1<=cptcoveff; z1++){
7764: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 7765: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 7766: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 7767: bool=0;
7768: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 7769: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 7770: bool=0;
7771: }
7772: }
7773: if(bool==1){ /* Otherwise we skip that wave/person */
7774: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
7775: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
7776: if(m >=firstpass && m <=lastpass){
7777: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
7778: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
7779: if(agev[m][i]==0) agev[m][i]=iagemax+1;
7780: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 7781: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 7782: printf("Error on individual # %d agev[m][i]=%f <%d-%d or > %d+3+%d m=%d; either change agemin or agemax or fix data\n",i, agev[m][i],iagemin,AGEMARGE, iagemax,AGEMARGE,m);
7783: exit(1);
7784: }
7785: if (s[m][i]>0 && s[m][i]<=nlstate) {
7786: /*if(i>4620) printf(" i=%d m=%d s[m][i]=%d (int)agev[m][i]=%d weight[i]=%f prop=%f\n",i,m,s[m][i],(int)agev[m][m],weight[i],prop[s[m][i]][(int)agev[m][i]]);*/
7787: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
7788: prop[s[m][i]][iagemax+3] += weight[i];
7789: } /* end valid statuses */
7790: } /* end selection of dates */
7791: } /* end selection of waves */
7792: } /* end bool */
7793: } /* end wave */
7794: } /* end individual */
7795: for(i=iagemin; i <= iagemax+3; i++){
7796: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
7797: posprop += prop[jk][i];
7798: }
7799:
7800: for(jk=1; jk <=nlstate ; jk++){
7801: if( i <= iagemax){
7802: if(posprop>=1.e-5){
7803: probs[i][jk][j1]= prop[jk][i]/posprop;
7804: } else{
1.288 brouard 7805: if(!first){
7806: first=1;
1.266 brouard 7807: printf("Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
7808: }else{
1.288 brouard 7809: fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases.\n",jk,i,jk, j1,probs[i][jk][j1]);
1.227 brouard 7810: }
7811: }
7812: }
7813: }/* end jk */
7814: }/* end i */
1.222 brouard 7815: /*} *//* end i1 */
1.227 brouard 7816: } /* end j1 */
1.222 brouard 7817:
1.227 brouard 7818: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
7819: /*free_vector(pp,1,nlstate);*/
1.251 brouard 7820: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 7821: } /* End of prevalence */
1.126 brouard 7822:
7823: /************* Waves Concatenation ***************/
7824:
7825: void concatwav(int wav[], int **dh, int **bh, int **mw, int **s, double *agedc, double **agev, int firstpass, int lastpass, int imx, int nlstate, int stepm)
7826: {
1.298 brouard 7827: /* Concatenates waves: wav[i] is the number of effective (useful waves in the sense that a non interview is useless) of individual i.
1.126 brouard 7828: Death is a valid wave (if date is known).
7829: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
7830: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 7831: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 7832: */
1.126 brouard 7833:
1.224 brouard 7834: int i=0, mi=0, m=0, mli=0;
1.126 brouard 7835: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
7836: double sum=0., jmean=0.;*/
1.224 brouard 7837: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 7838: int j, k=0,jk, ju, jl;
7839: double sum=0.;
7840: first=0;
1.214 brouard 7841: firstwo=0;
1.217 brouard 7842: firsthree=0;
1.218 brouard 7843: firstfour=0;
1.164 brouard 7844: jmin=100000;
1.126 brouard 7845: jmax=-1;
7846: jmean=0.;
1.224 brouard 7847:
7848: /* Treating live states */
1.214 brouard 7849: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 7850: mi=0; /* First valid wave */
1.227 brouard 7851: mli=0; /* Last valid wave */
1.309 brouard 7852: m=firstpass; /* Loop on waves */
7853: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 7854: if(m >firstpass && s[m][i]==s[m-1][i] && mint[m][i]==mint[m-1][i] && anint[m][i]==anint[m-1][i]){/* Two succesive identical information on wave m */
7855: mli=m-1;/* mw[++mi][i]=m-1; */
7856: }else if(s[m][i]>=1 || s[m][i]==-4 || s[m][i]==-5){ /* Since 0.98r4 if status=-2 vital status is really unknown, wave should be skipped */
1.309 brouard 7857: mw[++mi][i]=m; /* Valid wave: incrementing mi and updating mi; mw[mi] is the wave number of mi_th valid transition */
1.227 brouard 7858: mli=m;
1.224 brouard 7859: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
7860: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 7861: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 7862: }
1.309 brouard 7863: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 7864: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 7865: break;
1.224 brouard 7866: #else
1.317 brouard 7867: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){ /* no death date and known date of interview, case -2 (vital status unknown is warned later */
1.227 brouard 7868: if(firsthree == 0){
1.302 brouard 7869: printf("Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
1.227 brouard 7870: firsthree=1;
1.317 brouard 7871: }else if(firsthree >=1 && firsthree < 10){
7872: fprintf(ficlog,"Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
7873: firsthree++;
7874: }else if(firsthree == 10){
7875: printf("Information, too many Information flags: no more reported to log either\n");
7876: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
7877: firsthree++;
7878: }else{
7879: firsthree++;
1.227 brouard 7880: }
1.309 brouard 7881: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 7882: mli=m;
7883: }
7884: if(s[m][i]==-2){ /* Vital status is really unknown */
7885: nbwarn++;
1.309 brouard 7886: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 7887: printf("Warning! Vital status for individual %ld (line=%d) at last wave %d interviewed at date %d/%d is unknown %d. Please, check if the vital status and the date of death %d/%d are really unknown. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], (int) moisdc[i], (int) andc[i], i, m);
7888: fprintf(ficlog,"Warning! Vital status for individual %ld (line=%d) at last wave %d interviewed at date %d/%d is unknown %d. Please, check if the vital status and the date of death %d/%d are really unknown. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], (int) moisdc[i], (int) andc[i], i, m);
7889: }
7890: break;
7891: }
7892: break;
1.224 brouard 7893: #endif
1.227 brouard 7894: }/* End m >= lastpass */
1.126 brouard 7895: }/* end while */
1.224 brouard 7896:
1.227 brouard 7897: /* mi is the last effective wave, m is lastpass, mw[j][i] gives the # of j-th effective wave for individual i */
1.216 brouard 7898: /* After last pass */
1.224 brouard 7899: /* Treating death states */
1.214 brouard 7900: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 7901: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
7902: /* } */
1.126 brouard 7903: mi++; /* Death is another wave */
7904: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 7905: /* Only death is a correct wave */
1.126 brouard 7906: mw[mi][i]=m;
1.257 brouard 7907: } /* else not in a death state */
1.224 brouard 7908: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 7909: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 7910: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 7911: if((andc[i]+moisdc[i]/12.) <=(anint[m][i]+mint[m][i]/12.)){ /* month of death occured before last wave month and status should have been death instead of -1 */
1.227 brouard 7912: nbwarn++;
7913: if(firstfiv==0){
1.309 brouard 7914: printf("Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7915: firstfiv=1;
7916: }else{
1.309 brouard 7917: fprintf(ficlog,"Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7918: }
1.309 brouard 7919: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
7920: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 7921: nberr++;
7922: if(firstwo==0){
1.309 brouard 7923: printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7924: firstwo=1;
7925: }
1.309 brouard 7926: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\n\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7927: }
1.257 brouard 7928: }else{ /* if date of interview is unknown */
1.227 brouard 7929: /* death is known but not confirmed by death status at any wave */
7930: if(firstfour==0){
1.309 brouard 7931: printf("Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d with status %d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7932: firstfour=1;
7933: }
1.309 brouard 7934: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d with status %d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.214 brouard 7935: }
1.224 brouard 7936: } /* end if date of death is known */
7937: #endif
1.309 brouard 7938: wav[i]=mi; /* mi should be the last effective wave (or mli), */
7939: /* wav[i]=mw[mi][i]; */
1.126 brouard 7940: if(mi==0){
7941: nbwarn++;
7942: if(first==0){
1.227 brouard 7943: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
7944: first=1;
1.126 brouard 7945: }
7946: if(first==1){
1.227 brouard 7947: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 7948: }
7949: } /* end mi==0 */
7950: } /* End individuals */
1.214 brouard 7951: /* wav and mw are no more changed */
1.223 brouard 7952:
1.317 brouard 7953: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
7954: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
7955:
7956:
1.126 brouard 7957: for(i=1; i<=imx; i++){
7958: for(mi=1; mi<wav[i];mi++){
7959: if (stepm <=0)
1.227 brouard 7960: dh[mi][i]=1;
1.126 brouard 7961: else{
1.260 brouard 7962: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 7963: if (agedc[i] < 2*AGESUP) {
7964: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
7965: if(j==0) j=1; /* Survives at least one month after exam */
7966: else if(j<0){
7967: nberr++;
1.359 brouard 7968: printf("Error! Negative delay (%d to death) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
1.227 brouard 7969: j=1; /* Temporary Dangerous patch */
7970: printf(" We assumed that the date of interview was correct (and not the date of death) and postponed the death %d month(s) (one stepm) after the interview. You MUST fix the contradiction between dates.\n",stepm);
1.359 brouard 7971: fprintf(ficlog,"Error! Negative delay (%d to death) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
1.227 brouard 7972: fprintf(ficlog," We assumed that the date of interview was correct (and not the date of death) and postponed the death %d month(s) (one stepm) after the interview. You MUST fix the contradiction between dates.\n",stepm);
7973: }
7974: k=k+1;
7975: if (j >= jmax){
7976: jmax=j;
7977: ijmax=i;
7978: }
7979: if (j <= jmin){
7980: jmin=j;
7981: ijmin=i;
7982: }
7983: sum=sum+j;
7984: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
7985: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
7986: }
7987: }
7988: else{
7989: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 7990: /* if (j<0) printf("%d %lf %lf %d %d %d\n", i,agev[mw[mi+1][i]][i], agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); */
1.223 brouard 7991:
1.227 brouard 7992: k=k+1;
7993: if (j >= jmax) {
7994: jmax=j;
7995: ijmax=i;
7996: }
7997: else if (j <= jmin){
7998: jmin=j;
7999: ijmin=i;
8000: }
8001: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
8002: /*printf("%d %lf %d %d %d\n", i,agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);*/
8003: if(j<0){
8004: nberr++;
1.359 brouard 8005: printf("Error! Negative delay (%d) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
8006: fprintf(ficlog,"Error! Negative delay (%d) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
1.227 brouard 8007: }
8008: sum=sum+j;
8009: }
8010: jk= j/stepm;
8011: jl= j -jk*stepm;
8012: ju= j -(jk+1)*stepm;
8013: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
8014: if(jl==0){
8015: dh[mi][i]=jk;
8016: bh[mi][i]=0;
8017: }else{ /* We want a negative bias in order to only have interpolation ie
8018: * to avoid the price of an extra matrix product in likelihood */
8019: dh[mi][i]=jk+1;
8020: bh[mi][i]=ju;
8021: }
8022: }else{
8023: if(jl <= -ju){
8024: dh[mi][i]=jk;
8025: bh[mi][i]=jl; /* bias is positive if real duration
8026: * is higher than the multiple of stepm and negative otherwise.
8027: */
8028: }
8029: else{
8030: dh[mi][i]=jk+1;
8031: bh[mi][i]=ju;
8032: }
8033: if(dh[mi][i]==0){
8034: dh[mi][i]=1; /* At least one step */
8035: bh[mi][i]=ju; /* At least one step */
8036: /* printf(" bh=%d ju=%d jl=%d dh=%d jk=%d stepm=%d %d\n",bh[mi][i],ju,jl,dh[mi][i],jk,stepm,i);*/
8037: }
8038: } /* end if mle */
1.126 brouard 8039: }
8040: } /* end wave */
8041: }
8042: jmean=sum/k;
8043: printf("Delay (in months) between two waves Min=%d (for indiviudal %ld) Max=%d (%ld) Mean=%f\n\n ",jmin, num[ijmin], jmax, num[ijmax], jmean);
1.141 brouard 8044: fprintf(ficlog,"Delay (in months) between two waves Min=%d (for indiviudal %d) Max=%d (%d) Mean=%f\n\n ",jmin, ijmin, jmax, ijmax, jmean);
1.227 brouard 8045: }
1.126 brouard 8046:
8047: /*********** Tricode ****************************/
1.220 brouard 8048: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 8049: {
8050: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
8051: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
8052: * Boring subroutine which should only output nbcode[Tvar[j]][k]
8053: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
8054: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
8055: */
1.130 brouard 8056:
1.242 brouard 8057: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
8058: int modmaxcovj=0; /* Modality max of covariates j */
8059: int cptcode=0; /* Modality max of covariates j */
8060: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 8061:
8062:
1.242 brouard 8063: /* cptcoveff=0; */
8064: /* *cptcov=0; */
1.126 brouard 8065:
1.242 brouard 8066: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 8067: for (k=1; k <= maxncov; k++)
8068: for(j=1; j<=2; j++)
8069: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 8070:
1.242 brouard 8071: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 8072: for (k=1; k<=cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.242 brouard 8073: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 8074: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 8075: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 3 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 8076: switch(Fixed[k]) {
8077: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 8078: modmaxcovj=0;
8079: modmincovj=0;
1.242 brouard 8080: for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/
1.339 brouard 8081: /* printf("Waiting for error tricode Tvar[%d]=%d i=%d (int)(covar[Tvar[k]][i]=%d\n",k,Tvar[k], i, (int)(covar[Tvar[k]][i])); */
1.242 brouard 8082: ij=(int)(covar[Tvar[k]][i]);
8083: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
8084: * If product of Vn*Vm, still boolean *:
8085: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
8086: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
8087: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
8088: modality of the nth covariate of individual i. */
8089: if (ij > modmaxcovj)
8090: modmaxcovj=ij;
8091: else if (ij < modmincovj)
8092: modmincovj=ij;
1.287 brouard 8093: if (ij <0 || ij >1 ){
1.311 brouard 8094: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
8095: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
8096: fflush(ficlog);
8097: exit(1);
1.287 brouard 8098: }
8099: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 8100: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
8101: exit(1);
8102: }else
8103: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
8104: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
8105: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
8106: /* getting the maximum value of the modality of the covariate
8107: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
8108: female ies 1, then modmaxcovj=1.
8109: */
8110: } /* end for loop on individuals i */
8111: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
8112: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
8113: cptcode=modmaxcovj;
8114: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
8115: /*for (i=0; i<=cptcode; i++) {*/
8116: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
8117: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
8118: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
8119: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
8120: if( j != -1){
8121: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
8122: covariate for which somebody answered excluding
8123: undefined. Usually 2: 0 and 1. */
8124: }
8125: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
8126: covariate for which somebody answered including
8127: undefined. Usually 3: -1, 0 and 1. */
8128: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
8129: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
8130: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 8131:
1.242 brouard 8132: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
8133: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
8134: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
8135: /* modmincovj=3; modmaxcovj = 7; */
8136: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
8137: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
8138: /* defining two dummy variables: variables V1_1 and V1_2.*/
8139: /* nbcode[Tvar[j]][ij]=k; */
8140: /* nbcode[Tvar[j]][1]=0; */
8141: /* nbcode[Tvar[j]][2]=1; */
8142: /* nbcode[Tvar[j]][3]=2; */
8143: /* To be continued (not working yet). */
8144: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 8145:
8146: /* for (i=modmincovj; i<=modmaxcovj; i++) { */ /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
8147: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
8148: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
8149: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
8150: /*, could be restored in the future */
8151: for (i=0; i<=1; i++) { /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
1.242 brouard 8152: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
8153: break;
8154: }
8155: ij++;
1.287 brouard 8156: nbcode[Tvar[k]][ij]=i; /* stores the original value of modality i in an array nbcode, ij modality from 1 to last non-nul modality. nbcode[1][1]=0 nbcode[1][2]=1 . Could be -1*/
1.242 brouard 8157: cptcode = ij; /* New max modality for covar j */
8158: } /* end of loop on modality i=-1 to 1 or more */
8159: break;
8160: case 1: /* Testing on varying covariate, could be simple and
8161: * should look at waves or product of fixed *
8162: * varying. No time to test -1, assuming 0 and 1 only */
8163: ij=0;
8164: for(i=0; i<=1;i++){
8165: nbcode[Tvar[k]][++ij]=i;
8166: }
8167: break;
8168: default:
8169: break;
8170: } /* end switch */
8171: } /* end dummy test */
1.349 brouard 8172: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 8173: for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/
1.335 brouard 8174: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
8175: printf("Error k=%d \n",k);
8176: exit(1);
8177: }
1.311 brouard 8178: if(isnan(covar[Tvar[k]][i])){
8179: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
8180: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
8181: fflush(ficlog);
8182: exit(1);
8183: }
8184: }
1.335 brouard 8185: } /* end Quanti */
1.287 brouard 8186: } /* end of loop on model-covariate k. nbcode[Tvark][1]=-1, nbcode[Tvark][1]=0 and nbcode[Tvark][2]=1 sets the value of covariate k*/
1.242 brouard 8187:
8188: for (k=-1; k< maxncov; k++) Ndum[k]=0;
8189: /* Look at fixed dummy (single or product) covariates to check empty modalities */
8190: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
8191: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
8192: ij=Tvar[i]; /* Tvar 5,4,3,6,5,7,1,4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V4*age */
8193: Ndum[ij]++; /* Count the # of 1, 2 etc: {1,1,1,2,2,1,1} because V1 once, V2 once, two V4 and V5 in above */
8194: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
8195: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
8196:
8197: ij=0;
8198: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
1.335 brouard 8199: for (k=1; k<= cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
8200: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 8201: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
8202: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 8203: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
8204: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
8205: /* Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product*/
1.242 brouard 8206: /* If product not in single variable we don't print results */
8207: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 8208: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
8209: /* k= 1 2 3 4 5 6 7 8 9 */
8210: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
8211: /* ij 1 2 3 */
8212: /* Tvaraff[ij]= 4 3 1 */
8213: /* Tmodelind[ij]=2 3 9 */
8214: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 8215: Tvaraff[ij]=Tvar[k]; /* For printing combination *//* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, Tvar {5, 4, 3, 6, 5, 2, 7, 1, 1} Tvaraff={4, 3, 1} V4, V3, V1*/
8216: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
8217: TmodelInvind[ij]=Tvar[k]- ncovcol-nqv; /* Inverse TmodelInvind[2=V4]=2 second dummy varying cov (V4)4-1-1 {0, 2, 1, } TmodelInvind[3]=1 */
8218: if(Fixed[k]!=0)
8219: anyvaryingduminmodel=1;
8220: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
8221: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
8222: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
8223: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
8224: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
8225: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
8226: }
8227: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
8228: /* ij--; */
8229: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 8230: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 8231: * because they can be excluded from the model and real
8232: * if in the model but excluded because missing values, but how to get k from ij?*/
8233: for(j=ij+1; j<= cptcovt; j++){
8234: Tvaraff[j]=0;
8235: Tmodelind[j]=0;
8236: }
8237: for(j=ntveff+1; j<= cptcovt; j++){
8238: TmodelInvind[j]=0;
8239: }
8240: /* To be sorted */
8241: ;
8242: }
1.126 brouard 8243:
1.145 brouard 8244:
1.126 brouard 8245: /*********** Health Expectancies ****************/
8246:
1.235 brouard 8247: void evsij(double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int cij, int estepm,char strstart[], int nres )
1.126 brouard 8248:
8249: {
8250: /* Health expectancies, no variances */
1.329 brouard 8251: /* cij is the combination in the list of combination of dummy covariates */
8252: /* strstart is a string of time at start of computing */
1.164 brouard 8253: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 8254: int nhstepma, nstepma; /* Decreasing with age */
8255: double age, agelim, hf;
8256: double ***p3mat;
8257: double eip;
8258:
1.238 brouard 8259: /* pstamp(ficreseij); */
1.126 brouard 8260: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
8261: fprintf(ficreseij,"# Age");
8262: for(i=1; i<=nlstate;i++){
8263: for(j=1; j<=nlstate;j++){
8264: fprintf(ficreseij," e%1d%1d ",i,j);
8265: }
8266: fprintf(ficreseij," e%1d. ",i);
8267: }
8268: fprintf(ficreseij,"\n");
8269:
8270:
8271: if(estepm < stepm){
8272: printf ("Problem %d lower than %d\n",estepm, stepm);
8273: }
8274: else hstepm=estepm;
8275: /* We compute the life expectancy from trapezoids spaced every estepm months
8276: * This is mainly to measure the difference between two models: for example
8277: * if stepm=24 months pijx are given only every 2 years and by summing them
8278: * we are calculating an estimate of the Life Expectancy assuming a linear
8279: * progression in between and thus overestimating or underestimating according
8280: * to the curvature of the survival function. If, for the same date, we
8281: * estimate the model with stepm=1 month, we can keep estepm to 24 months
8282: * to compare the new estimate of Life expectancy with the same linear
8283: * hypothesis. A more precise result, taking into account a more precise
8284: * curvature will be obtained if estepm is as small as stepm. */
8285:
8286: /* For example we decided to compute the life expectancy with the smallest unit */
8287: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8288: nhstepm is the number of hstepm from age to agelim
8289: nstepm is the number of stepm from age to agelin.
1.270 brouard 8290: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 8291: and note for a fixed period like estepm months */
8292: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
8293: survival function given by stepm (the optimization length). Unfortunately it
8294: means that if the survival funtion is printed only each two years of age and if
8295: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8296: results. So we changed our mind and took the option of the best precision.
8297: */
8298: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8299:
8300: agelim=AGESUP;
8301: /* If stepm=6 months */
8302: /* Computed by stepm unit matrices, product of hstepm matrices, stored
8303: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
8304:
8305: /* nhstepm age range expressed in number of stepm */
8306: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8307: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8308: /* if (stepm >= YEARM) hstepm=1;*/
8309: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8310: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8311:
8312: for (age=bage; age<=fage; age ++){
8313: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8314: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8315: /* if (stepm >= YEARM) hstepm=1;*/
8316: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
8317:
8318: /* If stepm=6 months */
8319: /* Computed by stepm unit matrices, product of hstepma matrices, stored
8320: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 8321: /* printf("HELLO evsij Entering hpxij age=%d cij=%d hstepm=%d x[1]=%f nres=%d\n",(int) age, cij, hstepm, x[1], nres); */
1.235 brouard 8322: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 8323:
8324: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
8325:
8326: printf("%d|",(int)age);fflush(stdout);
8327: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
8328:
8329: /* Computing expectancies */
8330: for(i=1; i<=nlstate;i++)
8331: for(j=1; j<=nlstate;j++)
8332: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
8333: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
8334:
8335: /* if((int)age==70)printf("i=%2d,j=%2d,h=%2d,age=%3d,%9.4f,%9.4f,%9.4f\n",i,j,h,(int)age,p3mat[i][j][h],hf,eij[i][j][(int)age]);*/
8336:
8337: }
8338:
8339: fprintf(ficreseij,"%3.0f",age );
8340: for(i=1; i<=nlstate;i++){
8341: eip=0;
8342: for(j=1; j<=nlstate;j++){
8343: eip +=eij[i][j][(int)age];
8344: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
8345: }
8346: fprintf(ficreseij,"%9.4f", eip );
8347: }
8348: fprintf(ficreseij,"\n");
8349:
8350: }
8351: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8352: printf("\n");
8353: fprintf(ficlog,"\n");
8354:
8355: }
8356:
1.235 brouard 8357: void cvevsij(double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int cij, int estepm,double delti[],double **matcov,char strstart[], int nres )
1.126 brouard 8358:
8359: {
8360: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 8361: to initial status i, ei. .
1.126 brouard 8362: */
1.336 brouard 8363: /* Very time consuming function, but already optimized with precov */
1.126 brouard 8364: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
8365: int nhstepma, nstepma; /* Decreasing with age */
8366: double age, agelim, hf;
8367: double ***p3matp, ***p3matm, ***varhe;
8368: double **dnewm,**doldm;
8369: double *xp, *xm;
8370: double **gp, **gm;
8371: double ***gradg, ***trgradg;
8372: int theta;
8373:
8374: double eip, vip;
8375:
8376: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
8377: xp=vector(1,npar);
8378: xm=vector(1,npar);
8379: dnewm=matrix(1,nlstate*nlstate,1,npar);
8380: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
8381:
8382: pstamp(ficresstdeij);
8383: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
8384: fprintf(ficresstdeij,"# Age");
8385: for(i=1; i<=nlstate;i++){
8386: for(j=1; j<=nlstate;j++)
8387: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
8388: fprintf(ficresstdeij," e%1d. ",i);
8389: }
8390: fprintf(ficresstdeij,"\n");
8391:
8392: pstamp(ficrescveij);
8393: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
8394: fprintf(ficrescveij,"# Age");
8395: for(i=1; i<=nlstate;i++)
8396: for(j=1; j<=nlstate;j++){
8397: cptj= (j-1)*nlstate+i;
8398: for(i2=1; i2<=nlstate;i2++)
8399: for(j2=1; j2<=nlstate;j2++){
8400: cptj2= (j2-1)*nlstate+i2;
8401: if(cptj2 <= cptj)
8402: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
8403: }
8404: }
8405: fprintf(ficrescveij,"\n");
8406:
8407: if(estepm < stepm){
8408: printf ("Problem %d lower than %d\n",estepm, stepm);
8409: }
8410: else hstepm=estepm;
8411: /* We compute the life expectancy from trapezoids spaced every estepm months
8412: * This is mainly to measure the difference between two models: for example
8413: * if stepm=24 months pijx are given only every 2 years and by summing them
8414: * we are calculating an estimate of the Life Expectancy assuming a linear
8415: * progression in between and thus overestimating or underestimating according
8416: * to the curvature of the survival function. If, for the same date, we
8417: * estimate the model with stepm=1 month, we can keep estepm to 24 months
8418: * to compare the new estimate of Life expectancy with the same linear
8419: * hypothesis. A more precise result, taking into account a more precise
8420: * curvature will be obtained if estepm is as small as stepm. */
8421:
8422: /* For example we decided to compute the life expectancy with the smallest unit */
8423: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8424: nhstepm is the number of hstepm from age to agelim
8425: nstepm is the number of stepm from age to agelin.
8426: Look at hpijx to understand the reason of that which relies in memory size
8427: and note for a fixed period like estepm months */
8428: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
8429: survival function given by stepm (the optimization length). Unfortunately it
8430: means that if the survival funtion is printed only each two years of age and if
8431: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8432: results. So we changed our mind and took the option of the best precision.
8433: */
8434: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8435:
8436: /* If stepm=6 months */
8437: /* nhstepm age range expressed in number of stepm */
8438: agelim=AGESUP;
8439: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
8440: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8441: /* if (stepm >= YEARM) hstepm=1;*/
8442: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8443:
8444: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8445: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8446: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
8447: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
8448: gp=matrix(0,nhstepm,1,nlstate*nlstate);
8449: gm=matrix(0,nhstepm,1,nlstate*nlstate);
8450:
8451: for (age=bage; age<=fage; age ++){
8452: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8453: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8454: /* if (stepm >= YEARM) hstepm=1;*/
8455: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 8456:
1.126 brouard 8457: /* If stepm=6 months */
8458: /* Computed by stepm unit matrices, product of hstepma matrices, stored
8459: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
8460:
8461: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 8462:
1.126 brouard 8463: /* Computing Variances of health expectancies */
8464: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
8465: decrease memory allocation */
8466: for(theta=1; theta <=npar; theta++){
8467: for(i=1; i<=npar; i++){
1.222 brouard 8468: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8469: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 8470: }
1.235 brouard 8471: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
8472: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 8473:
1.126 brouard 8474: for(j=1; j<= nlstate; j++){
1.222 brouard 8475: for(i=1; i<=nlstate; i++){
8476: for(h=0; h<=nhstepm-1; h++){
8477: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
8478: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
8479: }
8480: }
1.126 brouard 8481: }
1.218 brouard 8482:
1.126 brouard 8483: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 8484: for(h=0; h<=nhstepm-1; h++){
8485: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
8486: }
1.126 brouard 8487: }/* End theta */
8488:
8489:
8490: for(h=0; h<=nhstepm-1; h++)
8491: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 8492: for(theta=1; theta <=npar; theta++)
8493: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 8494:
1.218 brouard 8495:
1.222 brouard 8496: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 8497: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 8498: varhe[ij][ji][(int)age] =0.;
1.218 brouard 8499:
1.222 brouard 8500: printf("%d|",(int)age);fflush(stdout);
8501: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
8502: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 8503: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 8504: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
8505: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
8506: for(ij=1;ij<=nlstate*nlstate;ij++)
8507: for(ji=1;ji<=nlstate*nlstate;ji++)
8508: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 8509: }
8510: }
1.320 brouard 8511: /* if((int)age ==50){ */
8512: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
8513: /* } */
1.126 brouard 8514: /* Computing expectancies */
1.235 brouard 8515: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 8516: for(i=1; i<=nlstate;i++)
8517: for(j=1; j<=nlstate;j++)
1.222 brouard 8518: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
8519: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 8520:
1.222 brouard 8521: /* if((int)age==70)printf("i=%2d,j=%2d,h=%2d,age=%3d,%9.4f,%9.4f,%9.4f\n",i,j,h,(int)age,p3mat[i][j][h],hf,eij[i][j][(int)age]);*/
1.218 brouard 8522:
1.222 brouard 8523: }
1.269 brouard 8524:
8525: /* Standard deviation of expectancies ij */
1.126 brouard 8526: fprintf(ficresstdeij,"%3.0f",age );
8527: for(i=1; i<=nlstate;i++){
8528: eip=0.;
8529: vip=0.;
8530: for(j=1; j<=nlstate;j++){
1.222 brouard 8531: eip += eij[i][j][(int)age];
8532: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
8533: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
8534: fprintf(ficresstdeij," %9.4f (%.4f)", eij[i][j][(int)age], sqrt(varhe[(j-1)*nlstate+i][(j-1)*nlstate+i][(int)age]) );
1.126 brouard 8535: }
8536: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
8537: }
8538: fprintf(ficresstdeij,"\n");
1.218 brouard 8539:
1.269 brouard 8540: /* Variance of expectancies ij */
1.126 brouard 8541: fprintf(ficrescveij,"%3.0f",age );
8542: for(i=1; i<=nlstate;i++)
8543: for(j=1; j<=nlstate;j++){
1.222 brouard 8544: cptj= (j-1)*nlstate+i;
8545: for(i2=1; i2<=nlstate;i2++)
8546: for(j2=1; j2<=nlstate;j2++){
8547: cptj2= (j2-1)*nlstate+i2;
8548: if(cptj2 <= cptj)
8549: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
8550: }
1.126 brouard 8551: }
8552: fprintf(ficrescveij,"\n");
1.218 brouard 8553:
1.126 brouard 8554: }
8555: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
8556: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
8557: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
8558: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
8559: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8560: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8561: printf("\n");
8562: fprintf(ficlog,"\n");
1.218 brouard 8563:
1.126 brouard 8564: free_vector(xm,1,npar);
8565: free_vector(xp,1,npar);
8566: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
8567: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
8568: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
8569: }
1.218 brouard 8570:
1.126 brouard 8571: /************ Variance ******************/
1.235 brouard 8572: void varevsij(char optionfilefiname[], double ***vareij, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int *ncvyearp, int ij, int estepm, int cptcov, int cptcod, int popbased, int mobilav, char strstart[], int nres)
1.218 brouard 8573: {
1.361 ! brouard 8574: /** Computes the matrix of variance covariance of health expectancies e.j= sum_i w_i e_ij where w_i depends of popbased,
! 8575: * either cross-sectional or implied.
! 8576: * return vareij[i][j][(int)age]=cov(e.i,e.j)=sum_h sum_k trgrad(h_p.i) V(theta) grad(k_p.k) Equation 20
1.279 brouard 8577: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
8578: * double **newm;
8579: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
8580: */
1.218 brouard 8581:
8582: /* int movingaverage(); */
8583: double **dnewm,**doldm;
8584: double **dnewmp,**doldmp;
8585: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 8586: int first=0;
1.218 brouard 8587: int k;
8588: double *xp;
1.279 brouard 8589: double **gp, **gm; /**< for var eij */
8590: double ***gradg, ***trgradg; /**< for var eij */
8591: double **gradgp, **trgradgp; /**< for var p point j */
8592: double *gpp, *gmp; /**< for var p point j */
1.361 ! brouard 8593: double **varppt; /**< for var e.. nlstate+1 to nlstate+ndeath */
1.218 brouard 8594: double ***p3mat;
8595: double age,agelim, hf;
8596: /* double ***mobaverage; */
8597: int theta;
8598: char digit[4];
8599: char digitp[25];
8600:
8601: char fileresprobmorprev[FILENAMELENGTH];
8602:
8603: if(popbased==1){
8604: if(mobilav!=0)
8605: strcpy(digitp,"-POPULBASED-MOBILAV_");
8606: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
8607: }
8608: else
8609: strcpy(digitp,"-STABLBASED_");
1.126 brouard 8610:
1.218 brouard 8611: /* if (mobilav!=0) { */
8612: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8613: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
8614: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
8615: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
8616: /* } */
8617: /* } */
8618:
8619: strcpy(fileresprobmorprev,"PRMORPREV-");
8620: sprintf(digit,"%-d",ij);
8621: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
8622: strcat(fileresprobmorprev,digit); /* Tvar to be done */
8623: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
8624: strcat(fileresprobmorprev,fileresu);
8625: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
8626: printf("Problem with resultfile: %s\n", fileresprobmorprev);
8627: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
8628: }
8629: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
8630: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
8631: pstamp(ficresprobmorprev);
8632: fprintf(ficresprobmorprev,"# probabilities of dying before estepm=%d months for people of exact age and weighted probabilities w1*p1j+w2*p2j+... stand dev in()\n",estepm);
1.238 brouard 8633: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 8634:
8635: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
8636: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
8637: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
8638: /* } */
8639: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 8640: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 8641: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 8642: }
1.337 brouard 8643: /* for(j=1;j<=cptcoveff;j++) */
8644: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 8645: fprintf(ficresprobmorprev,"\n");
8646:
1.218 brouard 8647: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
8648: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
8649: fprintf(ficresprobmorprev," p.%-d SE",j);
8650: for(i=1; i<=nlstate;i++)
8651: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
8652: }
8653: fprintf(ficresprobmorprev,"\n");
8654:
8655: fprintf(ficgp,"\n# Routine varevsij");
8656: fprintf(ficgp,"\nunset title \n");
8657: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
8658: fprintf(fichtm,"\n<li><h4> Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)</h4></li>\n");
8659: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 8660:
1.361 ! brouard 8661: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); /* In fact, currently a double */
1.218 brouard 8662: pstamp(ficresvij);
8663: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
8664: if(popbased==1)
8665: fprintf(ficresvij,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally\n in each health state (popbased=1) (mobilav=%d\n",mobilav);
8666: else
8667: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
8668: fprintf(ficresvij,"# Age");
8669: for(i=1; i<=nlstate;i++)
8670: for(j=1; j<=nlstate;j++)
8671: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
8672: fprintf(ficresvij,"\n");
8673:
8674: xp=vector(1,npar);
8675: dnewm=matrix(1,nlstate,1,npar);
8676: doldm=matrix(1,nlstate,1,nlstate);
8677: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
8678: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8679:
8680: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
8681: gpp=vector(nlstate+1,nlstate+ndeath);
8682: gmp=vector(nlstate+1,nlstate+ndeath);
8683: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 8684:
1.218 brouard 8685: if(estepm < stepm){
8686: printf ("Problem %d lower than %d\n",estepm, stepm);
8687: }
8688: else hstepm=estepm;
8689: /* For example we decided to compute the life expectancy with the smallest unit */
8690: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8691: nhstepm is the number of hstepm from age to agelim
8692: nstepm is the number of stepm from age to agelim.
8693: Look at function hpijx to understand why because of memory size limitations,
8694: we decided (b) to get a life expectancy respecting the most precise curvature of the
8695: survival function given by stepm (the optimization length). Unfortunately it
8696: means that if the survival funtion is printed every two years of age and if
8697: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8698: results. So we changed our mind and took the option of the best precision.
8699: */
8700: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8701: agelim = AGESUP;
8702: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
8703: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
8704: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8705: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8706: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
8707: gp=matrix(0,nhstepm,1,nlstate);
8708: gm=matrix(0,nhstepm,1,nlstate);
8709:
8710:
8711: for(theta=1; theta <=npar; theta++){
8712: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
8713: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8714: }
1.279 brouard 8715: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
8716: * returns into prlim .
1.288 brouard 8717: */
1.242 brouard 8718: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 8719:
8720: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 8721: if (popbased==1) {
8722: if(mobilav ==0){
8723: for(i=1; i<=nlstate;i++)
8724: prlim[i][i]=probs[(int)age][i][ij];
8725: }else{ /* mobilav */
8726: for(i=1; i<=nlstate;i++)
8727: prlim[i][i]=mobaverage[(int)age][i][ij];
8728: }
8729: }
1.361 ! brouard 8730: /**< Computes the shifted plus (gp) transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 8731: */
8732: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
1.292 brouard 8733: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}x\f$, which are the probability
1.279 brouard 8734: * at horizon h in state j including mortality.
8735: */
1.218 brouard 8736: for(j=1; j<= nlstate; j++){
8737: for(h=0; h<=nhstepm; h++){
8738: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
1.361 ! brouard 8739: gp[h][j] += prlim[i][i]*p3mat[i][j][h]; /* gp[h][j]= w_i h_pij */
1.218 brouard 8740: }
8741: }
1.279 brouard 8742: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 8743: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 8744: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 8745: */
1.361 ! brouard 8746: for(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once for theta plus p.3(age) Sum_i wi pi3*/
1.218 brouard 8747: for(i=1,gpp[j]=0.; i<= nlstate; i++)
8748: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 8749: }
8750:
8751: /* Again with minus shift */
1.218 brouard 8752:
8753: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
8754: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 8755:
1.242 brouard 8756: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 8757:
8758: if (popbased==1) {
8759: if(mobilav ==0){
8760: for(i=1; i<=nlstate;i++)
8761: prlim[i][i]=probs[(int)age][i][ij];
8762: }else{ /* mobilav */
8763: for(i=1; i<=nlstate;i++)
8764: prlim[i][i]=mobaverage[(int)age][i][ij];
8765: }
8766: }
8767:
1.361 ! brouard 8768: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Still minus */
1.218 brouard 8769:
1.361 ! brouard 8770: for(j=1; j<= nlstate; j++){ /* gm[h][j]= Sum_i of wi * pij = h_p.j */
1.218 brouard 8771: for(h=0; h<=nhstepm; h++){
8772: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
8773: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
8774: }
8775: }
8776: /* This for computing probability of death (h=1 means
8777: computed over hstepm matrices product = hstepm*stepm months)
1.361 ! brouard 8778: as a weighted average of prlim. j is death. gmp[3]=sum_i w_i*p_i3=p.3 minus theta
1.218 brouard 8779: */
1.361 ! brouard 8780: for(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once theta_minus p.3=Sum_i wi pi3*/
1.218 brouard 8781: for(i=1,gmp[j]=0.; i<= nlstate; i++)
8782: gmp[j] += prlim[i][i]*p3mat[i][j][1];
8783: }
1.279 brouard 8784: /* end shifting computations */
8785:
1.361 ! brouard 8786: /**< Computing gradient of p.j matrix at horizon h and still for one parameter of vector theta
! 8787: * equation 31 and 32
1.279 brouard 8788: */
1.361 ! brouard 8789: for(j=1; j<= nlstate; j++) /* computes grad p.j(x, over each h) where p.j is Sum_i w_i*pij(x over h)
! 8790: * equation 24 */
1.218 brouard 8791: for(h=0; h<=nhstepm; h++){
8792: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
8793: }
1.361 ! brouard 8794: /**< Gradient of overall mortality p.3 (or p.death)
1.279 brouard 8795: */
1.361 ! brouard 8796: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* computes grad of p.3 from wi+pi3 grad p.3 (theta) */
1.218 brouard 8797: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
8798: }
8799:
8800: } /* End theta */
1.279 brouard 8801:
1.361 ! brouard 8802: /* We got the gradient matrix for each theta and each state j of gradg(h]theta][j)=grad(_hp.j(theta) */
! 8803: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar);
1.218 brouard 8804:
1.361 ! brouard 8805: for(h=0; h<=nhstepm; h++) /* veij */ /* computes the transposed of grad (_hp.j(theta)*/
1.218 brouard 8806: for(j=1; j<=nlstate;j++)
8807: for(theta=1; theta <=npar; theta++)
8808: trgradg[h][j][theta]=gradg[h][theta][j];
8809:
1.361 ! brouard 8810: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* computes transposed of grad p.3 (theta)*/
1.218 brouard 8811: for(theta=1; theta <=npar; theta++)
8812: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 8813: /**< as well as its transposed matrix
8814: */
1.218 brouard 8815:
8816: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
8817: for(i=1;i<=nlstate;i++)
8818: for(j=1;j<=nlstate;j++)
8819: vareij[i][j][(int)age] =0.;
1.279 brouard 8820:
8821: /* Computing trgradg by matcov by gradg at age and summing over h
1.361 ! brouard 8822: * and k (nhstepm) formula 32 of article
! 8823: * Lievre-Brouard-Heathcote so that for each j, computes the cov(e.j,e.k) (formula 31).
! 8824: * for given h and k computes trgradg[h](i,j) matcov (theta) gradg(k)(i,j) into vareij[i][j] which is
! 8825: cov(e.i,e.j) and sums on h and k
! 8826: * including the covariances.
1.279 brouard 8827: */
8828:
1.218 brouard 8829: for(h=0;h<=nhstepm;h++){
8830: for(k=0;k<=nhstepm;k++){
8831: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
8832: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
8833: for(i=1;i<=nlstate;i++)
8834: for(j=1;j<=nlstate;j++)
1.361 ! brouard 8835: vareij[i][j][(int)age] += doldm[i][j]*hf*hf; /* This is vareij=sum_h sum_k trgrad(h_pij) V(theta) grad(k_pij)
! 8836: including the covariances of e.j */
1.218 brouard 8837: }
8838: }
8839:
1.361 ! brouard 8840: /* Mortality: pptj is p.3 or p.death = trgradgp by cov by gradgp, variance of
! 8841: * p.3=1-p..=1-sum i p.i overall mortality computed directly because
1.279 brouard 8842: * we compute the grad (wix pijx) instead of grad (pijx),even if
1.361 ! brouard 8843: * wix is independent of theta.
1.279 brouard 8844: */
1.218 brouard 8845: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
8846: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
8847: for(j=nlstate+1;j<=nlstate+ndeath;j++)
8848: for(i=nlstate+1;i<=nlstate+ndeath;i++)
1.361 ! brouard 8849: varppt[j][i]=doldmp[j][i]; /* This is the variance of p.3 */
1.218 brouard 8850: /* end ppptj */
8851: /* x centered again */
8852:
1.242 brouard 8853: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 8854:
8855: if (popbased==1) {
8856: if(mobilav ==0){
8857: for(i=1; i<=nlstate;i++)
8858: prlim[i][i]=probs[(int)age][i][ij];
8859: }else{ /* mobilav */
8860: for(i=1; i<=nlstate;i++)
8861: prlim[i][i]=mobaverage[(int)age][i][ij];
8862: }
8863: }
8864:
8865: /* This for computing probability of death (h=1 means
8866: computed over hstepm (estepm) matrices product = hstepm*stepm months)
8867: as a weighted average of prlim.
8868: */
1.235 brouard 8869: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 8870: for(j=nlstate+1;j<=nlstate+ndeath;j++){
8871: for(i=1,gmp[j]=0.;i<= nlstate; i++)
1.361 ! brouard 8872: gmp[j] += prlim[i][i]*p3mat[i][j][1]; /* gmp[j] is p.3 */
1.218 brouard 8873: }
8874: /* end probability of death */
8875:
8876: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
8877: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
1.361 ! brouard 8878: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));/* p.3 (STD p.3) */
1.218 brouard 8879: for(i=1; i<=nlstate;i++){
1.361 ! brouard 8880: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]); /* wi, pi3 */
1.218 brouard 8881: }
8882: }
8883: fprintf(ficresprobmorprev,"\n");
8884:
8885: fprintf(ficresvij,"%.0f ",age );
8886: for(i=1; i<=nlstate;i++)
8887: for(j=1; j<=nlstate;j++){
8888: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
8889: }
8890: fprintf(ficresvij,"\n");
8891: free_matrix(gp,0,nhstepm,1,nlstate);
8892: free_matrix(gm,0,nhstepm,1,nlstate);
8893: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
8894: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
8895: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8896: } /* End age */
8897: free_vector(gpp,nlstate+1,nlstate+ndeath);
8898: free_vector(gmp,nlstate+1,nlstate+ndeath);
8899: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
8900: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
8901: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
8902: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
8903: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
8904: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
8905: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
8906: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
8907: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
8908: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
8909: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
8910: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
8911: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
8912: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
8913: fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months. <br> <img src=\"%s%s.svg\"> <br>\n", estepm,subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
8914: /* fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months and then divided by estepm and multiplied by %.0f in order to have the probability to die over a year <br> <img src=\"varmuptjgr%s%s.svg\"> <br>\n", stepm,YEARM,digitp,digit);
1.126 brouard 8915: */
1.218 brouard 8916: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
8917: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 8918:
1.218 brouard 8919: free_vector(xp,1,npar);
8920: free_matrix(doldm,1,nlstate,1,nlstate);
8921: free_matrix(dnewm,1,nlstate,1,npar);
8922: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8923: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
8924: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8925: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8926: fclose(ficresprobmorprev);
8927: fflush(ficgp);
8928: fflush(fichtm);
8929: } /* end varevsij */
1.126 brouard 8930:
8931: /************ Variance of prevlim ******************/
1.269 brouard 8932: void varprevlim(char fileresvpl[], FILE *ficresvpl, double **varpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int *ncvyearp, int ij, char strstart[], int nres)
1.126 brouard 8933: {
1.205 brouard 8934: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 8935: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 8936:
1.268 brouard 8937: double **dnewmpar,**doldm;
1.126 brouard 8938: int i, j, nhstepm, hstepm;
8939: double *xp;
8940: double *gp, *gm;
8941: double **gradg, **trgradg;
1.208 brouard 8942: double **mgm, **mgp;
1.126 brouard 8943: double age,agelim;
8944: int theta;
8945:
8946: pstamp(ficresvpl);
1.288 brouard 8947: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 8948: fprintf(ficresvpl,"# Age ");
8949: if(nresult >=1)
8950: fprintf(ficresvpl," Result# ");
1.126 brouard 8951: for(i=1; i<=nlstate;i++)
8952: fprintf(ficresvpl," %1d-%1d",i,i);
8953: fprintf(ficresvpl,"\n");
8954:
8955: xp=vector(1,npar);
1.268 brouard 8956: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 8957: doldm=matrix(1,nlstate,1,nlstate);
8958:
8959: hstepm=1*YEARM; /* Every year of age */
8960: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
8961: agelim = AGESUP;
8962: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
8963: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
8964: if (stepm >= YEARM) hstepm=1;
8965: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
8966: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 8967: mgp=matrix(1,npar,1,nlstate);
8968: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 8969: gp=vector(1,nlstate);
8970: gm=vector(1,nlstate);
8971:
8972: for(theta=1; theta <=npar; theta++){
8973: for(i=1; i<=npar; i++){ /* Computes gradient */
8974: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8975: }
1.288 brouard 8976: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
8977: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
8978: /* else */
8979: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 8980: for(i=1;i<=nlstate;i++){
1.126 brouard 8981: gp[i] = prlim[i][i];
1.208 brouard 8982: mgp[theta][i] = prlim[i][i];
8983: }
1.126 brouard 8984: for(i=1; i<=npar; i++) /* Computes gradient */
8985: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 8986: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
8987: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
8988: /* else */
8989: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 8990: for(i=1;i<=nlstate;i++){
1.126 brouard 8991: gm[i] = prlim[i][i];
1.208 brouard 8992: mgm[theta][i] = prlim[i][i];
8993: }
1.126 brouard 8994: for(i=1;i<=nlstate;i++)
8995: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 8996: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 8997: } /* End theta */
8998:
8999: trgradg =matrix(1,nlstate,1,npar);
9000:
9001: for(j=1; j<=nlstate;j++)
9002: for(theta=1; theta <=npar; theta++)
9003: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 9004: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9005: /* printf("\nmgm mgp %d ",(int)age); */
9006: /* for(j=1; j<=nlstate;j++){ */
9007: /* printf(" %d ",j); */
9008: /* for(theta=1; theta <=npar; theta++) */
9009: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
9010: /* printf("\n "); */
9011: /* } */
9012: /* } */
9013: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9014: /* printf("\n gradg %d ",(int)age); */
9015: /* for(j=1; j<=nlstate;j++){ */
9016: /* printf("%d ",j); */
9017: /* for(theta=1; theta <=npar; theta++) */
9018: /* printf("%d %lf ",theta,gradg[theta][j]); */
9019: /* printf("\n "); */
9020: /* } */
9021: /* } */
1.126 brouard 9022:
9023: for(i=1;i<=nlstate;i++)
9024: varpl[i][(int)age] =0.;
1.209 brouard 9025: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 9026: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9027: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 9028: }else{
1.268 brouard 9029: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9030: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 9031: }
1.126 brouard 9032: for(i=1;i<=nlstate;i++)
9033: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
9034:
9035: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 9036: if(nresult >=1)
9037: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 9038: for(i=1; i<=nlstate;i++){
1.126 brouard 9039: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 9040: /* for(j=1;j<=nlstate;j++) */
9041: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
9042: }
1.126 brouard 9043: fprintf(ficresvpl,"\n");
9044: free_vector(gp,1,nlstate);
9045: free_vector(gm,1,nlstate);
1.208 brouard 9046: free_matrix(mgm,1,npar,1,nlstate);
9047: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 9048: free_matrix(gradg,1,npar,1,nlstate);
9049: free_matrix(trgradg,1,nlstate,1,npar);
9050: } /* End age */
9051:
9052: free_vector(xp,1,npar);
9053: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 9054: free_matrix(dnewmpar,1,nlstate,1,nlstate);
9055:
9056: }
9057:
9058:
9059: /************ Variance of backprevalence limit ******************/
1.269 brouard 9060: void varbrevlim(char fileresvbl[], FILE *ficresvbl, double **varbpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **bprlim, double ftolpl, int mobilavproj, int *ncvyearp, int ij, char strstart[], int nres)
1.268 brouard 9061: {
9062: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
9063: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
9064:
9065: double **dnewmpar,**doldm;
9066: int i, j, nhstepm, hstepm;
9067: double *xp;
9068: double *gp, *gm;
9069: double **gradg, **trgradg;
9070: double **mgm, **mgp;
9071: double age,agelim;
9072: int theta;
9073:
9074: pstamp(ficresvbl);
9075: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
9076: fprintf(ficresvbl,"# Age ");
9077: if(nresult >=1)
9078: fprintf(ficresvbl," Result# ");
9079: for(i=1; i<=nlstate;i++)
9080: fprintf(ficresvbl," %1d-%1d",i,i);
9081: fprintf(ficresvbl,"\n");
9082:
9083: xp=vector(1,npar);
9084: dnewmpar=matrix(1,nlstate,1,npar);
9085: doldm=matrix(1,nlstate,1,nlstate);
9086:
9087: hstepm=1*YEARM; /* Every year of age */
9088: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
9089: agelim = AGEINF;
9090: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
9091: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
9092: if (stepm >= YEARM) hstepm=1;
9093: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
9094: gradg=matrix(1,npar,1,nlstate);
9095: mgp=matrix(1,npar,1,nlstate);
9096: mgm=matrix(1,npar,1,nlstate);
9097: gp=vector(1,nlstate);
9098: gm=vector(1,nlstate);
9099:
9100: for(theta=1; theta <=npar; theta++){
9101: for(i=1; i<=npar; i++){ /* Computes gradient */
9102: xp[i] = x[i] + (i==theta ?delti[theta]:0);
9103: }
9104: if(mobilavproj > 0 )
9105: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9106: else
9107: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9108: for(i=1;i<=nlstate;i++){
9109: gp[i] = bprlim[i][i];
9110: mgp[theta][i] = bprlim[i][i];
9111: }
9112: for(i=1; i<=npar; i++) /* Computes gradient */
9113: xp[i] = x[i] - (i==theta ?delti[theta]:0);
9114: if(mobilavproj > 0 )
9115: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9116: else
9117: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9118: for(i=1;i<=nlstate;i++){
9119: gm[i] = bprlim[i][i];
9120: mgm[theta][i] = bprlim[i][i];
9121: }
9122: for(i=1;i<=nlstate;i++)
9123: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
9124: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
9125: } /* End theta */
9126:
9127: trgradg =matrix(1,nlstate,1,npar);
9128:
9129: for(j=1; j<=nlstate;j++)
9130: for(theta=1; theta <=npar; theta++)
9131: trgradg[j][theta]=gradg[theta][j];
9132: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9133: /* printf("\nmgm mgp %d ",(int)age); */
9134: /* for(j=1; j<=nlstate;j++){ */
9135: /* printf(" %d ",j); */
9136: /* for(theta=1; theta <=npar; theta++) */
9137: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
9138: /* printf("\n "); */
9139: /* } */
9140: /* } */
9141: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9142: /* printf("\n gradg %d ",(int)age); */
9143: /* for(j=1; j<=nlstate;j++){ */
9144: /* printf("%d ",j); */
9145: /* for(theta=1; theta <=npar; theta++) */
9146: /* printf("%d %lf ",theta,gradg[theta][j]); */
9147: /* printf("\n "); */
9148: /* } */
9149: /* } */
9150:
9151: for(i=1;i<=nlstate;i++)
9152: varbpl[i][(int)age] =0.;
9153: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
9154: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9155: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
9156: }else{
9157: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9158: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
9159: }
9160: for(i=1;i<=nlstate;i++)
9161: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
9162:
9163: fprintf(ficresvbl,"%.0f ",age );
9164: if(nresult >=1)
9165: fprintf(ficresvbl,"%d ",nres );
9166: for(i=1; i<=nlstate;i++)
9167: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
9168: fprintf(ficresvbl,"\n");
9169: free_vector(gp,1,nlstate);
9170: free_vector(gm,1,nlstate);
9171: free_matrix(mgm,1,npar,1,nlstate);
9172: free_matrix(mgp,1,npar,1,nlstate);
9173: free_matrix(gradg,1,npar,1,nlstate);
9174: free_matrix(trgradg,1,nlstate,1,npar);
9175: } /* End age */
9176:
9177: free_vector(xp,1,npar);
9178: free_matrix(doldm,1,nlstate,1,npar);
9179: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 9180:
9181: }
9182:
9183: /************ Variance of one-step probabilities ******************/
9184: void varprob(char optionfilefiname[], double **matcov, double x[], double delti[], int nlstate, double bage, double fage, int ij, int *Tvar, int **nbcode, int *ncodemax, char strstart[])
1.222 brouard 9185: {
9186: int i, j=0, k1, l1, tj;
9187: int k2, l2, j1, z1;
9188: int k=0, l;
9189: int first=1, first1, first2;
1.326 brouard 9190: int nres=0; /* New */
1.222 brouard 9191: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
9192: double **dnewm,**doldm;
9193: double *xp;
9194: double *gp, *gm;
9195: double **gradg, **trgradg;
9196: double **mu;
9197: double age, cov[NCOVMAX+1];
9198: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
9199: int theta;
9200: char fileresprob[FILENAMELENGTH];
9201: char fileresprobcov[FILENAMELENGTH];
9202: char fileresprobcor[FILENAMELENGTH];
9203: double ***varpij;
9204:
9205: strcpy(fileresprob,"PROB_");
1.356 brouard 9206: strcat(fileresprob,fileresu);
1.222 brouard 9207: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
9208: printf("Problem with resultfile: %s\n", fileresprob);
9209: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
9210: }
9211: strcpy(fileresprobcov,"PROBCOV_");
9212: strcat(fileresprobcov,fileresu);
9213: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
9214: printf("Problem with resultfile: %s\n", fileresprobcov);
9215: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
9216: }
9217: strcpy(fileresprobcor,"PROBCOR_");
9218: strcat(fileresprobcor,fileresu);
9219: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
9220: printf("Problem with resultfile: %s\n", fileresprobcor);
9221: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
9222: }
9223: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
9224: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
9225: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
9226: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
9227: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
9228: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
9229: pstamp(ficresprob);
9230: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
9231: fprintf(ficresprob,"# Age");
9232: pstamp(ficresprobcov);
9233: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
9234: fprintf(ficresprobcov,"# Age");
9235: pstamp(ficresprobcor);
9236: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
9237: fprintf(ficresprobcor,"# Age");
1.126 brouard 9238:
9239:
1.222 brouard 9240: for(i=1; i<=nlstate;i++)
9241: for(j=1; j<=(nlstate+ndeath);j++){
9242: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
9243: fprintf(ficresprobcov," p%1d-%1d ",i,j);
9244: fprintf(ficresprobcor," p%1d-%1d ",i,j);
9245: }
9246: /* fprintf(ficresprob,"\n");
9247: fprintf(ficresprobcov,"\n");
9248: fprintf(ficresprobcor,"\n");
9249: */
9250: xp=vector(1,npar);
9251: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
9252: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
9253: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
9254: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
9255: first=1;
9256: fprintf(ficgp,"\n# Routine varprob");
9257: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
9258: fprintf(fichtm,"\n");
9259:
1.288 brouard 9260: fprintf(fichtm,"\n<li><h4> <a href=\"%s\">Matrix of variance-covariance of one-step probabilities (drawings)</a></h4> this page is important in order to visualize confidence intervals and especially correlation between disability and recovery, or more generally, way in and way back. File %s</li>\n",optionfilehtmcov,optionfilehtmcov);
1.222 brouard 9261: fprintf(fichtmcov,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Matrix of variance-covariance of pairs of step probabilities</h4>\n",optionfilehtmcov, optionfilehtmcov);
9262: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 9263: and drawn. It helps understanding how is the covariance between two incidences.\
9264: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 9265: fprintf(fichtmcov,"\n<br> Contour plot corresponding to x'cov<sup>-1</sup>x = 4 (where x is the column vector (pij,pkl)) are drawn. \
1.126 brouard 9266: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
9267: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
9268: standard deviations wide on each axis. <br>\
9269: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
9270: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
9271: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
9272:
1.222 brouard 9273: cov[1]=1;
9274: /* tj=cptcoveff; */
1.225 brouard 9275: tj = (int) pow(2,cptcoveff);
1.222 brouard 9276: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
9277: j1=0;
1.332 brouard 9278:
9279: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
9280: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 9281: /* printf("Varprob TKresult[nres]=%d j1=%d, nres=%d, cptcovn=%d, cptcoveff=%d tj=%d cptcovs=%d\n", TKresult[nres], j1, nres, cptcovn, cptcoveff, tj, cptcovs); */
1.332 brouard 9282: if(tj != 1 && TKresult[nres]!= j1)
9283: continue;
9284:
9285: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
9286: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
9287: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 9288: if (cptcovn>0) {
1.334 brouard 9289: fprintf(ficresprob, "\n#********** Variable ");
9290: fprintf(ficresprobcov, "\n#********** Variable ");
9291: fprintf(ficgp, "\n#********** Variable ");
9292: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
9293: fprintf(ficresprobcor, "\n#********** Variable ");
9294:
9295: /* Including quantitative variables of the resultline to be done */
9296: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 9297: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 9298: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
9299: /* fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s resultline[%d]=%s \n",nres, z1, modelresult[nres][z1], model, nres, resultline[nres]); */
1.334 brouard 9300: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
9301: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
9302: fprintf(ficresprob,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9303: fprintf(ficresprobcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9304: fprintf(ficgp,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9305: fprintf(fichtmcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9306: fprintf(ficresprobcor,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9307: fprintf(ficresprob,"fixed ");
9308: fprintf(ficresprobcov,"fixed ");
9309: fprintf(ficgp,"fixed ");
9310: fprintf(fichtmcov,"fixed ");
9311: fprintf(ficresprobcor,"fixed ");
9312: }else{
9313: fprintf(ficresprob,"varyi ");
9314: fprintf(ficresprobcov,"varyi ");
9315: fprintf(ficgp,"varyi ");
9316: fprintf(fichtmcov,"varyi ");
9317: fprintf(ficresprobcor,"varyi ");
9318: }
9319: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
9320: /* For each selected (single) quantitative value */
1.337 brouard 9321: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 9322: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
9323: fprintf(ficresprob,"fixed ");
9324: fprintf(ficresprobcov,"fixed ");
9325: fprintf(ficgp,"fixed ");
9326: fprintf(fichtmcov,"fixed ");
9327: fprintf(ficresprobcor,"fixed ");
9328: }else{
9329: fprintf(ficresprob,"varyi ");
9330: fprintf(ficresprobcov,"varyi ");
9331: fprintf(ficgp,"varyi ");
9332: fprintf(fichtmcov,"varyi ");
9333: fprintf(ficresprobcor,"varyi ");
9334: }
9335: }else{
9336: printf("Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff); /* end if dummy or quanti */
9337: fprintf(ficlog,"Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff); /* end if dummy or quanti */
9338: exit(1);
9339: }
9340: } /* End loop on variable of this resultline */
9341: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 9342: fprintf(ficresprob, "**********\n#\n");
9343: fprintf(ficresprobcov, "**********\n#\n");
9344: fprintf(ficgp, "**********\n#\n");
9345: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
9346: fprintf(ficresprobcor, "**********\n#");
9347: if(invalidvarcomb[j1]){
9348: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
9349: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
9350: continue;
9351: }
9352: }
9353: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
9354: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
9355: gp=vector(1,(nlstate)*(nlstate+ndeath));
9356: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 9357: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 9358: cov[2]=age;
9359: if(nagesqr==1)
9360: cov[3]= age*age;
1.334 brouard 9361: /* New code end of combination but for each resultline */
9362: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 9363: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 9364: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 9365: }else{
1.334 brouard 9366: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 9367: }
1.334 brouard 9368: }/* End of loop on model equation */
9369: /* Old code */
9370: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
9371: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
9372: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
9373: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
9374: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
9375: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
9376: /* * 1 1 1 1 1 */
9377: /* * 2 2 1 1 1 */
9378: /* * 3 1 2 1 1 */
9379: /* *\/ */
9380: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
9381: /* } */
9382: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
9383: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
9384: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
9385: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
9386: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
9387: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
9388: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
9389: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
9390: /* printf("Internal IMaCh error, don't know which value for quantitative covariate with age, Tage[k]%d, k=%d, Tvar[Tage[k]]=V%d, age=%d\n",Tage[k],k ,Tvar[Tage[k]], (int)cov[2]); */
9391: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
9392: /* /\* exit(1); *\/ */
9393: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
9394: /* } */
9395: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
9396: /* } */
9397: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
9398: /* if(Dummy[Tvard[k][1]]==0){ */
9399: /* if(Dummy[Tvard[k][2]]==0){ */
9400: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])]; */
9401: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
9402: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
9403: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
9404: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
9405: /* } */
9406: /* }else{ */
9407: /* if(Dummy[Tvard[k][2]]==0){ */
9408: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
9409: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
9410: /* }else{ */
9411: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
9412: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
9413: /* } */
9414: /* } */
9415: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
9416: /* } */
1.326 brouard 9417: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 9418: for(theta=1; theta <=npar; theta++){
9419: for(i=1; i<=npar; i++)
9420: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 9421:
1.222 brouard 9422: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 9423:
1.222 brouard 9424: k=0;
9425: for(i=1; i<= (nlstate); i++){
9426: for(j=1; j<=(nlstate+ndeath);j++){
9427: k=k+1;
9428: gp[k]=pmmij[i][j];
9429: }
9430: }
1.220 brouard 9431:
1.222 brouard 9432: for(i=1; i<=npar; i++)
9433: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 9434:
1.222 brouard 9435: pmij(pmmij,cov,ncovmodel,xp,nlstate);
9436: k=0;
9437: for(i=1; i<=(nlstate); i++){
9438: for(j=1; j<=(nlstate+ndeath);j++){
9439: k=k+1;
9440: gm[k]=pmmij[i][j];
9441: }
9442: }
1.220 brouard 9443:
1.222 brouard 9444: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
9445: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
9446: }
1.126 brouard 9447:
1.222 brouard 9448: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
9449: for(theta=1; theta <=npar; theta++)
9450: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 9451:
1.222 brouard 9452: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
9453: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 9454:
1.222 brouard 9455: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 9456:
1.222 brouard 9457: k=0;
9458: for(i=1; i<=(nlstate); i++){
9459: for(j=1; j<=(nlstate+ndeath);j++){
9460: k=k+1;
9461: mu[k][(int) age]=pmmij[i][j];
9462: }
9463: }
9464: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
9465: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
9466: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 9467:
1.222 brouard 9468: /*printf("\n%d ",(int)age);
9469: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
9470: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
9471: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
9472: }*/
1.220 brouard 9473:
1.222 brouard 9474: fprintf(ficresprob,"\n%d ",(int)age);
9475: fprintf(ficresprobcov,"\n%d ",(int)age);
9476: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 9477:
1.222 brouard 9478: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
9479: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
9480: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
9481: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
9482: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
9483: }
9484: i=0;
9485: for (k=1; k<=(nlstate);k++){
9486: for (l=1; l<=(nlstate+ndeath);l++){
9487: i++;
9488: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
9489: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
9490: for (j=1; j<=i;j++){
9491: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
9492: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
9493: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
9494: }
9495: }
9496: }/* end of loop for state */
9497: } /* end of loop for age */
9498: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
9499: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
9500: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
9501: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
9502:
9503: /* Confidence intervalle of pij */
9504: /*
9505: fprintf(ficgp,"\nunset parametric;unset label");
9506: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
9507: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
9508: fprintf(fichtm,"\n<br>Probability with confidence intervals expressed in year<sup>-1</sup> :<a href=\"pijgr%s.png\">pijgr%s.png</A>, ",optionfilefiname,optionfilefiname);
9509: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
9510: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
9511: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
9512: */
9513:
9514: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
9515: first1=1;first2=2;
9516: for (k2=1; k2<=(nlstate);k2++){
9517: for (l2=1; l2<=(nlstate+ndeath);l2++){
9518: if(l2==k2) continue;
9519: j=(k2-1)*(nlstate+ndeath)+l2;
9520: for (k1=1; k1<=(nlstate);k1++){
9521: for (l1=1; l1<=(nlstate+ndeath);l1++){
9522: if(l1==k1) continue;
9523: i=(k1-1)*(nlstate+ndeath)+l1;
9524: if(i<=j) continue;
9525: for (age=bage; age<=fage; age ++){
9526: if ((int)age %5==0){
9527: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
9528: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
9529: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
9530: mu1=mu[i][(int) age]/stepm*YEARM ;
9531: mu2=mu[j][(int) age]/stepm*YEARM;
9532: c12=cv12/sqrt(v1*v2);
9533: /* Computing eigen value of matrix of covariance */
9534: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
9535: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
9536: if ((lc2 <0) || (lc1 <0) ){
9537: if(first2==1){
9538: first1=0;
9539: printf("Strange: j1=%d One eigen value of 2x2 matrix of covariance is negative, lc1=%11.3e, lc2=%11.3e, v1=%11.3e, v2=%11.3e, cv12=%11.3e.\n It means that the matrix was not well estimated (varpij), for i=%2d, j=%2d, age=%4d .\n See files %s and %s. Probably WRONG RESULTS. See log file for details...\n", j1, lc1, lc2, v1, v2, cv12, i, j, (int)age,fileresprobcov, fileresprobcor);
9540: }
9541: fprintf(ficlog,"Strange: j1=%d One eigen value of 2x2 matrix of covariance is negative, lc1=%11.3e, lc2=%11.3e, v1=%11.3e, v2=%11.3e, cv12=%11.3e.\n It means that the matrix was not well estimated (varpij), for i=%2d, j=%2d, age=%4d .\n See files %s and %s. Probably WRONG RESULTS.\n", j1, lc1, lc2, v1, v2, cv12, i, j, (int)age,fileresprobcov, fileresprobcor);fflush(ficlog);
9542: /* lc1=fabs(lc1); */ /* If we want to have them positive */
9543: /* lc2=fabs(lc2); */
9544: }
1.220 brouard 9545:
1.222 brouard 9546: /* Eigen vectors */
1.280 brouard 9547: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
9548: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
9549: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
9550: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
9551: }else
9552: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 9553: /*v21=sqrt(1.-v11*v11); *//* error */
9554: v21=(lc1-v1)/cv12*v11;
9555: v12=-v21;
9556: v22=v11;
9557: tnalp=v21/v11;
9558: if(first1==1){
9559: first1=0;
9560: printf("%d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tang %.3f\nOthers in log...\n",(int) age,k1,l1,k2,l2,mu1,mu2,v1,v2,c12,cv12,lc1,lc2,v11,v21,tnalp);
9561: }
9562: fprintf(ficlog,"%d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tan %.3f\n",(int) age,k1,l1,k2,l2,mu1,mu2,v1,v2,c12,cv12,lc1,lc2,v11,v21,tnalp);
9563: /*printf(fignu*/
9564: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
9565: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
9566: if(first==1){
9567: first=0;
9568: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
9569: fprintf(ficgp,"\nset parametric;unset label");
9570: fprintf(ficgp,"\nset log y;set log x; set xlabel \"p%1d%1d (year-1)\";set ylabel \"p%1d%1d (year-1)\"",k1,l1,k2,l2);
9571: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 9572: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 9573: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 9574: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 9575: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
9576: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9577: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9578: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
9579: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9580: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
9581: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
9582: fprintf(ficgp,"\nplot [-pi:pi] %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.280 brouard 9583: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
9584: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 9585: }else{
9586: first=0;
9587: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
9588: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
9589: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
9590: fprintf(ficgp,"\nreplot %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.266 brouard 9591: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
9592: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 9593: }/* if first */
9594: } /* age mod 5 */
9595: } /* end loop age */
9596: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9597: first=1;
9598: } /*l12 */
9599: } /* k12 */
9600: } /*l1 */
9601: }/* k1 */
1.332 brouard 9602: } /* loop on combination of covariates j1 */
1.326 brouard 9603: } /* loop on nres */
1.222 brouard 9604: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
9605: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
9606: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
9607: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
9608: free_vector(xp,1,npar);
9609: fclose(ficresprob);
9610: fclose(ficresprobcov);
9611: fclose(ficresprobcor);
9612: fflush(ficgp);
9613: fflush(fichtmcov);
9614: }
1.126 brouard 9615:
9616:
9617: /******************* Printing html file ***********/
1.201 brouard 9618: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9619: int lastpass, int stepm, int weightopt, char model[],\
9620: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 9621: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
9622: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
9623: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.359 brouard 9624: int jj1, k1, cpt, nres;
1.319 brouard 9625: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 9626: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
9627: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
9628: </ul>");
1.319 brouard 9629: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
9630: /* </ul>", model); */
1.214 brouard 9631: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
9632: fprintf(fichtm,"<li>- Observed frequency between two states (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"%s\">%s</a> (html file)<br/>\n",
9633: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 9634: fprintf(fichtm,"<li> - Observed prevalence (cross-sectional prevalence) in each state (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"%s\">%s</a> (html file) ",
1.213 brouard 9635: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
9636: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 9637: fprintf(fichtm,"\
9638: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 9639: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 9640: fprintf(fichtm,"\
1.217 brouard 9641: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
9642: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
9643: fprintf(fichtm,"\
1.288 brouard 9644: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 9645: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 9646: fprintf(fichtm,"\
1.288 brouard 9647: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 9648: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
9649: fprintf(fichtm,"\
1.211 brouard 9650: - (a) Life expectancies by health status at initial age, e<sub>i.</sub> (b) health expectancies by health status at initial age, e<sub>ij</sub> . If one or more covariates are included, specific tables for each value of the covariate are output in sequences within the same file (estepm=%2d months): \
1.126 brouard 9651: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 9652: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 9653: if(prevfcast==1){
9654: fprintf(fichtm,"\
9655: - Prevalence projections by age and states: \
1.201 brouard 9656: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 9657: }
1.126 brouard 9658:
9659:
1.225 brouard 9660: m=pow(2,cptcoveff);
1.222 brouard 9661: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 9662:
1.317 brouard 9663: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 9664:
9665: jj1=0;
9666:
9667: fprintf(fichtm," \n<ul>");
1.337 brouard 9668: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9669: /* k1=nres; */
1.338 brouard 9670: k1=TKresult[nres];
9671: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 9672: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9673: /* if(m != 1 && TKresult[nres]!= k1) */
9674: /* continue; */
1.264 brouard 9675: jj1++;
9676: if (cptcovn > 0) {
9677: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 9678: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9679: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9680: }
1.337 brouard 9681: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
9682: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
9683: /* } */
9684: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9685: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9686: /* } */
1.264 brouard 9687: fprintf(fichtm,"\">");
9688:
9689: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
9690: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 9691: for (cpt=1; cpt<=cptcovs;cpt++){
9692: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9693: }
1.337 brouard 9694: /* fprintf(fichtm,"************ Results for covariates"); */
9695: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
9696: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
9697: /* } */
9698: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9699: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9700: /* } */
1.264 brouard 9701: if(invalidvarcomb[k1]){
9702: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
9703: continue;
9704: }
9705: fprintf(fichtm,"</a></li>");
9706: } /* cptcovn >0 */
9707: }
1.317 brouard 9708: fprintf(fichtm," \n</ul>");
1.264 brouard 9709:
1.222 brouard 9710: jj1=0;
1.237 brouard 9711:
1.337 brouard 9712: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9713: /* k1=nres; */
1.338 brouard 9714: k1=TKresult[nres];
9715: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9716: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9717: /* if(m != 1 && TKresult[nres]!= k1) */
9718: /* continue; */
1.220 brouard 9719:
1.222 brouard 9720: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
9721: jj1++;
9722: if (cptcovn > 0) {
1.264 brouard 9723: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 9724: for (cpt=1; cpt<=cptcovs;cpt++){
9725: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9726: }
1.337 brouard 9727: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9728: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9729: /* } */
1.264 brouard 9730: fprintf(fichtm,"\"</a>");
9731:
1.222 brouard 9732: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 9733: for (cpt=1; cpt<=cptcovs;cpt++){
9734: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
9735: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 9736: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
9737: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 9738: }
1.230 brouard 9739: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 9740: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 9741: if(invalidvarcomb[k1]){
9742: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
9743: printf("\nCombination (%d) ignored because no cases \n",k1);
9744: continue;
9745: }
9746: }
9747: /* aij, bij */
1.259 brouard 9748: fprintf(fichtm,"<br>- Logit model (yours is: logit(pij)=log(pij/pii)= aij+ bij age+%s) as a function of age: <a href=\"%s_%d-1-%d.svg\">%s_%d-1-%d.svg</a><br> \
1.241 brouard 9749: <img src=\"%s_%d-1-%d.svg\">",model,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres);
1.222 brouard 9750: /* Pij */
1.241 brouard 9751: fprintf(fichtm,"<br>\n- P<sub>ij</sub> or conditional probabilities to be observed in state j being in state i, %d (stepm) months before: <a href=\"%s_%d-2-%d.svg\">%s_%d-2-%d.svg</a><br> \
9752: <img src=\"%s_%d-2-%d.svg\">",stepm,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres);
1.222 brouard 9753: /* Quasi-incidences */
9754: fprintf(fichtm,"<br>\n- I<sub>ij</sub> or Conditional probabilities to be observed in state j being in state i %d (stepm) months\
1.220 brouard 9755: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 9756: incidence (rates) are the limit when h tends to zero of the ratio of the probability <sub>h</sub>P<sub>ij</sub> \
1.241 brouard 9757: divided by h: <sub>h</sub>P<sub>ij</sub>/h : <a href=\"%s_%d-3-%d.svg\">%s_%d-3-%d.svg</a><br> \
9758: <img src=\"%s_%d-3-%d.svg\">",stepm,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres);
1.222 brouard 9759: /* Survival functions (period) in state j */
9760: for(cpt=1; cpt<=nlstate;cpt++){
1.359 brouard 9761: fprintf(fichtm,"<br>\n- Survival functions in state %d. And probability to be observed in state %d being in state (1 to %d) at different ages. Mean times spent in state (or Life Expectancy or Health Expectancy etc.) are the areas under each curve. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.329 brouard 9762: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
9763: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 9764: }
9765: /* State specific survival functions (period) */
9766: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 9767: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
1.359 brouard 9768: And probability to be observed in various states (up to %d) being in state %d at different ages. Mean times spent in state (or Life Expectancy or Health Expectancy etc.) are the areas under each curve. \
1.329 brouard 9769: <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> ", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
9770: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
9771: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 9772: }
1.288 brouard 9773: /* Period (forward stable) prevalence in each health state */
1.222 brouard 9774: for(cpt=1; cpt<=nlstate;cpt++){
1.359 brouard 9775: fprintf(fichtm,"<br>\n- Convergence to period (stable) prevalence in state %d. Or probability for a person being in state (1 to %d) at different ages, to be alive in state %d some years after. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.338 brouard 9776: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 9777: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 9778: }
1.296 brouard 9779: if(prevbcast==1){
1.288 brouard 9780: /* Backward prevalence in each health state */
1.222 brouard 9781: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 9782: fprintf(fichtm,"<br>\n- Convergence to mixed (stable) back prevalence in state %d. Or probability for a person to be in state %d at a younger age, knowing that she/he was in state (1 to %d) at different older ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
9783: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
9784: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 9785: }
1.217 brouard 9786: }
1.222 brouard 9787: if(prevfcast==1){
1.288 brouard 9788: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 9789: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 9790: fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), from year %.1f up to year %.1f tending to period (stable) forward prevalence in state %d. Or probability to be in state %d being in an observed weighted state (from 1 to %d). <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
9791: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
9792: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
9793: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 9794: }
9795: }
1.296 brouard 9796: if(prevbcast==1){
1.268 brouard 9797: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
9798: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 9799: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
1.359 brouard 9800: from year %.1f up to year %.1f (probably close to stable [mixed] back prevalence in state %d). Randomness in cross-sectional prevalence is not taken into \
9801: account but can visually be appreciated. Or probability to have been in an state %d, knowing that the person was in either state (1 or %d) \
1.314 brouard 9802: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9803: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
9804: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 9805: }
9806: }
1.220 brouard 9807:
1.222 brouard 9808: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 9809: fprintf(fichtm,"\n<br>- Life expectancy by health state (%d) at initial age and its decomposition into health expectancies in each alive state (1 to %d) (or area under each survival functions): <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
9810: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
9811: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 9812: }
9813: /* } /\* end i1 *\/ */
1.337 brouard 9814: }/* End k1=nres */
1.222 brouard 9815: fprintf(fichtm,"</ul>");
1.126 brouard 9816:
1.222 brouard 9817: fprintf(fichtm,"\
1.126 brouard 9818: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 9819: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 9820: - 95%% confidence intervals and Wald tests of the estimated parameters are in the log file if optimization has been done (mle != 0).<br> \
1.197 brouard 9821: But because parameters are usually highly correlated (a higher incidence of disability \
9822: and a higher incidence of recovery can give very close observed transition) it might \
9823: be very useful to look not only at linear confidence intervals estimated from the \
9824: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
9825: (parameters) of the logistic regression, it might be more meaningful to visualize the \
9826: covariance matrix of the one-step probabilities. \
9827: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 9828:
1.222 brouard 9829: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
9830: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
9831: fprintf(fichtm,"\
1.126 brouard 9832: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9833: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 9834:
1.222 brouard 9835: fprintf(fichtm,"\
1.126 brouard 9836: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9837: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
9838: fprintf(fichtm,"\
1.126 brouard 9839: - Variances and covariances of health expectancies by age and <b>initial health status</b> (cov(e<sup>ij</sup>,e<sup>kl</sup>)(estepm=%2d months): \
9840: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 9841: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 9842: fprintf(fichtm,"\
1.126 brouard 9843: - (a) Health expectancies by health status at initial age (e<sup>ij</sup>) and standard errors (in parentheses) (b) life expectancies and standard errors (e<sup>i.</sup>=e<sup>i1</sup>+e<sup>i2</sup>+...)(estepm=%2d months): \
9844: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 9845: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 9846: fprintf(fichtm,"\
1.288 brouard 9847: - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), e<sup>ij</sup> are weighted by the forward (period) prevalences in each state i (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a><br>\n",
1.222 brouard 9848: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
9849: fprintf(fichtm,"\
1.128 brouard 9850: - Total life expectancy and total health expectancies to be spent in each health state e<sup>.j</sup> with their standard errors (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9851: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
9852: fprintf(fichtm,"\
1.288 brouard 9853: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 9854: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 9855:
9856: /* if(popforecast==1) fprintf(fichtm,"\n */
9857: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
9858: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
9859: /* <br>",fileres,fileres,fileres,fileres); */
9860: /* else */
1.338 brouard 9861: /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=1+age+%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
1.222 brouard 9862: fflush(fichtm);
1.126 brouard 9863:
1.225 brouard 9864: m=pow(2,cptcoveff);
1.222 brouard 9865: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 9866:
1.317 brouard 9867: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
9868:
9869: jj1=0;
9870:
9871: fprintf(fichtm," \n<ul>");
1.337 brouard 9872: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9873: /* k1=nres; */
1.338 brouard 9874: k1=TKresult[nres];
1.337 brouard 9875: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9876: /* if(m != 1 && TKresult[nres]!= k1) */
9877: /* continue; */
1.317 brouard 9878: jj1++;
9879: if (cptcovn > 0) {
9880: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 9881: for (cpt=1; cpt<=cptcovs;cpt++){
9882: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9883: }
9884: fprintf(fichtm,"\">");
9885:
9886: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
9887: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 9888: for (cpt=1; cpt<=cptcovs;cpt++){
9889: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9890: }
9891: if(invalidvarcomb[k1]){
9892: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
9893: continue;
9894: }
9895: fprintf(fichtm,"</a></li>");
9896: } /* cptcovn >0 */
1.337 brouard 9897: } /* End nres */
1.317 brouard 9898: fprintf(fichtm," \n</ul>");
9899:
1.222 brouard 9900: jj1=0;
1.237 brouard 9901:
1.241 brouard 9902: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9903: /* k1=nres; */
1.338 brouard 9904: k1=TKresult[nres];
9905: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9906: /* for(k1=1; k1<=m;k1++){ */
9907: /* if(m != 1 && TKresult[nres]!= k1) */
9908: /* continue; */
1.222 brouard 9909: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
9910: jj1++;
1.126 brouard 9911: if (cptcovn > 0) {
1.317 brouard 9912: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 9913: for (cpt=1; cpt<=cptcovs;cpt++){
9914: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9915: }
9916: fprintf(fichtm,"\"</a>");
9917:
1.126 brouard 9918: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 9919: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
9920: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
9921: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 9922: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 9923: }
1.237 brouard 9924:
1.338 brouard 9925: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 9926:
1.222 brouard 9927: if(invalidvarcomb[k1]){
9928: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
9929: continue;
9930: }
1.337 brouard 9931: } /* If cptcovn >0 */
1.126 brouard 9932: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 9933: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 9934: prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d-%d.svg\"> %s_%d-%d-%d.svg</a>",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
9935: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
9936: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 9937: }
9938: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.360 brouard 9939: health expectancies in each live state (1 to %d) with confidence intervals \
9940: on left y-scale as well as proportions of time spent in each live state \
9941: (with confidence intervals) on right y-scale 0 to 100%%.\
9942: If popbased=1 the smooth (due to the model) \
1.128 brouard 9943: true period expectancies (those weighted with period prevalences are also\
9944: drawn in addition to the population based expectancies computed using\
1.314 brouard 9945: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>",nlstate, subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
9946: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
9947: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 9948: /* } /\* end i1 *\/ */
1.241 brouard 9949: }/* End nres */
1.222 brouard 9950: fprintf(fichtm,"</ul>");
9951: fflush(fichtm);
1.126 brouard 9952: }
9953:
9954: /******************* Gnuplot file **************/
1.296 brouard 9955: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double bage, double fage , int prevfcast, int prevbcast, char pathc[], double p[], int offyear, int offbyear){
1.126 brouard 9956:
1.354 brouard 9957: char dirfileres[256],optfileres[256];
9958: char gplotcondition[256], gplotlabel[256];
1.343 brouard 9959: int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,kf=0,kvar=0,kk=0,ipos=0,iposold=0,ij=0, ijp=0, l=0;
1.211 brouard 9960: int lv=0, vlv=0, kl=0;
1.130 brouard 9961: int ng=0;
1.201 brouard 9962: int vpopbased;
1.223 brouard 9963: int ioffset; /* variable offset for columns */
1.270 brouard 9964: int iyearc=1; /* variable column for year of projection */
9965: int iagec=1; /* variable column for age of projection */
1.235 brouard 9966: int nres=0; /* Index of resultline */
1.266 brouard 9967: int istart=1; /* For starting graphs in projections */
1.219 brouard 9968:
1.126 brouard 9969: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
9970: /* printf("Problem with file %s",optionfilegnuplot); */
9971: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
9972: /* } */
9973:
9974: /*#ifdef windows */
9975: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 9976: /*#endif */
1.225 brouard 9977: m=pow(2,cptcoveff);
1.126 brouard 9978:
1.274 brouard 9979: /* diagram of the model */
9980: fprintf(ficgp,"\n#Diagram of the model \n");
9981: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
9982: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
9983: fprintf(ficgp,"\n#Peripheral arrows\nset for [i=1:%d] for [j=1:%d] arrow i*10+j from cos(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.95*(cos(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) - cos(pi*((1-(%d/2)*2./%d)/2+(j-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta2:0)), -0.95*(sin(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) - sin(pi*((1-(%d/2)*2./%d)/2+(j-1)*2./%d))+( i!=j?(i-j)/abs(i-j)*delta2:0)) ls (i < j? 1:2)\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
9984:
1.343 brouard 9985: fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=1:%d] for [j=1:%d] arrow (%d+1)*10+i from cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.80*(cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) ), -0.80*(sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) + yoff ) ls 4\n",nlstate, nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
1.274 brouard 9986: fprintf(ficgp,"\n#show arrow\nunset label\n");
9987: fprintf(ficgp,"\n#States labels, starting from 2 (2-i) instead of (1-i), was (i-1)\nset for [i=1:%d] label i sprintf(\"State %%d\",i) center at cos(pi*((1-(%d/2)*2./%d)/2+(2-i)*2./%d)), yoff+sin(pi*((1-(%d/2)*2./%d)/2+(2-i)*2./%d)) font \"helvetica, 16\" tc rgbcolor \"blue\"\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
9988: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
9989: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
9990: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
9991: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
9992:
1.202 brouard 9993: /* Contribution to likelihood */
9994: /* Plot the probability implied in the likelihood */
1.223 brouard 9995: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
9996: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
9997: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
9998: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 9999: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 10000: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
10001: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 10002: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
10003: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
10004: fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$13):6 t \"All sample, transitions colored by destination\" with dots lc variable; set out;\n",subdirf(fileresilk));
10005: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
10006: fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$13):5 t \"All sample, transitions colored by origin\" with dots lc variable; set out;\n\n",subdirf(fileresilk));
10007: for (i=1; i<= nlstate ; i ++) {
10008: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
10009: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
10010: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($12/4.):6 t \"p%d%d\" with points pointtype 7 ps variable lc variable \\\n",i,1,i,1);
10011: for (j=2; j<= nlstate+ndeath ; j ++) {
10012: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($12/4.):6 t \"p%d%d\" with points pointtype 7 ps variable lc variable ",i,j,i,j);
10013: }
10014: fprintf(ficgp,";\nset out; unset ylabel;\n");
10015: }
10016: /* unset log; plot "rrtest1_sorted_4/ILK_rrtest1_sorted_4.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with points lc variable */
10017: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
10018: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
10019: fprintf(ficgp,"\nset out;unset log\n");
10020: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 10021:
1.343 brouard 10022: /* Plot the probability implied in the likelihood by covariate value */
10023: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
10024: /* if(debugILK==1){ */
10025: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 10026: kvar=Tvar[TvarFind[kf]]; /* variable name */
10027: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 10028: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
1.356 brouard 10029: /* k=19+kf;/\*offset because there are 19 columns in the ILK_ file *\/ */
1.355 brouard 10030: k=16+nlstate+kf;/*offset because there are 19 columns in the ILK_ file, first cov Vn on col 21 with 4 living states */
1.343 brouard 10031: for (i=1; i<= nlstate ; i ++) {
10032: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
10033: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 10034: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
10035: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
10036: for (j=2; j<= nlstate+ndeath ; j ++) {
10037: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
10038: }
10039: }else{
10040: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar);
10041: for (j=2; j<= nlstate+ndeath ; j ++) {
10042: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar);
10043: }
1.343 brouard 10044: }
10045: fprintf(ficgp,";\nset out; unset ylabel;\n");
10046: }
10047: } /* End of each covariate dummy */
10048: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
10049: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
10050: * kmodel = 1 2 3 4 5 6 7 8 9
10051: * varying 1 2 3 4 5
10052: * ncovv 1 2 3 4 5 6 7 8
10053: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
10054: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
10055: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
10056: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
10057: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
10058: */
10059: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
10060: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
10061: /* printf("DebugILK ficgp ncovv=%d, kvar=TvarVV[ncovv]=%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
10062: if(ipos!=iposold){ /* Not a product or first of a product */
10063: /* printf(" %d",ipos); */
10064: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
10065: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
10066: kk++; /* Position of the ncovv column in ILK_ */
10067: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
10068: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
10069: for (i=1; i<= nlstate ; i ++) {
10070: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
10071: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
10072:
1.348 brouard 10073: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 10074: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
10075: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
10076: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
10077: for (j=2; j<= nlstate+ndeath ; j ++) {
10078: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
10079: }
10080: }else{
10081: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
10082: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar);
10083: for (j=2; j<= nlstate+ndeath ; j ++) {
10084: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar);
10085: }
10086: }
10087: fprintf(ficgp,";\nset out; unset ylabel;\n");
10088: }
10089: }/* End if dummy varying */
10090: }else{ /*Product */
10091: /* printf("*"); */
10092: /* fprintf(ficresilk,"*"); */
10093: }
10094: iposold=ipos;
10095: } /* For each time varying covariate */
10096: /* } /\* debugILK==1 *\/ */
10097: /* unset log; plot "rrtest1_sorted_4/ILK_rrtest1_sorted_4.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with points lc variable */
10098: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
10099: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
10100: fprintf(ficgp,"\nset out;unset log\n");
10101: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
10102:
10103:
10104:
1.126 brouard 10105: strcpy(dirfileres,optionfilefiname);
10106: strcpy(optfileres,"vpl");
1.223 brouard 10107: /* 1eme*/
1.238 brouard 10108: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 10109: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 10110: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10111: k1=TKresult[nres];
1.338 brouard 10112: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 10113: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 10114: /* if(m != 1 && TKresult[nres]!= k1) */
10115: /* continue; */
1.238 brouard 10116: /* We are interested in selected combination by the resultline */
1.246 brouard 10117: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 10118: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 10119: strcpy(gplotlabel,"(");
1.337 brouard 10120: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10121: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10122: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10123:
10124: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
10125: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
10126: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10127: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10128: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10129: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10130: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
10131: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
10132: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
10133: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10134: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10135: /* } */
10136: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10137: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
10138: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10139: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 10140: }
10141: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 10142: /* printf("\n#\n"); */
1.238 brouard 10143: fprintf(ficgp,"\n#\n");
10144: if(invalidvarcomb[k1]){
1.260 brouard 10145: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 10146: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10147: continue;
10148: }
1.235 brouard 10149:
1.241 brouard 10150: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
10151: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 10152: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
1.338 brouard 10153: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 10154: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
10155: /* fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); */
10156: /* k1-1 error should be nres-1*/
1.238 brouard 10157: for (i=1; i<= nlstate ; i ++) {
10158: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10159: else fprintf(ficgp," %%*lf (%%*lf)");
10160: }
1.288 brouard 10161: fprintf(ficgp,"\" t\"Forward prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 10162: for (i=1; i<= nlstate ; i ++) {
10163: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10164: else fprintf(ficgp," %%*lf (%%*lf)");
10165: }
1.260 brouard 10166: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 10167: for (i=1; i<= nlstate ; i ++) {
10168: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10169: else fprintf(ficgp," %%*lf (%%*lf)");
10170: }
1.265 brouard 10171: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
10172:
10173: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
10174: if(cptcoveff ==0){
1.271 brouard 10175: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 10176: }else{
10177: kl=0;
10178: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 10179: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
10180: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 10181: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10182: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10183: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
10184: vlv= nbcode[Tvaraff[k]][lv];
10185: kl++;
10186: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
10187: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10188: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10189: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10190: if(k==cptcoveff){
10191: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
10192: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
10193: }else{
10194: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
10195: kl++;
10196: }
10197: } /* end covariate */
10198: } /* end if no covariate */
10199:
1.296 brouard 10200: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 10201: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 10202: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 10203: if(cptcoveff ==0){
1.245 brouard 10204: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 10205: }else{
10206: kl=0;
10207: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 10208: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
10209: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 10210: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10211: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10212: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 10213: /* vlv= nbcode[Tvaraff[k]][lv]; */
10214: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 10215: kl++;
1.238 brouard 10216: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
10217: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10218: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10219: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10220: if(k==cptcoveff){
1.245 brouard 10221: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 10222: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 10223: }else{
1.332 brouard 10224: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 10225: kl++;
10226: }
10227: } /* end covariate */
10228: } /* end if no covariate */
1.296 brouard 10229: if(prevbcast == 1){
1.268 brouard 10230: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
10231: /* k1-1 error should be nres-1*/
10232: for (i=1; i<= nlstate ; i ++) {
10233: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10234: else fprintf(ficgp," %%*lf (%%*lf)");
10235: }
1.271 brouard 10236: fprintf(ficgp,"\" t\"Backward (stable) prevalence\" w l lt 6 dt 3,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
1.268 brouard 10237: for (i=1; i<= nlstate ; i ++) {
10238: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10239: else fprintf(ficgp," %%*lf (%%*lf)");
10240: }
1.276 brouard 10241: fprintf(ficgp,"\" t\"95%% CI\" w l lt 4,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
1.268 brouard 10242: for (i=1; i<= nlstate ; i ++) {
10243: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10244: else fprintf(ficgp," %%*lf (%%*lf)");
10245: }
1.274 brouard 10246: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 10247: } /* end if backprojcast */
1.296 brouard 10248: } /* end if prevbcast */
1.276 brouard 10249: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
10250: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 10251: } /* nres */
1.337 brouard 10252: /* } /\* k1 *\/ */
1.201 brouard 10253: } /* cpt */
1.235 brouard 10254:
10255:
1.126 brouard 10256: /*2 eme*/
1.337 brouard 10257: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 10258: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10259: k1=TKresult[nres];
1.338 brouard 10260: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10261: /* if(m != 1 && TKresult[nres]!= k1) */
10262: /* continue; */
1.238 brouard 10263: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 10264: strcpy(gplotlabel,"(");
1.337 brouard 10265: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10266: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10267: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10268: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10269: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10270: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10271: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10272: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10273: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10274: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10275: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10276: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10277: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10278: /* } */
10279: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
10280: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10281: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10282: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10283: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 10284: }
1.264 brouard 10285: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 10286: fprintf(ficgp,"\n#\n");
1.223 brouard 10287: if(invalidvarcomb[k1]){
10288: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10289: continue;
10290: }
1.219 brouard 10291:
1.241 brouard 10292: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 10293: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 10294: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
10295: if(vpopbased==0){
1.360 brouard 10296: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nunset ytics; unset y2tics; set ytics nomirror; set y2tics 0,10,100;set y2range [0:100];\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 10297: }else
1.238 brouard 10298: fprintf(ficgp,"\nreplot ");
1.360 brouard 10299: for (i=1; i<= nlstate+1 ; i ++) { /* For state i-1=0 is LE, while i-1=1 to nlstate are origin state */
1.238 brouard 10300: k=2*i;
1.360 brouard 10301: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ?$4 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1, vpopbased); /* for fixed variables age, popbased, mobilav */
10302: for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/
10303: if (j==i) fprintf(ficgp," %%lf (%%lf)"); /* We want to read e.. i=1,j=1, e.1 i=2,j=2, e.2 i=3,j=3 */
10304: else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */
1.238 brouard 10305: }
10306: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
1.360 brouard 10307: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1); /* state=i-1=1 to nlstate */
1.261 brouard 10308: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4-$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
1.238 brouard 10309: for (j=1; j<= nlstate+1 ; j ++) {
10310: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10311: else fprintf(ficgp," %%*lf (%%*lf)");
10312: }
10313: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 10314: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4+$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
1.238 brouard 10315: for (j=1; j<= nlstate+1 ; j ++) {
10316: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10317: else fprintf(ficgp," %%*lf (%%*lf)");
10318: }
1.360 brouard 10319: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0,\\\n"); /* ,\\\n added for th percentage graphs */
1.238 brouard 10320: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
10321: } /* state */
1.360 brouard 10322: /* again for the percentag spent in state i-1=1 to i-1=nlstate */
10323: for (i=2; i<= nlstate+1 ; i ++) { /* For state i-1=0 is LE, while i-1=1 to nlstate are origin state */
10324: k=2*i;
10325: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && ($4)<=1 && ($4)>=0 ?($4)*100. : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1, vpopbased); /* for fixed variables age, popbased, mobilav */
10326: for (j=1; j<= nlstate ; j ++)
10327: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10328: for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/
10329: if (j==i) fprintf(ficgp," %%lf (%%lf)"); /* We want to read e.. i=1,j=1, e.1 i=2,j=2, e.2 i=3,j=3 */
10330: else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */
10331: }
10332: if (i== 1) fprintf(ficgp,"\" t\"%%TLE\" w l lt %d axis x1y2, \\\n",i); /* Not used */
10333: else fprintf(ficgp,"\" t\"%%LE in state (%d)\" w l lw 2 lt %d axis x1y2, \\\n",i-1,i+1); /* state=i-1=1 to nlstate */
10334: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && ($4-$5*2)<=1 && ($4-$5*2)>=0? ($4-$5*2)*100. : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
10335: for (j=1; j<= nlstate ; j ++)
10336: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10337: for (j=1; j<= nlstate+1 ; j ++) {
10338: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10339: else fprintf(ficgp," %%*lf (%%*lf)");
10340: }
10341: fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,");
10342: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && ($4+$5*2)<=1 && ($4+$5*2)>=0 ? ($4+$5*2)*100. : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
10343: for (j=1; j<= nlstate ; j ++)
10344: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10345: for (j=1; j<= nlstate+1 ; j ++) {
10346: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10347: else fprintf(ficgp," %%*lf (%%*lf)");
10348: }
10349: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2");
10350: else fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,\\\n");
10351: } /* state for percent */
1.238 brouard 10352: } /* vpopbased */
1.264 brouard 10353: fprintf(ficgp,"\nset out;set out \"%s_%d-%d.svg\"; replot; set out; unset label;\n",subdirf2(optionfilefiname,"E_"),k1,nres); /* Buggy gnuplot */
1.238 brouard 10354: } /* end nres */
1.337 brouard 10355: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 10356:
10357:
10358: /*3eme*/
1.337 brouard 10359: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 10360: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10361: k1=TKresult[nres];
1.338 brouard 10362: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10363: /* if(m != 1 && TKresult[nres]!= k1) */
10364: /* continue; */
1.238 brouard 10365:
1.332 brouard 10366: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 10367: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 10368: strcpy(gplotlabel,"(");
1.337 brouard 10369: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10370: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10371: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10372: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10373: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10374: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10375: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10376: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10377: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10378: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10379: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10380: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10381: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10382: /* } */
10383: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10384: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
10385: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
10386: }
1.264 brouard 10387: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10388: fprintf(ficgp,"\n#\n");
10389: if(invalidvarcomb[k1]){
10390: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10391: continue;
10392: }
10393:
10394: /* k=2+nlstate*(2*cpt-2); */
10395: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 10396: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 10397: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 10398: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 10399: plot [%.f:%.f] \"%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",ageminpar,fage,subdirf2(fileresu,"E_"),nres-1,nres-1,k,cpt);
1.238 brouard 10400: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
10401: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
10402: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
10403: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
10404: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
10405: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 10406:
1.238 brouard 10407: */
10408: for (i=1; i< nlstate ; i ++) {
1.261 brouard 10409: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileresu,"E_"),nres-1,nres-1,k+i,cpt,i+1);
1.238 brouard 10410: /* fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileres,"e"),k1-1,k1-1,k+2*i,cpt,i+1);*/
1.219 brouard 10411:
1.238 brouard 10412: }
1.261 brouard 10413: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d.\" w l",subdirf2(fileresu,"E_"),nres-1,nres-1,k+nlstate,cpt);
1.238 brouard 10414: }
1.264 brouard 10415: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 10416: } /* end nres */
1.337 brouard 10417: /* } /\* end kl 3eme *\/ */
1.126 brouard 10418:
1.223 brouard 10419: /* 4eme */
1.201 brouard 10420: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 10421: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 10422: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10423: k1=TKresult[nres];
1.338 brouard 10424: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10425: /* if(m != 1 && TKresult[nres]!= k1) */
10426: /* continue; */
1.238 brouard 10427: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 10428: strcpy(gplotlabel,"(");
1.337 brouard 10429: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
10430: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10431: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10432: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10433: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10434: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10435: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10436: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10437: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10438: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10439: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10440: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10441: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10442: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10443: /* } */
10444: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10445: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10446: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 10447: }
1.264 brouard 10448: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10449: fprintf(ficgp,"\n#\n");
10450: if(invalidvarcomb[k1]){
10451: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10452: continue;
1.223 brouard 10453: }
1.238 brouard 10454:
1.241 brouard 10455: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 10456: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 10457: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
10458: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10459: k=3;
10460: for (i=1; i<= nlstate ; i ++){
10461: if(i==1){
10462: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10463: }else{
10464: fprintf(ficgp,", '' ");
10465: }
10466: l=(nlstate+ndeath)*(i-1)+1;
10467: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
10468: for (j=2; j<= nlstate+ndeath ; j ++)
10469: fprintf(ficgp,"+$%d",k+l+j-1);
10470: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
10471: } /* nlstate */
1.264 brouard 10472: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 10473: } /* end cpt state*/
10474: } /* end nres */
1.337 brouard 10475: /* } /\* end covariate k1 *\/ */
1.238 brouard 10476:
1.220 brouard 10477: /* 5eme */
1.201 brouard 10478: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 10479: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 10480: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10481: k1=TKresult[nres];
1.338 brouard 10482: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10483: /* if(m != 1 && TKresult[nres]!= k1) */
10484: /* continue; */
1.238 brouard 10485: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 10486: strcpy(gplotlabel,"(");
1.238 brouard 10487: fprintf(ficgp,"\n#\n#\n# Survival functions in state j and all livestates from state i by final state j: 'lij' files, cov=%d state=%d",k1, cpt);
1.337 brouard 10488: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10489: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10490: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10491: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10492: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10493: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10494: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10495: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10496: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10497: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10498: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10499: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10500: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10501: /* } */
10502: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10503: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10504: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 10505: }
1.264 brouard 10506: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10507: fprintf(ficgp,"\n#\n");
10508: if(invalidvarcomb[k1]){
10509: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10510: continue;
10511: }
1.227 brouard 10512:
1.241 brouard 10513: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 10514: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 10515: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
10516: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10517: k=3;
10518: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
10519: if(j==1)
10520: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10521: else
10522: fprintf(ficgp,", '' ");
10523: l=(nlstate+ndeath)*(cpt-1) +j;
10524: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
10525: /* for (i=2; i<= nlstate+ndeath ; i ++) */
10526: /* fprintf(ficgp,"+$%d",k+l+i-1); */
10527: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
10528: } /* nlstate */
10529: fprintf(ficgp,", '' ");
10530: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
10531: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
10532: l=(nlstate+ndeath)*(cpt-1) +j;
10533: if(j < nlstate)
10534: fprintf(ficgp,"$%d +",k+l);
10535: else
10536: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
10537: }
1.264 brouard 10538: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 10539: } /* end cpt state*/
1.337 brouard 10540: /* } /\* end covariate *\/ */
1.238 brouard 10541: } /* end nres */
1.227 brouard 10542:
1.220 brouard 10543: /* 6eme */
1.202 brouard 10544: /* CV preval stable (period) for each covariate */
1.337 brouard 10545: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10546: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10547: k1=TKresult[nres];
1.338 brouard 10548: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10549: /* if(m != 1 && TKresult[nres]!= k1) */
10550: /* continue; */
1.255 brouard 10551: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 10552: strcpy(gplotlabel,"(");
1.288 brouard 10553: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10554: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10555: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10556: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10557: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10558: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10559: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10560: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10561: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10562: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10563: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10564: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10565: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10566: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10567: /* } */
10568: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10569: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10570: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10571: }
1.264 brouard 10572: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 10573: fprintf(ficgp,"\n#\n");
1.223 brouard 10574: if(invalidvarcomb[k1]){
1.227 brouard 10575: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10576: continue;
1.223 brouard 10577: }
1.227 brouard 10578:
1.241 brouard 10579: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 10580: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.126 brouard 10581: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 10582: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 10583: k=3; /* Offset */
1.255 brouard 10584: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 10585: if(i==1)
10586: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10587: else
10588: fprintf(ficgp,", '' ");
1.255 brouard 10589: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 10590: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
10591: for (j=2; j<= nlstate ; j ++)
10592: fprintf(ficgp,"+$%d",k+l+j-1);
10593: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 10594: } /* nlstate */
1.264 brouard 10595: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 10596: } /* end cpt state*/
10597: } /* end covariate */
1.227 brouard 10598:
10599:
1.220 brouard 10600: /* 7eme */
1.296 brouard 10601: if(prevbcast == 1){
1.288 brouard 10602: /* CV backward prevalence for each covariate */
1.337 brouard 10603: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10604: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10605: k1=TKresult[nres];
1.338 brouard 10606: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10607: /* if(m != 1 && TKresult[nres]!= k1) */
10608: /* continue; */
1.268 brouard 10609: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 10610: strcpy(gplotlabel,"(");
1.288 brouard 10611: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10612: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10613: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10614: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10615: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10616: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10617: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10618: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10619: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10620: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10621: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10622: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10623: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10624: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10625: /* } */
10626: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10627: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10628: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10629: }
1.264 brouard 10630: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 10631: fprintf(ficgp,"\n#\n");
10632: if(invalidvarcomb[k1]){
10633: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10634: continue;
10635: }
10636:
1.241 brouard 10637: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 10638: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 10639: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 10640: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 10641: k=3; /* Offset */
1.268 brouard 10642: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 10643: if(i==1)
10644: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
10645: else
10646: fprintf(ficgp,", '' ");
10647: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 10648: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 10649: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
10650: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a vérifier *\/ */
1.255 brouard 10651: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 10652: /* for (j=2; j<= nlstate ; j ++) */
10653: /* fprintf(ficgp,"+$%d",k+l+j-1); */
10654: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 10655: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 10656: } /* nlstate */
1.264 brouard 10657: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 10658: } /* end cpt state*/
10659: } /* end covariate */
1.296 brouard 10660: } /* End if prevbcast */
1.218 brouard 10661:
1.223 brouard 10662: /* 8eme */
1.218 brouard 10663: if(prevfcast==1){
1.288 brouard 10664: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 10665:
1.337 brouard 10666: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10667: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10668: k1=TKresult[nres];
1.338 brouard 10669: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10670: /* if(m != 1 && TKresult[nres]!= k1) */
10671: /* continue; */
1.211 brouard 10672: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 10673: strcpy(gplotlabel,"(");
1.288 brouard 10674: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10675: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10676: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10677: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10678: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10679: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10680: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10681: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10682: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10683: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10684: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10685: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10686: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10687: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10688: /* } */
10689: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10690: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10691: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10692: }
1.264 brouard 10693: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 10694: fprintf(ficgp,"\n#\n");
10695: if(invalidvarcomb[k1]){
10696: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10697: continue;
10698: }
10699:
10700: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 10701: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 10702: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 10703: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 10704: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 10705:
10706: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
10707: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
10708: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
10709: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 10710: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10711: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10712: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10713: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 10714: if(i==istart){
1.227 brouard 10715: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
10716: }else{
10717: fprintf(ficgp,",\\\n '' ");
10718: }
10719: if(cptcoveff ==0){ /* No covariate */
10720: ioffset=2; /* Age is in 2 */
10721: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10722: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10723: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10724: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10725: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 10726: if(i==nlstate+1){
1.270 brouard 10727: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 10728: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
10729: fprintf(ficgp,",\\\n '' ");
10730: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 10731: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 10732: offyear, \
1.268 brouard 10733: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 10734: }else
1.227 brouard 10735: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
10736: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
10737: }else{ /* more than 2 covariates */
1.270 brouard 10738: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
10739: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10740: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10741: iyearc=ioffset-1;
10742: iagec=ioffset;
1.227 brouard 10743: fprintf(ficgp," u %d:(",ioffset);
10744: kl=0;
10745: strcpy(gplotcondition,"(");
1.351 brouard 10746: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 10747: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 10748: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10749: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10750: lv=Tvresult[nres][k];
10751: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 10752: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10753: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10754: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 10755: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 10756: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 10757: kl++;
1.351 brouard 10758: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
10759: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 10760: kl++;
1.351 brouard 10761: if(k <cptcovs && cptcovs>1)
1.227 brouard 10762: sprintf(gplotcondition+strlen(gplotcondition)," && ");
10763: }
10764: strcpy(gplotcondition+strlen(gplotcondition),")");
10765: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
10766: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10767: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10768: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10769: if(i==nlstate+1){
1.270 brouard 10770: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
10771: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 10772: fprintf(ficgp,",\\\n '' ");
1.270 brouard 10773: fprintf(ficgp," u %d:(",iagec);
10774: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
10775: iyearc, iagec, offyear, \
10776: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 10777: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
1.227 brouard 10778: }else{
10779: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
10780: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
10781: }
10782: } /* end if covariate */
10783: } /* nlstate */
1.264 brouard 10784: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 10785: } /* end cpt state*/
10786: } /* end covariate */
10787: } /* End if prevfcast */
1.227 brouard 10788:
1.296 brouard 10789: if(prevbcast==1){
1.268 brouard 10790: /* Back projection from cross-sectional to stable (mixed) for each covariate */
10791:
1.337 brouard 10792: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 10793: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10794: k1=TKresult[nres];
1.338 brouard 10795: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10796: /* if(m != 1 && TKresult[nres]!= k1) */
10797: /* continue; */
1.268 brouard 10798: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
10799: strcpy(gplotlabel,"(");
10800: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
1.337 brouard 10801: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10802: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10803: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10804: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10805: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10806: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10807: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10808: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10809: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10810: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10811: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10812: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10813: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10814: /* } */
10815: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10816: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10817: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 10818: }
10819: strcpy(gplotlabel+strlen(gplotlabel),")");
10820: fprintf(ficgp,"\n#\n");
10821: if(invalidvarcomb[k1]){
10822: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10823: continue;
10824: }
10825:
10826: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
10827: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
10828: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
10829: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
10830: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10831:
10832: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
10833: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
10834: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
10835: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
10836: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10837: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10838: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10839: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10840: if(i==istart){
10841: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
10842: }else{
10843: fprintf(ficgp,",\\\n '' ");
10844: }
1.351 brouard 10845: /* if(cptcoveff ==0){ /\* No covariate *\/ */
10846: if(cptcovs ==0){ /* No covariate */
1.268 brouard 10847: ioffset=2; /* Age is in 2 */
10848: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10849: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10850: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10851: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10852: fprintf(ficgp," u %d:(", ioffset);
10853: if(i==nlstate+1){
1.270 brouard 10854: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 10855: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
10856: fprintf(ficgp,",\\\n '' ");
10857: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 10858: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 10859: offbyear, \
10860: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
10861: }else
10862: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
10863: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
10864: }else{ /* more than 2 covariates */
1.270 brouard 10865: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
10866: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10867: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10868: iyearc=ioffset-1;
10869: iagec=ioffset;
1.268 brouard 10870: fprintf(ficgp," u %d:(",ioffset);
10871: kl=0;
10872: strcpy(gplotcondition,"(");
1.337 brouard 10873: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 10874: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 10875: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
10876: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10877: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10878: lv=Tvresult[nres][k];
10879: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
10880: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10881: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10882: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
10883: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
10884: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10885: kl++;
10886: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
10887: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
10888: kl++;
1.338 brouard 10889: if(k <cptcovs && cptcovs>1)
1.337 brouard 10890: sprintf(gplotcondition+strlen(gplotcondition)," && ");
10891: }
1.268 brouard 10892: }
10893: strcpy(gplotcondition+strlen(gplotcondition),")");
10894: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
10895: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10896: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10897: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10898: if(i==nlstate+1){
1.270 brouard 10899: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
10900: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 10901: fprintf(ficgp,",\\\n '' ");
1.270 brouard 10902: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 10903: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 10904: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
10905: iyearc,iagec,offbyear, \
10906: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 10907: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
10908: }else{
10909: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
10910: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
10911: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
10912: }
10913: } /* end if covariate */
10914: } /* nlstate */
10915: fprintf(ficgp,"\nset out; unset label;\n");
10916: } /* end cpt state*/
10917: } /* end covariate */
1.296 brouard 10918: } /* End if prevbcast */
1.268 brouard 10919:
1.227 brouard 10920:
1.238 brouard 10921: /* 9eme writing MLE parameters */
10922: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 10923: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 10924: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 10925: for(k=1; k <=(nlstate+ndeath); k++){
10926: if (k != i) {
1.227 brouard 10927: fprintf(ficgp,"# current state %d\n",k);
10928: for(j=1; j <=ncovmodel; j++){
10929: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
10930: jk++;
10931: }
10932: fprintf(ficgp,"\n");
1.126 brouard 10933: }
10934: }
1.223 brouard 10935: }
1.187 brouard 10936: fprintf(ficgp,"##############\n#\n");
1.227 brouard 10937:
1.145 brouard 10938: /*goto avoid;*/
1.238 brouard 10939: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
10940: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 10941: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
10942: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
10943: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
10944: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
10945: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10946: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
10947: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10948: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
10949: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
10950: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10951: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
10952: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
10953: fprintf(ficgp,"#\n");
1.223 brouard 10954: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 10955: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 10956: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 10957: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 10958: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
10959: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 10960: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 10961: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10962: /* k1=nres; */
1.338 brouard 10963: k1=TKresult[nres];
10964: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10965: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 10966: strcpy(gplotlabel,"(");
1.276 brouard 10967: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 10968: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
10969: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
10970: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
10971: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10972: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10973: }
10974: /* if(m != 1 && TKresult[nres]!= k1) */
10975: /* continue; */
10976: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
10977: /* strcpy(gplotlabel,"("); */
10978: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
10979: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10980: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10981: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10982: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10983: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10984: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10985: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10986: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10987: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10988: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10989: /* } */
10990: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10991: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10992: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10993: /* } */
1.264 brouard 10994: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 10995: fprintf(ficgp,"\n#\n");
1.264 brouard 10996: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 10997: fprintf(ficgp,"\nset key outside ");
10998: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
10999: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 11000: fprintf(ficgp,"\nset ter svg size 640, 480 ");
11001: if (ng==1){
11002: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
11003: fprintf(ficgp,"\nunset log y");
11004: }else if (ng==2){
11005: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
11006: fprintf(ficgp,"\nset log y");
11007: }else if (ng==3){
11008: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
11009: fprintf(ficgp,"\nset log y");
11010: }else
11011: fprintf(ficgp,"\nunset title ");
11012: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
11013: i=1;
11014: for(k2=1; k2<=nlstate; k2++) {
11015: k3=i;
11016: for(k=1; k<=(nlstate+ndeath); k++) {
11017: if (k != k2){
11018: switch( ng) {
11019: case 1:
11020: if(nagesqr==0)
11021: fprintf(ficgp," p%d+p%d*x",i,i+1);
11022: else /* nagesqr =1 */
11023: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
11024: break;
11025: case 2: /* ng=2 */
11026: if(nagesqr==0)
11027: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
11028: else /* nagesqr =1 */
11029: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
11030: break;
11031: case 3:
11032: if(nagesqr==0)
11033: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
11034: else /* nagesqr =1 */
11035: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
11036: break;
11037: }
11038: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 11039: ijp=1; /* product no age */
11040: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
11041: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 11042: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 11043: switch(Typevar[j]){
11044: case 1:
11045: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
11046: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
11047: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
11048: if(DummyV[j]==0){/* Bug valgrind */
11049: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
11050: }else{ /* quantitative */
11051: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
11052: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11053: }
11054: ij++;
1.268 brouard 11055: }
1.237 brouard 11056: }
1.329 brouard 11057: }
11058: break;
11059: case 2:
11060: if(cptcovprod >0){
11061: if(j==Tprod[ijp]) { /* */
11062: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11063: if(ijp <=cptcovprod) { /* Product */
11064: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
11065: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
11066: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
11067: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11068: }else{ /* Vn is dummy and Vm is quanti */
11069: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
11070: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11071: }
11072: }else{ /* Vn*Vm Vn is quanti */
11073: if(DummyV[Tvard[ijp][2]]==0){
11074: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
11075: }else{ /* Both quanti */
11076: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11077: }
1.268 brouard 11078: }
1.329 brouard 11079: ijp++;
1.237 brouard 11080: }
1.329 brouard 11081: } /* end Tprod */
11082: }
11083: break;
1.349 brouard 11084: case 3:
11085: if(cptcovdageprod >0){
11086: /* if(j==Tprod[ijp]) { */ /* not necessary */
11087: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 11088: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
11089: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
11090: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 11091: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
11092: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11093: }else{ /* Vn is dummy and Vm is quanti */
11094: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 11095: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11096: }
1.350 brouard 11097: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 11098: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 11099: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 11100: }else{ /* Both quanti */
1.350 brouard 11101: fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11102: }
11103: }
11104: ijp++;
11105: }
11106: /* } */ /* end Tprod */
11107: }
11108: break;
1.329 brouard 11109: case 0:
11110: /* simple covariate */
1.264 brouard 11111: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 11112: if(Dummy[j]==0){
11113: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
11114: }else{ /* quantitative */
11115: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 11116: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 11117: }
1.329 brouard 11118: /* end simple */
11119: break;
11120: default:
11121: break;
11122: } /* end switch */
1.237 brouard 11123: } /* end j */
1.329 brouard 11124: }else{ /* k=k2 */
11125: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
11126: fprintf(ficgp," (1.");i=i-ncovmodel;
11127: }else
11128: i=i-ncovmodel;
1.223 brouard 11129: }
1.227 brouard 11130:
1.223 brouard 11131: if(ng != 1){
11132: fprintf(ficgp,")/(1");
1.227 brouard 11133:
1.264 brouard 11134: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 11135: if(nagesqr==0)
1.264 brouard 11136: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 11137: else /* nagesqr =1 */
1.264 brouard 11138: fprintf(ficgp,"+exp(p%d+p%d*x+p%d*x*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1,k3+(cpt-1)*ncovmodel+1+nagesqr);
1.217 brouard 11139:
1.223 brouard 11140: ij=1;
1.329 brouard 11141: ijp=1;
11142: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
11143: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
11144: switch(Typevar[j]){
11145: case 1:
11146: if(cptcovage >0){
11147: if(j==Tage[ij]) { /* Bug valgrind */
11148: if(ij <=cptcovage) { /* Bug valgrind */
11149: if(DummyV[j]==0){/* Bug valgrind */
11150: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
11151: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
11152: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
11153: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
11154: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11155: }else{ /* quantitative */
11156: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
11157: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
11158: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
11159: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11160: }
11161: ij++;
11162: }
11163: }
11164: }
11165: break;
11166: case 2:
11167: if(cptcovprod >0){
11168: if(j==Tprod[ijp]) { /* */
11169: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11170: if(ijp <=cptcovprod) { /* Product */
11171: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
11172: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
11173: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
11174: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11175: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
11176: }else{ /* Vn is dummy and Vm is quanti */
11177: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
11178: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11179: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11180: }
11181: }else{ /* Vn*Vm Vn is quanti */
11182: if(DummyV[Tvard[ijp][2]]==0){
11183: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
11184: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
11185: }else{ /* Both quanti */
11186: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11187: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11188: }
11189: }
11190: ijp++;
11191: }
11192: } /* end Tprod */
11193: } /* end if */
11194: break;
1.349 brouard 11195: case 3:
11196: if(cptcovdageprod >0){
11197: /* if(j==Tprod[ijp]) { /\* *\/ */
11198: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11199: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 11200: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
11201: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 11202: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
1.350 brouard 11203: fprintf(ficgp,"+p%d*%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11204: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
11205: }else{ /* Vn is dummy and Vm is quanti */
11206: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 11207: fprintf(ficgp,"+p%d*%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11208: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11209: }
11210: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 11211: if(DummyV[Tvardk[ijp][2]]==0){
11212: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 11213: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
11214: }else{ /* Both quanti */
1.350 brouard 11215: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11216: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11217: }
11218: }
11219: ijp++;
11220: }
11221: /* } /\* end Tprod *\/ */
11222: } /* end if */
11223: break;
1.329 brouard 11224: case 0:
11225: /* simple covariate */
11226: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
11227: if(Dummy[j]==0){
11228: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
11229: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
11230: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
11231: }else{ /* quantitative */
11232: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
11233: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
11234: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11235: }
11236: /* end simple */
11237: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
11238: break;
11239: default:
11240: break;
11241: } /* end switch */
1.223 brouard 11242: }
11243: fprintf(ficgp,")");
11244: }
11245: fprintf(ficgp,")");
11246: if(ng ==2)
1.276 brouard 11247: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"p%d%d\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.223 brouard 11248: else /* ng= 3 */
1.276 brouard 11249: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"i%d%d\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.329 brouard 11250: }else{ /* end ng <> 1 */
1.223 brouard 11251: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 11252: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"logit(p%d%d)\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.223 brouard 11253: }
11254: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
11255: fprintf(ficgp,",");
11256: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
11257: fprintf(ficgp,",");
11258: i=i+ncovmodel;
11259: } /* end k */
11260: } /* end k2 */
1.276 brouard 11261: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
11262: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 11263: } /* end resultline */
1.223 brouard 11264: } /* end ng */
11265: /* avoid: */
11266: fflush(ficgp);
1.126 brouard 11267: } /* end gnuplot */
11268:
11269:
11270: /*************** Moving average **************/
1.219 brouard 11271: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 11272: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 11273:
1.222 brouard 11274: int i, cpt, cptcod;
11275: int modcovmax =1;
11276: int mobilavrange, mob;
11277: int iage=0;
1.288 brouard 11278: int firstA1=0, firstA2=0;
1.222 brouard 11279:
1.266 brouard 11280: double sum=0., sumr=0.;
1.222 brouard 11281: double age;
1.266 brouard 11282: double *sumnewp, *sumnewm, *sumnewmr;
11283: double *agemingood, *agemaxgood;
11284: double *agemingoodr, *agemaxgoodr;
1.222 brouard 11285:
11286:
1.278 brouard 11287: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
11288: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 11289:
11290: sumnewp = vector(1,ncovcombmax);
11291: sumnewm = vector(1,ncovcombmax);
1.266 brouard 11292: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 11293: agemingood = vector(1,ncovcombmax);
1.266 brouard 11294: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 11295: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 11296: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 11297:
11298: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 11299: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 11300: sumnewp[cptcod]=0.;
1.266 brouard 11301: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
11302: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 11303: }
11304: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
11305:
1.266 brouard 11306: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
11307: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 11308: else mobilavrange=mobilav;
11309: for (age=bage; age<=fage; age++)
11310: for (i=1; i<=nlstate;i++)
11311: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
11312: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11313: /* We keep the original values on the extreme ages bage, fage and for
11314: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
11315: we use a 5 terms etc. until the borders are no more concerned.
11316: */
11317: for (mob=3;mob <=mobilavrange;mob=mob+2){
11318: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 11319: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
11320: sumnewm[cptcod]=0.;
11321: for (i=1; i<=nlstate;i++){
1.222 brouard 11322: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
11323: for (cpt=1;cpt<=(mob-1)/2;cpt++){
11324: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
11325: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
11326: }
11327: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 11328: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11329: } /* end i */
11330: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
11331: } /* end cptcod */
1.222 brouard 11332: }/* end age */
11333: }/* end mob */
1.266 brouard 11334: }else{
11335: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 11336: return -1;
1.266 brouard 11337: }
11338:
11339: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 11340: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
11341: if(invalidvarcomb[cptcod]){
11342: printf("\nCombination (%d) ignored because no cases \n",cptcod);
11343: continue;
11344: }
1.219 brouard 11345:
1.266 brouard 11346: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
11347: sumnewm[cptcod]=0.;
11348: sumnewmr[cptcod]=0.;
11349: for (i=1; i<=nlstate;i++){
11350: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11351: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11352: }
11353: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11354: agemingoodr[cptcod]=age;
11355: }
11356: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11357: agemingood[cptcod]=age;
11358: }
11359: } /* age */
11360: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 11361: sumnewm[cptcod]=0.;
1.266 brouard 11362: sumnewmr[cptcod]=0.;
1.222 brouard 11363: for (i=1; i<=nlstate;i++){
11364: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 11365: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11366: }
11367: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11368: agemaxgoodr[cptcod]=age;
1.222 brouard 11369: }
11370: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 11371: agemaxgood[cptcod]=age;
11372: }
11373: } /* age */
11374: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
11375: /* but they will change */
1.288 brouard 11376: firstA1=0;firstA2=0;
1.266 brouard 11377: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
11378: sumnewm[cptcod]=0.;
11379: sumnewmr[cptcod]=0.;
11380: for (i=1; i<=nlstate;i++){
11381: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11382: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11383: }
11384: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
11385: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11386: agemaxgoodr[cptcod]=age; /* age min */
11387: for (i=1; i<=nlstate;i++)
11388: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11389: }else{ /* bad we change the value with the values of good ages */
11390: for (i=1; i<=nlstate;i++){
11391: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
11392: } /* i */
11393: } /* end bad */
11394: }else{
11395: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11396: agemaxgood[cptcod]=age;
11397: }else{ /* bad we change the value with the values of good ages */
11398: for (i=1; i<=nlstate;i++){
11399: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
11400: } /* i */
11401: } /* end bad */
11402: }/* end else */
11403: sum=0.;sumr=0.;
11404: for (i=1; i<=nlstate;i++){
11405: sum+=mobaverage[(int)age][i][cptcod];
11406: sumr+=probs[(int)age][i][cptcod];
11407: }
11408: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 11409: if(!firstA1){
11410: firstA1=1;
11411: printf("Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
11412: }
11413: fprintf(ficlog,"Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.266 brouard 11414: } /* end bad */
11415: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
11416: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 11417: if(!firstA2){
11418: firstA2=1;
11419: printf("Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
11420: }
11421: fprintf(ficlog,"Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.222 brouard 11422: } /* end bad */
11423: }/* age */
1.266 brouard 11424:
11425: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 11426: sumnewm[cptcod]=0.;
1.266 brouard 11427: sumnewmr[cptcod]=0.;
1.222 brouard 11428: for (i=1; i<=nlstate;i++){
11429: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 11430: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11431: }
11432: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
11433: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
11434: agemingoodr[cptcod]=age;
11435: for (i=1; i<=nlstate;i++)
11436: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11437: }else{ /* bad we change the value with the values of good ages */
11438: for (i=1; i<=nlstate;i++){
11439: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
11440: } /* i */
11441: } /* end bad */
11442: }else{
11443: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11444: agemingood[cptcod]=age;
11445: }else{ /* bad */
11446: for (i=1; i<=nlstate;i++){
11447: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
11448: } /* i */
11449: } /* end bad */
11450: }/* end else */
11451: sum=0.;sumr=0.;
11452: for (i=1; i<=nlstate;i++){
11453: sum+=mobaverage[(int)age][i][cptcod];
11454: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 11455: }
1.266 brouard 11456: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 11457: printf("Moving average B1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you decrease fage=%d?\n",cptcod, sum, (int) age, (int)fage);
1.266 brouard 11458: } /* end bad */
11459: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
11460: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 11461: printf("Moving average B2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase fage=%d\n",cptcod,sumr, (int)age, (int)fage);
1.222 brouard 11462: } /* end bad */
11463: }/* age */
1.266 brouard 11464:
1.222 brouard 11465:
11466: for (age=bage; age<=fage; age++){
1.235 brouard 11467: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 11468: sumnewp[cptcod]=0.;
11469: sumnewm[cptcod]=0.;
11470: for (i=1; i<=nlstate;i++){
11471: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
11472: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11473: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
11474: }
11475: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
11476: }
11477: /* printf("\n"); */
11478: /* } */
1.266 brouard 11479:
1.222 brouard 11480: /* brutal averaging */
1.266 brouard 11481: /* for (i=1; i<=nlstate;i++){ */
11482: /* for (age=1; age<=bage; age++){ */
11483: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
11484: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
11485: /* } */
11486: /* for (age=fage; age<=AGESUP; age++){ */
11487: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
11488: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
11489: /* } */
11490: /* } /\* end i status *\/ */
11491: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
11492: /* for (age=1; age<=AGESUP; age++){ */
11493: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
11494: /* mobaverage[(int)age][i][cptcod]=0.; */
11495: /* } */
11496: /* } */
1.222 brouard 11497: }/* end cptcod */
1.266 brouard 11498: free_vector(agemaxgoodr,1, ncovcombmax);
11499: free_vector(agemaxgood,1, ncovcombmax);
11500: free_vector(agemingood,1, ncovcombmax);
11501: free_vector(agemingoodr,1, ncovcombmax);
11502: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 11503: free_vector(sumnewm,1, ncovcombmax);
11504: free_vector(sumnewp,1, ncovcombmax);
11505: return 0;
11506: }/* End movingaverage */
1.218 brouard 11507:
1.126 brouard 11508:
1.296 brouard 11509:
1.126 brouard 11510: /************** Forecasting ******************/
1.296 brouard 11511: /* void prevforecast(char fileres[], double dateintmean, double anprojd, double mprojd, double jprojd, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double anprojf, double p[], int cptcoveff)*/
11512: void prevforecast(char fileres[], double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
11513: /* dateintemean, mean date of interviews
11514: dateprojd, year, month, day of starting projection
11515: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 11516: agemin, agemax range of age
11517: dateprev1 dateprev2 range of dates during which prevalence is computed
11518: */
1.296 brouard 11519: /* double anprojd, mprojd, jprojd; */
11520: /* double anprojf, mprojf, jprojf; */
1.359 brouard 11521: int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0;
1.126 brouard 11522: double agec; /* generic age */
1.359 brouard 11523: double agelim, ppij;
11524: /*double *popcount;*/
1.126 brouard 11525: double ***p3mat;
1.218 brouard 11526: /* double ***mobaverage; */
1.126 brouard 11527: char fileresf[FILENAMELENGTH];
11528:
11529: agelim=AGESUP;
1.211 brouard 11530: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
11531: in each health status at the date of interview (if between dateprev1 and dateprev2).
11532: We still use firstpass and lastpass as another selection.
11533: */
1.214 brouard 11534: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
11535: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 11536:
1.201 brouard 11537: strcpy(fileresf,"F_");
11538: strcat(fileresf,fileresu);
1.126 brouard 11539: if((ficresf=fopen(fileresf,"w"))==NULL) {
11540: printf("Problem with forecast resultfile: %s\n", fileresf);
11541: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
11542: }
1.235 brouard 11543: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
11544: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 11545:
1.225 brouard 11546: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 11547:
11548:
11549: stepsize=(int) (stepm+YEARM-1)/YEARM;
11550: if (stepm<=12) stepsize=1;
11551: if(estepm < stepm){
11552: printf ("Problem %d lower than %d\n",estepm, stepm);
11553: }
1.270 brouard 11554: else{
11555: hstepm=estepm;
11556: }
11557: if(estepm > stepm){ /* Yes every two year */
11558: stepsize=2;
11559: }
1.296 brouard 11560: hstepm=hstepm/stepm;
1.126 brouard 11561:
1.296 brouard 11562:
11563: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
11564: /* fractional in yp1 *\/ */
11565: /* aintmean=yp; */
11566: /* yp2=modf((yp1*12),&yp); */
11567: /* mintmean=yp; */
11568: /* yp1=modf((yp2*30.5),&yp); */
11569: /* jintmean=yp; */
11570: /* if(jintmean==0) jintmean=1; */
11571: /* if(mintmean==0) mintmean=1; */
1.126 brouard 11572:
1.296 brouard 11573:
11574: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
11575: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
11576: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 11577: /* i1=pow(2,cptcoveff); */
11578: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 11579:
1.296 brouard 11580: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 11581:
11582: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 11583:
1.126 brouard 11584: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 11585: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11586: k=TKresult[nres];
11587: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11588: /* for(k=1; k<=i1;k++){ /\* We want to find the combination k corresponding to the values of the dummies given in this resut line (to be cleaned one day) *\/ */
11589: /* if(i1 != 1 && TKresult[nres]!= k) */
11590: /* continue; */
11591: /* if(invalidvarcomb[k]){ */
11592: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
11593: /* continue; */
11594: /* } */
1.227 brouard 11595: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 11596: for(j=1;j<=cptcovs;j++){
11597: /* for(j=1;j<=cptcoveff;j++) { */
11598: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
11599: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11600: /* } */
11601: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11602: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11603: /* } */
11604: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 11605: }
1.351 brouard 11606:
1.227 brouard 11607: fprintf(ficresf," yearproj age");
11608: for(j=1; j<=nlstate+ndeath;j++){
11609: for(i=1; i<=nlstate;i++)
11610: fprintf(ficresf," p%d%d",i,j);
11611: fprintf(ficresf," wp.%d",j);
11612: }
1.296 brouard 11613: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 11614: fprintf(ficresf,"\n");
1.296 brouard 11615: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 11616: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
11617: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 11618: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
11619: nhstepm = nhstepm/hstepm;
11620: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11621: oldm=oldms;savm=savms;
1.268 brouard 11622: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 11623: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 11624: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 11625: for (h=0; h<=nhstepm; h++){
11626: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 11627: break;
11628: }
11629: }
11630: fprintf(ficresf,"\n");
1.351 brouard 11631: /* for(j=1;j<=cptcoveff;j++) */
11632: for(j=1;j<=cptcovs;j++)
11633: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 11634: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 11635: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 11636: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 11637:
11638: for(j=1; j<=nlstate+ndeath;j++) {
11639: ppij=0.;
11640: for(i=1; i<=nlstate;i++) {
1.278 brouard 11641: if (mobilav>=1)
11642: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
11643: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
11644: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
11645: }
1.268 brouard 11646: fprintf(ficresf," %.3f", p3mat[i][j][h]);
11647: } /* end i */
11648: fprintf(ficresf," %.3f", ppij);
11649: }/* end j */
1.227 brouard 11650: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11651: } /* end agec */
1.266 brouard 11652: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
11653: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 11654: } /* end yearp */
11655: } /* end k */
1.219 brouard 11656:
1.126 brouard 11657: fclose(ficresf);
1.215 brouard 11658: printf("End of Computing forecasting \n");
11659: fprintf(ficlog,"End of Computing forecasting\n");
11660:
1.126 brouard 11661: }
11662:
1.269 brouard 11663: /************** Back Forecasting ******************/
1.296 brouard 11664: /* void prevbackforecast(char fileres[], double ***prevacurrent, double anback1, double mback1, double jback1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anback2, double p[], int cptcoveff){ */
11665: void prevbackforecast(char fileres[], double ***prevacurrent, double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
11666: /* back1, year, month, day of starting backprojection
1.267 brouard 11667: agemin, agemax range of age
11668: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 11669: anback2 year of end of backprojection (same day and month as back1).
11670: prevacurrent and prev are prevalences.
1.267 brouard 11671: */
1.359 brouard 11672: int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0;
1.267 brouard 11673: double agec; /* generic age */
1.359 brouard 11674: double agelim, ppij, ppi; /* ,jintmean,mintmean,aintmean;*/
11675: /*double *popcount;*/
1.267 brouard 11676: double ***p3mat;
11677: /* double ***mobaverage; */
11678: char fileresfb[FILENAMELENGTH];
11679:
1.268 brouard 11680: agelim=AGEINF;
1.267 brouard 11681: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
11682: in each health status at the date of interview (if between dateprev1 and dateprev2).
11683: We still use firstpass and lastpass as another selection.
11684: */
11685: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
11686: /* firstpass, lastpass, stepm, weightopt, model); */
11687:
11688: /*Do we need to compute prevalence again?*/
11689:
11690: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
11691:
11692: strcpy(fileresfb,"FB_");
11693: strcat(fileresfb,fileresu);
11694: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
11695: printf("Problem with back forecast resultfile: %s\n", fileresfb);
11696: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
11697: }
11698: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
11699: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
11700:
11701: if (cptcoveff==0) ncodemax[cptcoveff]=1;
11702:
11703:
11704: stepsize=(int) (stepm+YEARM-1)/YEARM;
11705: if (stepm<=12) stepsize=1;
11706: if(estepm < stepm){
11707: printf ("Problem %d lower than %d\n",estepm, stepm);
11708: }
1.270 brouard 11709: else{
11710: hstepm=estepm;
11711: }
11712: if(estepm >= stepm){ /* Yes every two year */
11713: stepsize=2;
11714: }
1.267 brouard 11715:
11716: hstepm=hstepm/stepm;
1.296 brouard 11717: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
11718: /* fractional in yp1 *\/ */
11719: /* aintmean=yp; */
11720: /* yp2=modf((yp1*12),&yp); */
11721: /* mintmean=yp; */
11722: /* yp1=modf((yp2*30.5),&yp); */
11723: /* jintmean=yp; */
11724: /* if(jintmean==0) jintmean=1; */
11725: /* if(mintmean==0) jintmean=1; */
1.267 brouard 11726:
1.351 brouard 11727: /* i1=pow(2,cptcoveff); */
11728: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 11729:
1.296 brouard 11730: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
11731: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 11732:
11733: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
11734:
1.351 brouard 11735: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11736: k=TKresult[nres];
11737: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11738: /* for(k=1; k<=i1;k++){ */
11739: /* if(i1 != 1 && TKresult[nres]!= k) */
11740: /* continue; */
11741: /* if(invalidvarcomb[k]){ */
11742: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
11743: /* continue; */
11744: /* } */
1.268 brouard 11745: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 11746: for(j=1;j<=cptcovs;j++){
11747: /* for(j=1;j<=cptcoveff;j++) { */
11748: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11749: /* } */
11750: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 11751: }
1.351 brouard 11752: /* fprintf(ficrespij,"******\n"); */
11753: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11754: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11755: /* } */
1.267 brouard 11756: fprintf(ficresfb," yearbproj age");
11757: for(j=1; j<=nlstate+ndeath;j++){
11758: for(i=1; i<=nlstate;i++)
1.268 brouard 11759: fprintf(ficresfb," b%d%d",i,j);
11760: fprintf(ficresfb," b.%d",j);
1.267 brouard 11761: }
1.296 brouard 11762: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 11763: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
11764: fprintf(ficresfb,"\n");
1.296 brouard 11765: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 11766: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 11767: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
11768: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 11769: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 11770: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 11771: nhstepm = nhstepm/hstepm;
11772: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11773: oldm=oldms;savm=savms;
1.268 brouard 11774: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 11775: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 11776: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 11777: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
11778: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
11779: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 11780: for (h=0; h<=nhstepm; h++){
1.268 brouard 11781: if (h*hstepm/YEARM*stepm ==-yearp) {
11782: break;
11783: }
11784: }
11785: fprintf(ficresfb,"\n");
1.351 brouard 11786: /* for(j=1;j<=cptcoveff;j++) */
11787: for(j=1;j<=cptcovs;j++)
11788: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11789: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 11790: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 11791: for(i=1; i<=nlstate+ndeath;i++) {
11792: ppij=0.;ppi=0.;
11793: for(j=1; j<=nlstate;j++) {
11794: /* if (mobilav==1) */
1.269 brouard 11795: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
11796: ppi=ppi+prevacurrent[(int)agec][j][k];
11797: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
11798: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 11799: /* else { */
11800: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
11801: /* } */
1.268 brouard 11802: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
11803: } /* end j */
11804: if(ppi <0.99){
11805: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
11806: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
11807: }
11808: fprintf(ficresfb," %.3f", ppij);
11809: }/* end j */
1.267 brouard 11810: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11811: } /* end agec */
11812: } /* end yearp */
11813: } /* end k */
1.217 brouard 11814:
1.267 brouard 11815: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 11816:
1.267 brouard 11817: fclose(ficresfb);
11818: printf("End of Computing Back forecasting \n");
11819: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 11820:
1.267 brouard 11821: }
1.217 brouard 11822:
1.269 brouard 11823: /* Variance of prevalence limit: varprlim */
11824: void varprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **prlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
1.288 brouard 11825: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 11826:
11827: char fileresvpl[FILENAMELENGTH];
11828: FILE *ficresvpl;
11829: double **oldm, **savm;
11830: double **varpl; /* Variances of prevalence limits by age */
11831: int i1, k, nres, j ;
11832:
11833: strcpy(fileresvpl,"VPL_");
11834: strcat(fileresvpl,fileresu);
11835: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 11836: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 11837: exit(0);
11838: }
1.288 brouard 11839: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
11840: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 11841:
11842: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11843: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
11844:
11845: i1=pow(2,cptcoveff);
11846: if (cptcovn < 1){i1=1;}
11847:
1.337 brouard 11848: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11849: k=TKresult[nres];
1.338 brouard 11850: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11851: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 11852: if(i1 != 1 && TKresult[nres]!= k)
11853: continue;
11854: fprintf(ficresvpl,"\n#****** ");
11855: printf("\n#****** ");
11856: fprintf(ficlog,"\n#****** ");
1.337 brouard 11857: for(j=1;j<=cptcovs;j++) {
11858: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11859: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11860: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11861: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11862: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 11863: }
1.337 brouard 11864: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11865: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11866: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11867: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11868: /* } */
1.269 brouard 11869: fprintf(ficresvpl,"******\n");
11870: printf("******\n");
11871: fprintf(ficlog,"******\n");
11872:
11873: varpl=matrix(1,nlstate,(int) bage, (int) fage);
11874: oldm=oldms;savm=savms;
11875: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
11876: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
11877: /*}*/
11878: }
11879:
11880: fclose(ficresvpl);
1.288 brouard 11881: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
11882: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 11883:
11884: }
11885: /* Variance of back prevalence: varbprlim */
11886: void varbprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **bprlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
11887: /*------- Variance of back (stable) prevalence------*/
11888:
11889: char fileresvbl[FILENAMELENGTH];
11890: FILE *ficresvbl;
11891:
11892: double **oldm, **savm;
11893: double **varbpl; /* Variances of back prevalence limits by age */
11894: int i1, k, nres, j ;
11895:
11896: strcpy(fileresvbl,"VBL_");
11897: strcat(fileresvbl,fileresu);
11898: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
11899: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
11900: exit(0);
11901: }
11902: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
11903: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
11904:
11905:
11906: i1=pow(2,cptcoveff);
11907: if (cptcovn < 1){i1=1;}
11908:
1.337 brouard 11909: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11910: k=TKresult[nres];
1.338 brouard 11911: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11912: /* for(k=1; k<=i1;k++){ */
11913: /* if(i1 != 1 && TKresult[nres]!= k) */
11914: /* continue; */
1.269 brouard 11915: fprintf(ficresvbl,"\n#****** ");
11916: printf("\n#****** ");
11917: fprintf(ficlog,"\n#****** ");
1.337 brouard 11918: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 11919: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
11920: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
11921: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 11922: /* for(j=1;j<=cptcoveff;j++) { */
11923: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11924: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11925: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11926: /* } */
11927: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11928: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11929: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11930: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 11931: }
11932: fprintf(ficresvbl,"******\n");
11933: printf("******\n");
11934: fprintf(ficlog,"******\n");
11935:
11936: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
11937: oldm=oldms;savm=savms;
11938:
11939: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
11940: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
11941: /*}*/
11942: }
11943:
11944: fclose(ficresvbl);
11945: printf("done variance-covariance of back prevalence\n");fflush(stdout);
11946: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
11947:
11948: } /* End of varbprlim */
11949:
1.126 brouard 11950: /************** Forecasting *****not tested NB*************/
1.227 brouard 11951: /* void populforecast(char fileres[], double anpyram,double mpyram,double jpyram,double ageminpar, double agemax,double dateprev1, double dateprev2s, int mobilav, double agedeb, double fage, int popforecast, char popfile[], double anpyram1,double p[], int i2){ */
1.126 brouard 11952:
1.227 brouard 11953: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
11954: /* int *popage; */
11955: /* double calagedatem, agelim, kk1, kk2; */
11956: /* double *popeffectif,*popcount; */
11957: /* double ***p3mat,***tabpop,***tabpopprev; */
11958: /* /\* double ***mobaverage; *\/ */
11959: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 11960:
1.227 brouard 11961: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
11962: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
11963: /* agelim=AGESUP; */
11964: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 11965:
1.227 brouard 11966: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 11967:
11968:
1.227 brouard 11969: /* strcpy(filerespop,"POP_"); */
11970: /* strcat(filerespop,fileresu); */
11971: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
11972: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
11973: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
11974: /* } */
11975: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
11976: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 11977:
1.227 brouard 11978: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 11979:
1.227 brouard 11980: /* /\* if (mobilav!=0) { *\/ */
11981: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
11982: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
11983: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
11984: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
11985: /* /\* } *\/ */
11986: /* /\* } *\/ */
1.126 brouard 11987:
1.227 brouard 11988: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
11989: /* if (stepm<=12) stepsize=1; */
1.126 brouard 11990:
1.227 brouard 11991: /* agelim=AGESUP; */
1.126 brouard 11992:
1.227 brouard 11993: /* hstepm=1; */
11994: /* hstepm=hstepm/stepm; */
1.218 brouard 11995:
1.227 brouard 11996: /* if (popforecast==1) { */
11997: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
11998: /* printf("Problem with population file : %s\n",popfile);exit(0); */
11999: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
12000: /* } */
12001: /* popage=ivector(0,AGESUP); */
12002: /* popeffectif=vector(0,AGESUP); */
12003: /* popcount=vector(0,AGESUP); */
1.126 brouard 12004:
1.227 brouard 12005: /* i=1; */
12006: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 12007:
1.227 brouard 12008: /* imx=i; */
12009: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
12010: /* } */
1.218 brouard 12011:
1.227 brouard 12012: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
12013: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
12014: /* k=k+1; */
12015: /* fprintf(ficrespop,"\n#******"); */
12016: /* for(j=1;j<=cptcoveff;j++) { */
12017: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
12018: /* } */
12019: /* fprintf(ficrespop,"******\n"); */
12020: /* fprintf(ficrespop,"# Age"); */
12021: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
12022: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 12023:
1.227 brouard 12024: /* for (cpt=0; cpt<=0;cpt++) { */
12025: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 12026:
1.227 brouard 12027: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
12028: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
12029: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 12030:
1.227 brouard 12031: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12032: /* oldm=oldms;savm=savms; */
12033: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 12034:
1.227 brouard 12035: /* for (h=0; h<=nhstepm; h++){ */
12036: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
12037: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
12038: /* } */
12039: /* for(j=1; j<=nlstate+ndeath;j++) { */
12040: /* kk1=0.;kk2=0; */
12041: /* for(i=1; i<=nlstate;i++) { */
12042: /* if (mobilav==1) */
12043: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
12044: /* else { */
12045: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
12046: /* } */
12047: /* } */
12048: /* if (h==(int)(calagedatem+12*cpt)){ */
12049: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
12050: /* /\*fprintf(ficrespop," %.3f", kk1); */
12051: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
12052: /* } */
12053: /* } */
12054: /* for(i=1; i<=nlstate;i++){ */
12055: /* kk1=0.; */
12056: /* for(j=1; j<=nlstate;j++){ */
12057: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
12058: /* } */
12059: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
12060: /* } */
1.218 brouard 12061:
1.227 brouard 12062: /* if (h==(int)(calagedatem+12*cpt)) */
12063: /* for(j=1; j<=nlstate;j++) */
12064: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
12065: /* } */
12066: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12067: /* } */
12068: /* } */
1.218 brouard 12069:
1.227 brouard 12070: /* /\******\/ */
1.218 brouard 12071:
1.227 brouard 12072: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
12073: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
12074: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
12075: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
12076: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 12077:
1.227 brouard 12078: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12079: /* oldm=oldms;savm=savms; */
12080: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12081: /* for (h=0; h<=nhstepm; h++){ */
12082: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
12083: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
12084: /* } */
12085: /* for(j=1; j<=nlstate+ndeath;j++) { */
12086: /* kk1=0.;kk2=0; */
12087: /* for(i=1; i<=nlstate;i++) { */
12088: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
12089: /* } */
12090: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
12091: /* } */
12092: /* } */
12093: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12094: /* } */
12095: /* } */
12096: /* } */
12097: /* } */
1.218 brouard 12098:
1.227 brouard 12099: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 12100:
1.227 brouard 12101: /* if (popforecast==1) { */
12102: /* free_ivector(popage,0,AGESUP); */
12103: /* free_vector(popeffectif,0,AGESUP); */
12104: /* free_vector(popcount,0,AGESUP); */
12105: /* } */
12106: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
12107: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
12108: /* fclose(ficrespop); */
12109: /* } /\* End of popforecast *\/ */
1.218 brouard 12110:
1.126 brouard 12111: int fileappend(FILE *fichier, char *optionfich)
12112: {
12113: if((fichier=fopen(optionfich,"a"))==NULL) {
12114: printf("Problem with file: %s\n", optionfich);
12115: fprintf(ficlog,"Problem with file: %s\n", optionfich);
12116: return (0);
12117: }
12118: fflush(fichier);
12119: return (1);
12120: }
12121:
12122:
12123: /**************** function prwizard **********************/
12124: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
12125: {
12126:
12127: /* Wizard to print covariance matrix template */
12128:
1.164 brouard 12129: char ca[32], cb[32];
12130: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 12131: int numlinepar;
12132:
12133: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12134: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12135: for(i=1; i <=nlstate; i++){
12136: jj=0;
12137: for(j=1; j <=nlstate+ndeath; j++){
12138: if(j==i) continue;
12139: jj++;
12140: /*ca[0]= k+'a'-1;ca[1]='\0';*/
12141: printf("%1d%1d",i,j);
12142: fprintf(ficparo,"%1d%1d",i,j);
12143: for(k=1; k<=ncovmodel;k++){
12144: /* printf(" %lf",param[i][j][k]); */
12145: /* fprintf(ficparo," %lf",param[i][j][k]); */
12146: printf(" 0.");
12147: fprintf(ficparo," 0.");
12148: }
12149: printf("\n");
12150: fprintf(ficparo,"\n");
12151: }
12152: }
12153: printf("# Scales (for hessian or gradient estimation)\n");
12154: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
12155: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
12156: for(i=1; i <=nlstate; i++){
12157: jj=0;
12158: for(j=1; j <=nlstate+ndeath; j++){
12159: if(j==i) continue;
12160: jj++;
12161: fprintf(ficparo,"%1d%1d",i,j);
12162: printf("%1d%1d",i,j);
12163: fflush(stdout);
12164: for(k=1; k<=ncovmodel;k++){
12165: /* printf(" %le",delti3[i][j][k]); */
12166: /* fprintf(ficparo," %le",delti3[i][j][k]); */
12167: printf(" 0.");
12168: fprintf(ficparo," 0.");
12169: }
12170: numlinepar++;
12171: printf("\n");
12172: fprintf(ficparo,"\n");
12173: }
12174: }
12175: printf("# Covariance matrix\n");
12176: /* # 121 Var(a12)\n\ */
12177: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12178: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12179: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12180: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12181: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12182: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12183: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12184: fflush(stdout);
12185: fprintf(ficparo,"# Covariance matrix\n");
12186: /* # 121 Var(a12)\n\ */
12187: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12188: /* # ...\n\ */
12189: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12190:
12191: for(itimes=1;itimes<=2;itimes++){
12192: jj=0;
12193: for(i=1; i <=nlstate; i++){
12194: for(j=1; j <=nlstate+ndeath; j++){
12195: if(j==i) continue;
12196: for(k=1; k<=ncovmodel;k++){
12197: jj++;
12198: ca[0]= k+'a'-1;ca[1]='\0';
12199: if(itimes==1){
12200: printf("#%1d%1d%d",i,j,k);
12201: fprintf(ficparo,"#%1d%1d%d",i,j,k);
12202: }else{
12203: printf("%1d%1d%d",i,j,k);
12204: fprintf(ficparo,"%1d%1d%d",i,j,k);
12205: /* printf(" %.5le",matcov[i][j]); */
12206: }
12207: ll=0;
12208: for(li=1;li <=nlstate; li++){
12209: for(lj=1;lj <=nlstate+ndeath; lj++){
12210: if(lj==li) continue;
12211: for(lk=1;lk<=ncovmodel;lk++){
12212: ll++;
12213: if(ll<=jj){
12214: cb[0]= lk +'a'-1;cb[1]='\0';
12215: if(ll<jj){
12216: if(itimes==1){
12217: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12218: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12219: }else{
12220: printf(" 0.");
12221: fprintf(ficparo," 0.");
12222: }
12223: }else{
12224: if(itimes==1){
12225: printf(" Var(%s%1d%1d)",ca,i,j);
12226: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
12227: }else{
12228: printf(" 0.");
12229: fprintf(ficparo," 0.");
12230: }
12231: }
12232: }
12233: } /* end lk */
12234: } /* end lj */
12235: } /* end li */
12236: printf("\n");
12237: fprintf(ficparo,"\n");
12238: numlinepar++;
12239: } /* end k*/
12240: } /*end j */
12241: } /* end i */
12242: } /* end itimes */
12243:
12244: } /* end of prwizard */
12245: /******************* Gompertz Likelihood ******************************/
12246: double gompertz(double x[])
12247: {
1.302 brouard 12248: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 12249: int i,n=0; /* n is the size of the sample */
12250:
1.220 brouard 12251: for (i=1;i<=imx ; i++) {
1.126 brouard 12252: sump=sump+weight[i];
12253: /* sump=sump+1;*/
12254: num=num+1;
12255: }
1.302 brouard 12256: L=0.0;
12257: /* agegomp=AGEGOMP; */
1.126 brouard 12258: /* for (i=0; i<=imx; i++)
12259: if (wav[i]>0) printf("i=%d ageex=%lf agecens=%lf agedc=%lf cens=%d %d\n" ,i,ageexmed[i],agecens[i],agedc[i],cens[i],wav[i]);*/
12260:
1.302 brouard 12261: for (i=1;i<=imx ; i++) {
12262: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
12263: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
12264: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
12265: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
12266: * +
12267: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
12268: */
12269: if (wav[i] > 1 || agedc[i] < AGESUP) {
12270: if (cens[i] == 1){
12271: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
12272: } else if (cens[i] == 0){
1.126 brouard 12273: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 12274: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
12275: } else
12276: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 12277: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 12278: L=L+A*weight[i];
1.126 brouard 12279: /* printf("\ni=%d A=%f L=%lf x[1]=%lf x[2]=%lf ageex=%lf agecens=%lf cens=%d agedc=%lf weight=%lf\n",i,A,L,x[1],x[2],ageexmed[i]*12,agecens[i]*12,cens[i],agedc[i]*12,weight[i]);*/
1.302 brouard 12280: }
12281: }
1.126 brouard 12282:
1.302 brouard 12283: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 12284:
12285: return -2*L*num/sump;
12286: }
12287:
1.136 brouard 12288: #ifdef GSL
12289: /******************* Gompertz_f Likelihood ******************************/
12290: double gompertz_f(const gsl_vector *v, void *params)
12291: {
1.302 brouard 12292: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 12293: double *x= (double *) v->data;
12294: int i,n=0; /* n is the size of the sample */
12295:
12296: for (i=0;i<=imx-1 ; i++) {
12297: sump=sump+weight[i];
12298: /* sump=sump+1;*/
12299: num=num+1;
12300: }
12301:
12302:
12303: /* for (i=0; i<=imx; i++)
12304: if (wav[i]>0) printf("i=%d ageex=%lf agecens=%lf agedc=%lf cens=%d %d\n" ,i,ageexmed[i],agecens[i],agedc[i],cens[i],wav[i]);*/
12305: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
12306: for (i=1;i<=imx ; i++)
12307: {
12308: if (cens[i] == 1 && wav[i]>1)
12309: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
12310:
12311: if (cens[i] == 0 && wav[i]>1)
12312: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
12313: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
12314:
12315: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
12316: if (wav[i] > 1 ) { /* ??? */
12317: LL=LL+A*weight[i];
12318: /* printf("\ni=%d A=%f L=%lf x[1]=%lf x[2]=%lf ageex=%lf agecens=%lf cens=%d agedc=%lf weight=%lf\n",i,A,L,x[1],x[2],ageexmed[i]*12,agecens[i]*12,cens[i],agedc[i]*12,weight[i]);*/
12319: }
12320: }
12321:
12322: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
12323: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
12324:
12325: return -2*LL*num/sump;
12326: }
12327: #endif
12328:
1.126 brouard 12329: /******************* Printing html file ***********/
1.201 brouard 12330: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 12331: int lastpass, int stepm, int weightopt, char model[],\
12332: int imx, double p[],double **matcov,double agemortsup){
12333: int i,k;
12334:
12335: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
12336: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
12337: for (i=1;i<=2;i++)
12338: fprintf(fichtm," p[%d] = %lf [%f ; %f]<br>\n",i,p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.199 brouard 12339: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 12340: fprintf(fichtm,"</ul>");
12341:
12342: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
12343:
12344: fprintf(fichtm,"\nAge l<inf>x</inf> q<inf>x</inf> d(x,x+1) L<inf>x</inf> T<inf>x</inf> e<infx</inf><br>");
12345:
12346: for (k=agegomp;k<(agemortsup-2);k++)
12347: fprintf(fichtm,"%d %.0lf %lf %.0lf %.0lf %.0lf %lf<br>\n",k,lsurv[k],p[1]*exp(p[2]*(k-agegomp)),(p[1]*exp(p[2]*(k-agegomp)))*lsurv[k],lpop[k],tpop[k],tpop[k]/lsurv[k]);
12348:
12349:
12350: fflush(fichtm);
12351: }
12352:
12353: /******************* Gnuplot file **************/
1.201 brouard 12354: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 12355:
12356: char dirfileres[132],optfileres[132];
1.164 brouard 12357:
1.359 brouard 12358: /*int ng;*/
1.126 brouard 12359:
12360:
12361: /*#ifdef windows */
12362: fprintf(ficgp,"cd \"%s\" \n",pathc);
12363: /*#endif */
12364:
12365:
12366: strcpy(dirfileres,optionfilefiname);
12367: strcpy(optfileres,"vpl");
1.199 brouard 12368: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 12369: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 12370: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 12371: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 12372: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
12373:
12374: }
12375:
1.136 brouard 12376: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
12377: {
1.126 brouard 12378:
1.136 brouard 12379: /*-------- data file ----------*/
12380: FILE *fic;
12381: char dummy[]=" ";
1.359 brouard 12382: int i = 0, j = 0, n = 0, iv = 0;/* , v;*/
1.223 brouard 12383: int lstra;
1.136 brouard 12384: int linei, month, year,iout;
1.302 brouard 12385: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 12386: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 12387: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 12388: char *stratrunc;
1.223 brouard 12389:
1.349 brouard 12390: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
12391: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 12392:
12393: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
12394:
1.136 brouard 12395: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 12396: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
12397: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 12398: }
1.126 brouard 12399:
1.302 brouard 12400: /* Is it a BOM UTF-8 Windows file? */
12401: /* First data line */
12402: linei=0;
12403: while(fgets(line, MAXLINE, fic)) {
12404: noffset=0;
12405: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12406: {
12407: noffset=noffset+3;
12408: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
12409: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
12410: fflush(ficlog); return 1;
12411: }
12412: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12413: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
12414: {
12415: noffset=noffset+2;
1.304 brouard 12416: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
12417: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 12418: fflush(ficlog); return 1;
12419: }
12420: else if( line[0] == 0 && line[1] == 0)
12421: {
12422: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12423: noffset=noffset+4;
1.304 brouard 12424: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
12425: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 12426: fflush(ficlog); return 1;
12427: }
12428: } else{
12429: ;/*printf(" Not a BOM file\n");*/
12430: }
12431: /* If line starts with a # it is a comment */
12432: if (line[noffset] == '#') {
12433: linei=linei+1;
12434: break;
12435: }else{
12436: break;
12437: }
12438: }
12439: fclose(fic);
12440: if((fic=fopen(datafile,"r"))==NULL) {
12441: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
12442: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
12443: }
12444: /* Not a Bom file */
12445:
1.136 brouard 12446: i=1;
12447: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
12448: linei=linei+1;
12449: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
12450: if(line[j] == '\t')
12451: line[j] = ' ';
12452: }
12453: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
12454: ;
12455: };
12456: line[j+1]=0; /* Trims blanks at end of line */
12457: if(line[0]=='#'){
12458: fprintf(ficlog,"Comment line\n%s\n",line);
12459: printf("Comment line\n%s\n",line);
12460: continue;
12461: }
12462: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 12463: strcpy(line, linetmp);
1.223 brouard 12464:
12465: /* Loops on waves */
12466: for (j=maxwav;j>=1;j--){
12467: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 12468: cutv(stra, strb, line, ' ');
12469: if(strb[0]=='.') { /* Missing value */
12470: lval=-1;
12471: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 12472: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 12473: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
12474: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. If missing, you should remove this individual or impute a value. Exiting.\n", strb, linei,i,line,iv, nqtv, j);
12475: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. If missing, you should remove this individual or impute a value. Exiting.\n", strb, linei,i,line,iv, nqtv, j);fflush(ficlog);
12476: return 1;
12477: }
12478: }else{
12479: errno=0;
12480: /* what_kind_of_number(strb); */
12481: dval=strtod(strb,&endptr);
12482: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
12483: /* if(strb != endptr && *endptr == '\0') */
12484: /* dval=dlval; */
12485: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
12486: if( strb[0]=='\0' || (*endptr != '\0')){
12487: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, nqtv, j,maxwav);
12488: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqtv, j,maxwav);fflush(ficlog);
12489: return 1;
12490: }
12491: cotqvar[j][iv][i]=dval;
1.341 brouard 12492: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 12493: }
12494: strcpy(line,stra);
1.223 brouard 12495: }/* end loop ntqv */
1.225 brouard 12496:
1.223 brouard 12497: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 12498: cutv(stra, strb, line, ' ');
12499: if(strb[0]=='.') { /* Missing value */
12500: lval=-1;
12501: }else{
12502: errno=0;
12503: lval=strtol(strb,&endptr,10);
12504: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
12505: if( strb[0]=='\0' || (*endptr != '\0')){
12506: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th dummy covariate out of %d measured at wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, ntv, j,maxwav);
12507: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d dummy covariate out of %d measured wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, ntv,j,maxwav);fflush(ficlog);
12508: return 1;
12509: }
12510: }
12511: if(lval <-1 || lval >1){
12512: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 12513: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 12514: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 12515: For example, for multinomial values like 1, 2 and 3,\n \
12516: build V1=0 V2=0 for the reference value (1),\n \
12517: V1=1 V2=0 for (2) \n \
1.223 brouard 12518: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 12519: output of IMaCh is often meaningless.\n \
1.319 brouard 12520: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 12521: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 12522: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 12523: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 12524: For example, for multinomial values like 1, 2 and 3,\n \
12525: build V1=0 V2=0 for the reference value (1),\n \
12526: V1=1 V2=0 for (2) \n \
1.223 brouard 12527: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 12528: output of IMaCh is often meaningless.\n \
1.319 brouard 12529: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 12530: return 1;
12531: }
1.341 brouard 12532: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 12533: strcpy(line,stra);
1.223 brouard 12534: }/* end loop ntv */
1.225 brouard 12535:
1.223 brouard 12536: /* Statuses at wave */
1.137 brouard 12537: cutv(stra, strb, line, ' ');
1.223 brouard 12538: if(strb[0]=='.') { /* Missing value */
1.238 brouard 12539: lval=-1;
1.136 brouard 12540: }else{
1.238 brouard 12541: errno=0;
12542: lval=strtol(strb,&endptr,10);
12543: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 12544: if( strb[0]=='\0' || (*endptr != '\0' )){
12545: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a status of wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,j,maxwav);
12546: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a status of wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,j,maxwav);fflush(ficlog);
12547: return 1;
12548: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 12549: printf("Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile);fflush(stdout);
12550: fprintf(ficlog,"Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile); fflush(ficlog);
1.238 brouard 12551: return 1;
12552: }
1.136 brouard 12553: }
1.225 brouard 12554:
1.136 brouard 12555: s[j][i]=lval;
1.225 brouard 12556:
1.223 brouard 12557: /* Date of Interview */
1.136 brouard 12558: strcpy(line,stra);
12559: cutv(stra, strb,line,' ');
1.169 brouard 12560: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12561: }
1.169 brouard 12562: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 12563: month=99;
12564: year=9999;
1.136 brouard 12565: }else{
1.225 brouard 12566: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of interview (mm/yyyy or .) at wave %d. Exiting.\n",strb, linei,i, line,j);
12567: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of interview (mm/yyyy or .) at wave %d. Exiting.\n",strb, linei,i, line,j);fflush(ficlog);
12568: return 1;
1.136 brouard 12569: }
12570: anint[j][i]= (double) year;
1.302 brouard 12571: mint[j][i]= (double)month;
12572: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
12573: /* printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
12574: /* fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
12575: /* } */
1.136 brouard 12576: strcpy(line,stra);
1.223 brouard 12577: } /* End loop on waves */
1.225 brouard 12578:
1.223 brouard 12579: /* Date of death */
1.136 brouard 12580: cutv(stra, strb,line,' ');
1.169 brouard 12581: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12582: }
1.169 brouard 12583: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 12584: month=99;
12585: year=9999;
12586: }else{
1.141 brouard 12587: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of death (mm/yyyy or .). Exiting.\n",strb, linei,i,line);
1.225 brouard 12588: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of death (mm/yyyy or .). Exiting.\n",strb, linei,i,line);fflush(ficlog);
12589: return 1;
1.136 brouard 12590: }
12591: andc[i]=(double) year;
12592: moisdc[i]=(double) month;
12593: strcpy(line,stra);
12594:
1.223 brouard 12595: /* Date of birth */
1.136 brouard 12596: cutv(stra, strb,line,' ');
1.169 brouard 12597: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12598: }
1.169 brouard 12599: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 12600: month=99;
12601: year=9999;
12602: }else{
1.141 brouard 12603: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy or .). Exiting.\n",strb, linei,i,line);
12604: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy or .). Exiting.\n",strb, linei,i,line);fflush(ficlog);
1.225 brouard 12605: return 1;
1.136 brouard 12606: }
12607: if (year==9999) {
1.141 brouard 12608: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy) but at least the year of birth should be given. Exiting.\n",strb, linei,i,line);
12609: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy) but at least the year of birth should be given. Exiting.\n",strb, linei,i,line);fflush(ficlog);
1.225 brouard 12610: return 1;
12611:
1.136 brouard 12612: }
12613: annais[i]=(double)(year);
1.302 brouard 12614: moisnais[i]=(double)(month);
12615: for (j=1;j<=maxwav;j++){
12616: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
12617: printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j,(int)moisnais[i],(int)annais[i]);
12618: fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j, (int)moisnais[i],(int)annais[i]);
12619: }
12620: }
12621:
1.136 brouard 12622: strcpy(line,stra);
1.225 brouard 12623:
1.223 brouard 12624: /* Sample weight */
1.136 brouard 12625: cutv(stra, strb,line,' ');
12626: errno=0;
12627: dval=strtod(strb,&endptr);
12628: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 12629: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
12630: fprintf(ficlog,"Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
1.136 brouard 12631: fflush(ficlog);
12632: return 1;
12633: }
12634: weight[i]=dval;
12635: strcpy(line,stra);
1.225 brouard 12636:
1.223 brouard 12637: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
12638: cutv(stra, strb, line, ' ');
12639: if(strb[0]=='.') { /* Missing value */
1.225 brouard 12640: lval=-1;
1.311 brouard 12641: coqvar[iv][i]=NAN;
12642: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 12643: }else{
1.225 brouard 12644: errno=0;
12645: /* what_kind_of_number(strb); */
12646: dval=strtod(strb,&endptr);
12647: /* if(strb != endptr && *endptr == '\0') */
12648: /* dval=dlval; */
12649: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
12650: if( strb[0]=='\0' || (*endptr != '\0')){
12651: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value (out of %d) constant for all waves. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqv, maxwav);
12652: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value (out of %d) constant for all waves. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqv, maxwav);fflush(ficlog);
12653: return 1;
12654: }
12655: coqvar[iv][i]=dval;
1.226 brouard 12656: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 12657: }
12658: strcpy(line,stra);
12659: }/* end loop nqv */
1.136 brouard 12660:
1.223 brouard 12661: /* Covariate values */
1.136 brouard 12662: for (j=ncovcol;j>=1;j--){
12663: cutv(stra, strb,line,' ');
1.223 brouard 12664: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 12665: lval=-1;
1.136 brouard 12666: }else{
1.225 brouard 12667: errno=0;
12668: lval=strtol(strb,&endptr,10);
12669: if( strb[0]=='\0' || (*endptr != '\0')){
12670: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\nShould be a covariate value (=0 for the reference or 1 for alternative). Exiting.\n",lval, linei,i, line);
12671: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\nShould be a covariate value (=0 for the reference or 1 for alternative). Exiting.\n",lval, linei,i, line);fflush(ficlog);
12672: return 1;
12673: }
1.136 brouard 12674: }
12675: if(lval <-1 || lval >1){
1.225 brouard 12676: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 12677: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
12678: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 12679: For example, for multinomial values like 1, 2 and 3,\n \
12680: build V1=0 V2=0 for the reference value (1),\n \
12681: V1=1 V2=0 for (2) \n \
1.136 brouard 12682: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 12683: output of IMaCh is often meaningless.\n \
1.136 brouard 12684: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 12685: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 12686: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
12687: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 12688: For example, for multinomial values like 1, 2 and 3,\n \
12689: build V1=0 V2=0 for the reference value (1),\n \
12690: V1=1 V2=0 for (2) \n \
1.136 brouard 12691: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 12692: output of IMaCh is often meaningless.\n \
1.136 brouard 12693: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 12694: return 1;
1.136 brouard 12695: }
12696: covar[j][i]=(double)(lval);
12697: strcpy(line,stra);
12698: }
12699: lstra=strlen(stra);
1.225 brouard 12700:
1.136 brouard 12701: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
12702: stratrunc = &(stra[lstra-9]);
12703: num[i]=atol(stratrunc);
12704: }
12705: else
12706: num[i]=atol(stra);
12707: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
12708: printf("%ld %.lf %.lf %.lf %.lf/%.lf %.lf/%.lf %.lf/%.lf %d %.lf/%.lf %d %.lf/%.lf %d %.lf/%.lf %d\n",num[i],(covar[1][i]), (covar[2][i]),weight[i], (moisnais[i]), (annais[i]), (moisdc[i]), (andc[i]), (mint[1][i]), (anint[1][i]), (s[1][i]), (mint[2][i]), (anint[2][i]), (s[2][i]), (mint[3][i]), (anint[3][i]), (s[3][i]), (mint[4][i]), (anint[4][i]), (s[4][i])); ij=ij+1;}*/
12709:
12710: i=i+1;
12711: } /* End loop reading data */
1.225 brouard 12712:
1.136 brouard 12713: *imax=i-1; /* Number of individuals */
12714: fclose(fic);
1.225 brouard 12715:
1.136 brouard 12716: return (0);
1.164 brouard 12717: /* endread: */
1.225 brouard 12718: printf("Exiting readdata: ");
12719: fclose(fic);
12720: return (1);
1.223 brouard 12721: }
1.126 brouard 12722:
1.234 brouard 12723: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 12724: char *p1 = *stri, *p2 = *stri;
1.235 brouard 12725: while (*p2 == ' ')
1.234 brouard 12726: p2++;
12727: /* while ((*p1++ = *p2++) !=0) */
12728: /* ; */
12729: /* do */
12730: /* while (*p2 == ' ') */
12731: /* p2++; */
12732: /* while (*p1++ == *p2++); */
12733: *stri=p2;
1.145 brouard 12734: }
12735:
1.330 brouard 12736: int decoderesult( char resultline[], int nres)
1.230 brouard 12737: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
12738: {
1.235 brouard 12739: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 12740: char resultsav[MAXLINE];
1.330 brouard 12741: /* int resultmodel[MAXLINE]; */
1.334 brouard 12742: /* int modelresult[MAXLINE]; */
1.230 brouard 12743: char stra[80], strb[80], strc[80], strd[80],stre[80];
12744:
1.234 brouard 12745: removefirstspace(&resultline);
1.332 brouard 12746: printf("decoderesult:%s\n",resultline);
1.230 brouard 12747:
1.332 brouard 12748: strcpy(resultsav,resultline);
1.342 brouard 12749: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 12750: if (strlen(resultsav) >1){
1.334 brouard 12751: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 12752: }
1.353 brouard 12753: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 12754: TKresult[nres]=0; /* Combination for the nresult and the model */
12755: return (0);
12756: }
1.234 brouard 12757: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 brouard 12758: fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(ficlog);
12759: printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(stdout);
12760: if(j==0)
12761: return 1;
1.234 brouard 12762: }
1.334 brouard 12763: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 12764: if(nbocc(resultsav,'=') >1){
1.318 brouard 12765: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' ' (stra is the rest of the resultline to be analyzed in the next loop *//* resultsav= "V4=1 V5=25.1 V3=0" stra= "V5=25.1 V3=0" strb= "V4=1" */
1.332 brouard 12766: /* If resultsav= "V4= 1 V5=25.1 V3=0" with a blank then strb="V4=" and stra="1 V5=25.1 V3=0" */
1.318 brouard 12767: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 12768: /* If a blank, then strc="V4=" and strd='\0' */
12769: if(strc[0]=='\0'){
12770: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
12771: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
12772: return 1;
12773: }
1.234 brouard 12774: }else
12775: cutl(strc,strd,resultsav,'=');
1.318 brouard 12776: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 12777:
1.230 brouard 12778: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 12779: Tvarsel[k]=atoi(strc); /* 4 */ /* Tvarsel is the id of the kth covariate in the result line Tvarsel[1] in "V4=1.." is 4.*/
1.230 brouard 12780: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
12781: /* cptcovsel++; */
12782: if (nbocc(stra,'=') >0)
12783: strcpy(resultsav,stra); /* and analyzes it */
12784: }
1.235 brouard 12785: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 12786: /* Feeds resultmodel[nres][k1]=k2 for k1th product covariate with age in the model equation fed by the index k2 of the resutline*/
1.334 brouard 12787: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on MODEL LINE V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.332 brouard 12788: if(Typevar[k1]==0){ /* Single covariate in model */
12789: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 12790: match=0;
1.318 brouard 12791: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12792: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 12793: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 12794: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 12795: break;
12796: }
12797: }
12798: if(match == 0){
1.338 brouard 12799: printf("Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s. Tvar[k1=%d]=%d is different from Tvarsel[k2=%d]=%d.\n",Tvar[k1], resultline, model,k1, Tvar[k1], k2, Tvarsel[k2]);
12800: fprintf(ficlog,"Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s\n",Tvar[k1], resultline, model);
1.310 brouard 12801: return 1;
1.234 brouard 12802: }
1.332 brouard 12803: }else if(Typevar[k1]==1){ /* Product with age We want to get the position k2 in the resultline of the product k1 in the model line*/
12804: /* We feed resultmodel[k1]=k2; */
12805: match=0;
12806: for(k2=1; k2 <=j;k2++){/* Loop on resultline. jth occurence of = signs in the result line. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12807: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 12808: modelresult[nres][k2]=k1;/* we found a Vn=1 corrresponding to Vn*age in the model modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.332 brouard 12809: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 12810: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 12811: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12812: break;
12813: }
12814: }
12815: if(match == 0){
1.338 brouard 12816: printf("Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
12817: fprintf(ficlog,"Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
1.332 brouard 12818: return 1;
12819: }
1.349 brouard 12820: }else if(Typevar[k1]==2 || Typevar[k1]==3){ /* Product with or without age. We want to get the position in the resultline of the product in the model line*/
1.332 brouard 12821: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
12822: match=0;
1.342 brouard 12823: /* printf("Decoderesult very first Product Tvardk[k1=%d][1]=%d Tvardk[k1=%d][2]=%d V%d * V%d\n",k1,Tvardk[k1][1],k1,Tvardk[k1][2],Tvardk[k1][1],Tvardk[k1][2]); */
1.332 brouard 12824: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12825: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
12826: /* modelresult[k2]=k1; */
1.342 brouard 12827: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 12828: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12829: }
12830: }
12831: if(match == 0){
1.349 brouard 12832: printf("Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
12833: fprintf(ficlog,"Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 12834: return 1;
12835: }
12836: match=0;
12837: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12838: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
12839: /* modelresult[k2]=k1;*/
1.342 brouard 12840: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 12841: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12842: break;
12843: }
12844: }
12845: if(match == 0){
1.349 brouard 12846: printf("Error in result line (Product without age second variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
12847: fprintf(ficlog,"Error in result line (Product without age second variable or double product with age): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 12848: return 1;
12849: }
12850: }/* End of testing */
1.333 brouard 12851: }/* End loop cptcovt */
1.235 brouard 12852: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 12853: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 12854: for(k2=1; k2 <=j;k2++){ /* j or cptcovs is the number of single covariates used either in the model line as well as in the result line (dummy or quantitative)
12855: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 12856: match=0;
1.318 brouard 12857: for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.332 brouard 12858: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 12859: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 12860: resultmodel[nres][k1]=k2; /* k1th position in the model equation corresponds to k2th position in the result line. resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.334 brouard 12861: modelresult[nres][k2]=k1; /* k1th position in the model equation corresponds to k2th position in the result line. modelresult[1]=2 modelresult[2]=1 modelresult[3]=3 remodelresult[4]=6 modelresult[5]=9 */
1.234 brouard 12862: ++match;
12863: }
12864: }
12865: }
12866: if(match == 0){
1.338 brouard 12867: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
12868: fprintf(ficlog,"Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
1.310 brouard 12869: return 1;
1.234 brouard 12870: }else if(match > 1){
1.338 brouard 12871: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
12872: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 12873: return 1;
1.234 brouard 12874: }
12875: }
1.334 brouard 12876: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 12877: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 12878: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 12879: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
12880: /* should correspond to the combination 6 of dummy: V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 1*1 + 0*2 + 1*4 = 5 + (1offset) = 6*/
12881: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 12882: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
12883: /* 1 0 0 0 */
12884: /* 2 1 0 0 */
12885: /* 3 0 1 0 */
1.330 brouard 12886: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 12887: /* 5 0 0 1 */
1.330 brouard 12888: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 12889: /* 7 0 1 1 */
12890: /* 8 1 1 1 */
1.237 brouard 12891: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
12892: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
12893: /* V5*age V5 known which value for nres? */
12894: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 12895: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* cptcovt number of covariates (excluding 1 and age or age*age) in the MODEL equation.
12896: * loop on position k1 in the MODEL LINE */
1.331 brouard 12897: /* k counting number of combination of single dummies in the equation model */
12898: /* k4 counting single dummies in the equation model */
12899: /* k4q counting single quantitatives in the equation model */
1.344 brouard 12900: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, fixed or timevarying, k1 is sorting according to MODEL, but k3 to resultline */
1.334 brouard 12901: /* k4+1= (not always if quant in model) position in the resultline V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) */
1.332 brouard 12902: /* modelresult[k3]=k1: k3th position in the result line corresponds to the k1 position in the model line (doesn't work with products)*/
1.330 brouard 12903: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 12904: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
12905: /* k3 is the position in the nres result line of the k1th variable of the model equation */
12906: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
12907: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
12908: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 12909: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 12910: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 12911: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 12912: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
12913: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
12914: k2=(int)Tvarsel[k3]; /* from position k3 in resultline get name k2: nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
1.330 brouard 12915: k+=Tvalsel[k3]*pow(2,k4); /* nres=1 k1=2 Tvalsel[1]=1 (V4=1); k1=3 k3=2 Tvalsel[2]=0 (V3=0) */
1.334 brouard 12916: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 12917: /* Tinvresult[nres][4]=1 */
1.334 brouard 12918: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
12919: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
12920: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
12921: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 12922: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 12923: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 12924: /* printf("Decoderesult Dummy k=%d, k1=%d precov[nres=%d][k1=%d]=%.f V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k1, nres, k1,precov[nres][k1], k2, k3, (int)Tvalsel[k3], k4); */
1.235 brouard 12925: k4++;;
1.331 brouard 12926: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 12927: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 12928: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 12929: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 12930: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
12931: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
12932: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 12933: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
12934: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
12935: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
12936: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
12937: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
12938: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 12939: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 12940: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 12941: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 12942: /* printf("Decoderesult Quantitative nres=%d,precov[nres=%d][k1=%d]=%.f V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, nres, k1,precov[nres][k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.235 brouard 12943: k4q++;;
1.350 brouard 12944: }else if( Dummy[k1]==2 ){ /* For dummy with age product "V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
12945: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 12946: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 12947: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
12948: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
12949: /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */
12950: }else{
12951: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
12952: k2=(int)Tvarsel[k3]; /* nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
12953: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
12954: precov[nres][k1]=Tvalsel[k3];
12955: }
1.342 brouard 12956: /* printf("Decoderesult Dummy with age k=%d, k1=%d precov[nres=%d][k1=%d]=%.f Tvar[%d]=V%d k2=Tvarsel[%d]=%d Tvalsel[%d]=%d\n",k, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k3,(int)Tvarsel[k3], k3, (int)Tvalsel[k3]); */
1.331 brouard 12957: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 12958: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
12959: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
12960: /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */
12961: }else{
12962: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
12963: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
12964: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
12965: precov[nres][k1]=Tvalsel[k3q];
12966: }
1.342 brouard 12967: /* printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.349 brouard 12968: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 12969: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 12970: /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */
1.330 brouard 12971: }else{
1.332 brouard 12972: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
12973: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 12974: }
12975: }
1.234 brouard 12976:
1.334 brouard 12977: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 12978: return (0);
12979: }
1.235 brouard 12980:
1.230 brouard 12981: int decodemodel( char model[], int lastobs)
12982: /**< This routine decodes the model and returns:
1.224 brouard 12983: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
12984: * - nagesqr = 1 if age*age in the model, otherwise 0.
12985: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
12986: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
12987: * - cptcovage number of covariates with age*products =2
12988: * - cptcovs number of simple covariates
1.339 brouard 12989: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 12990: * - Tvar[k] is the id of the kth covariate Tvar[1]@12 {1, 2, 3, 8, 10, 11, 8, 3, 7, 8, 5, 6}, thus Tvar[5=V7*V8]=10
1.339 brouard 12991: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 12992: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 12993: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
12994: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
12995: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
12996: */
1.319 brouard 12997: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.136 brouard 12998: {
1.359 brouard 12999: int i, j, k, ks;/* , v;*/
1.349 brouard 13000: int n,m;
13001: int j1, k1, k11, k12, k2, k3, k4;
13002: char modelsav[300];
13003: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 13004: char *strpt;
1.349 brouard 13005: int **existcomb;
13006:
13007: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
13008: for(i=1;i<=NCOVMAX;i++)
13009: for(j=1;j<=NCOVMAX;j++)
13010: existcomb[i][j]=0;
13011:
1.145 brouard 13012: /*removespace(model);*/
1.136 brouard 13013: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 13014: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 13015: if (strstr(model,"AGE") !=0){
1.192 brouard 13016: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
13017: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 13018: return 1;
13019: }
1.141 brouard 13020: if (strstr(model,"v") !=0){
1.338 brouard 13021: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
13022: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 13023: return 1;
13024: }
1.187 brouard 13025: strcpy(modelsav,model);
13026: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 13027: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 13028: if(strpt != model){
1.338 brouard 13029: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 13030: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 13031: corresponding column of parameters.\n",model);
1.338 brouard 13032: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 13033: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 13034: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 13035: return 1;
1.225 brouard 13036: }
1.187 brouard 13037: nagesqr=1;
13038: if (strstr(model,"+age*age") !=0)
1.234 brouard 13039: substrchaine(modelsav, model, "+age*age");
1.187 brouard 13040: else if (strstr(model,"age*age+") !=0)
1.234 brouard 13041: substrchaine(modelsav, model, "age*age+");
1.187 brouard 13042: else
1.234 brouard 13043: substrchaine(modelsav, model, "age*age");
1.187 brouard 13044: }else
13045: nagesqr=0;
1.349 brouard 13046: if (strlen(modelsav) >1){ /* V2 +V3 +V4 +V6 +V7 +V6*V2 +V7*V2 +V6*V3 +V7*V3 +V6*V4 +V7*V4 +age*V2 +age*V3 +age*V4 +age*V6 +age*V7 +age*V6*V2 +V7*V2 +age*V6*V3 +age*V7*V3 +age*V6*V4 +age*V7*V4 */
1.187 brouard 13047: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
13048: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 13049: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 13050: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 13051: * cst, age and age*age
13052: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
13053: /* including age products which are counted in cptcovage.
13054: * but the covariates which are products must be treated
13055: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 13056: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
13057: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 13058: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 13059: cptcovprodage=0;
13060: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 13061:
1.187 brouard 13062: /* Design
13063: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
13064: * < ncovcol=8 >
13065: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
13066: * k= 1 2 3 4 5 6 7 8
13067: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 13068: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 13069: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
13070: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 13071: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
13072: * Tage[++cptcovage]=k
1.345 brouard 13073: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 13074: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
13075: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
13076: * Tvard[k1][1]=m Tvard[k1][2]=m; Tvard[1][1]=5 (V5) Tvard[1][2]=6 Tvard[2][1]=7 (V7) Tvard[2][2]=8
13077: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
13078: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
13079: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 13080: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 13081: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
13082: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 13083: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
13084: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 13085: * p Tprod[1]@2={ 6, 5}
13086: *p Tvard[1][1]@4= {7, 8, 5, 6}
13087: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
13088: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 13089: *How to reorganize? Tvars(orted)
1.187 brouard 13090: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
13091: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
13092: * {2, 1, 4, 8, 5, 6, 3, 7}
13093: * Struct []
13094: */
1.225 brouard 13095:
1.187 brouard 13096: /* This loop fills the array Tvar from the string 'model'.*/
13097: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
13098: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
13099: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
13100: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
13101: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
13102: /* k=1 Tvar[1]=2 (from V2) */
13103: /* k=5 Tvar[5] */
13104: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 13105: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 13106: /* } */
1.198 brouard 13107: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 13108: /*
13109: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 13110: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
13111: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
13112: }
1.187 brouard 13113: cptcovage=0;
1.351 brouard 13114:
13115: /* First loop in order to calculate */
13116: /* for age*VN*Vm
13117: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
13118: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
13119: */
13120: /* Needs FixedV[Tvardk[k][1]] */
13121: /* For others:
13122: * Sets Typevar[k];
13123: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
13124: * Tposprod[k]=k11;
13125: * Tprod[k11]=k;
13126: * Tvardk[k][1] =m;
13127: * Needs FixedV[Tvardk[k][1]] == 0
13128: */
13129:
1.319 brouard 13130: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
13131: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
13132: modelsav==V2+V1+V5*age+V4+V3*age strb=V3*age stra=V2+V1V5*age+V4 */ /* <model> "V5+V4+V3+V4*V3+V5*age+V1*age+V1" strb="V5" stra="V4+V3+V4*V3+V5*age+V1*age+V1" */
13133: if (nbocc(modelsav,'+')==0)
13134: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 13135: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
13136: /*scanf("%d",i);*/
1.349 brouard 13137: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age OR double product with age strb=age*V6*V2 or V6*V2*age or V6*age*V2 */
13138: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 OR strb=age*V6*V2 strc=V6*V2 strd=age OR c=V2*age OR c=age*V2 */
13139: if(strchr(strc,'*')) { /**< Model with age and DOUBLE product: allowed since 0.99r44, strc=V6*V2 or V2*age or age*V2, strd=age or V6 or V6 */
13140: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
13141: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
13142: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
13143: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
13144: /* We want strb=Vn*Vm */
13145: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
13146: strcpy(strb,strd);
13147: strcat(strb,"*");
13148: strcat(strb,stre);
13149: }else{ /* strf=Vm If strf=V6 then stre=V2 */
13150: strcpy(strb,strf);
13151: strcat(strb,"*");
13152: strcat(strb,stre);
13153: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
13154: }
1.351 brouard 13155: /* printf("DEBUG FIXED k=%d, Tage[k]=%d, Tvar[Tage[k]=%d,FixedV[Tvar[Tage[k]]]=%d\n",k,Tage[k],Tvar[Tage[k]],FixedV[Tvar[Tage[k]]]); */
13156: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 13157: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
13158: strcpy(stre,strb); /* save full b in stre */
13159: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
13160: strcpy(strf,strc); /* save short c in new short f */
13161: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
13162: /* strcpy(strc,stre);*/ /* save full e in c for future */
13163: }
13164: cptcovdageprod++; /* double product with age Which product is it? */
13165: /* strcpy(strb,strc); /\* strb was age*V6*V2 or V6*V2*age or V6*age*V2 IS now V6*V2 or V2*age or age*V2 *\/ */
13166: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 13167: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 13168: n=atoi(stre);
1.234 brouard 13169: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 13170: m=atoi(strc);
13171: cptcovage++; /* Counts the number of covariates which include age as a product */
13172: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
13173: if(existcomb[n][m] == 0){
13174: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
13175: printf("Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
13176: fprintf(ficlog,"Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
13177: fflush(ficlog);
13178: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
13179: k12++;
13180: existcomb[n][m]=k1;
13181: existcomb[m][n]=k1;
13182: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
13183: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2+ age*V6*V3 Gives the k position of the k1 double product Vn*Vm or age*Vn*Vm*/
13184: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
13185: Tvard[k1][1] =m; /* m 1 for V1*/
13186: Tvardk[k][1] =m; /* m 1 for V1*/
13187: Tvard[k1][2] =n; /* n 4 for V4*/
13188: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 13189: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 13190: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
13191: for (i=1; i<=lastobs;i++){/* For fixed product */
13192: /* Computes the new covariate which is a product of
13193: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
13194: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
13195: }
13196: cptcovprodage++; /* Counting the number of fixed covariate with age */
13197: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
13198: k12++;
13199: FixedV[ncovcolt+k12]=0;
13200: }else{ /*End of FixedV */
13201: cptcovprodvage++; /* Counting the number of varying covariate with age */
13202: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
13203: k12++;
13204: FixedV[ncovcolt+k12]=1;
13205: }
13206: }else{ /* k1 Vn*Vm already exists */
13207: k11=existcomb[n][m];
13208: Tposprod[k]=k11; /* OK */
13209: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
13210: Tvardk[k][1]=m;
13211: Tvardk[k][2]=n;
13212: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
13213: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
13214: cptcovprodage++; /* Counting the number of fixed covariate with age */
13215: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
13216: Tvar[Tage[cptcovage]]=k1;
13217: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
13218: k12++;
13219: FixedV[ncovcolt+k12]=0;
13220: }else{ /* Already exists but time varying (and age) */
13221: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
13222: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
13223: /* Tvar[Tage[cptcovage]]=k1; */
13224: cptcovprodvage++;
13225: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
13226: k12++;
13227: FixedV[ncovcolt+k12]=1;
13228: }
13229: }
13230: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
13231: /* Tvar[k]=k11; /\* HERY *\/ */
13232: } else {/* simple product strb=age*Vn so that c=Vn and d=age, or strb=Vn*age so that c=age and d=Vn, or b=Vn*Vm so that c=Vm and d=Vn */
13233: cptcovprod++;
13234: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
13235: /* covar is not filled and then is empty */
13236: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
13237: Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
13238: Typevar[k]=1; /* 1 for age product */
13239: cptcovage++; /* Counts the number of covariates which include age as a product */
13240: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
13241: if( FixedV[Tvar[k]] == 0){
13242: cptcovprodage++; /* Counting the number of fixed covariate with age */
13243: }else{
13244: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
13245: }
13246: /*printf("stre=%s ", stre);*/
13247: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
13248: cutl(stre,strb,strc,'V');
13249: Tvar[k]=atoi(stre);
13250: Typevar[k]=1; /* 1 for age product */
13251: cptcovage++;
13252: Tage[cptcovage]=k;
13253: if( FixedV[Tvar[k]] == 0){
13254: cptcovprodage++; /* Counting the number of fixed covariate with age */
13255: }else{
13256: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 13257: }
1.349 brouard 13258: }else{ /* for product Vn*Vm */
13259: Typevar[k]=2; /* 2 for product Vn*Vm */
13260: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
13261: n=atoi(stre);
13262: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
13263: m=atoi(strc);
13264: k1++;
13265: cptcovprodnoage++;
13266: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
13267: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
13268: fprintf(ficlog,"Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
13269: fflush(ficlog);
13270: k11=existcomb[n][m];
13271: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
13272: Tposprod[k]=k11;
13273: Tprod[k11]=k;
13274: Tvardk[k][1] =m; /* m 1 for V1*/
13275: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
13276: Tvardk[k][2] =n; /* n 4 for V4*/
13277: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
13278: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
13279: existcomb[n][m]=k1;
13280: existcomb[m][n]=k1;
13281: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
13282: because this model-covariate is a construction we invent a new column
13283: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
13284: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
13285: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
13286: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
13287: /* Please remark that the new variables are model dependent */
13288: /* If we have 4 variable but the model uses only 3, like in
13289: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
13290: * k= 1 2 3 4 5 6 7 8
13291: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
13292: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
13293: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
13294: */
13295: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
13296: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
13297: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
13298: Tvard[k1][1] =m; /* m 1 for V1*/
13299: Tvardk[k][1] =m; /* m 1 for V1*/
13300: Tvard[k1][2] =n; /* n 4 for V4*/
13301: Tvardk[k][2] =n; /* n 4 for V4*/
13302: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
13303: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
13304: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
13305: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
13306: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
13307: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
13308: for (i=1; i<=lastobs;i++){/* For fixed product */
13309: /* Computes the new covariate which is a product of
13310: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
13311: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
13312: }
13313: /* TvarVV[k2]=n; */
13314: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13315: /* TvarVV[k2+1]=m; */
13316: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13317: }else{ /* not FixedV */
13318: /* TvarVV[k2]=n; */
13319: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13320: /* TvarVV[k2+1]=m; */
13321: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13322: }
13323: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
13324: } /* End of product Vn*Vm */
13325: } /* End of age*double product or simple product */
13326: }else { /* not a product */
1.234 brouard 13327: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
13328: /* scanf("%d",i);*/
13329: cutl(strd,strc,strb,'V');
13330: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
13331: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
13332: Tvar[k]=atoi(strd);
13333: Typevar[k]=0; /* 0 for simple covariates */
13334: }
13335: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 13336: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 13337: scanf("%d",i);*/
1.187 brouard 13338: } /* end of loop + on total covariates */
1.351 brouard 13339:
13340:
1.187 brouard 13341: } /* end if strlen(modelsave == 0) age*age might exist */
13342: } /* end if strlen(model == 0) */
1.349 brouard 13343: cptcovs=cptcovt - cptcovdageprod - cptcovprod;/**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age + age*v4*V3=> V1 + V3 =4+1-3=2 */
13344:
1.136 brouard 13345: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
13346: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 13347:
1.136 brouard 13348: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 13349: printf("cptcovprod=%d ", cptcovprod);
13350: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
13351: scanf("%d ",i);*/
13352:
13353:
1.230 brouard 13354: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
13355: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 13356: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
13357: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
13358: k = 1 2 3 4 5 6 7 8 9
13359: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 13360: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 13361: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
13362: Dummy[k] 1 0 0 0 3 1 1 2 3
13363: Tmodelind[combination of covar]=k;
1.225 brouard 13364: */
13365: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 13366: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 13367: /* Tvar[k] is the value n of Vn with n varying for 1 to nvcol, or p Vp=Vn*Vm for product */
1.226 brouard 13368: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 13369: printf("Model=1+age+%s\n\
1.349 brouard 13370: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 13371: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
13372: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.318 brouard 13373: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 13374: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 13375: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
13376: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.342 brouard 13377: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
13378: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 13379:
13380:
13381: /* Second loop for calculating Fixed[k], Dummy[k]*/
13382:
13383:
1.349 brouard 13384: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0,ncovva=0,ncovvta=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt loop on k from model */
1.234 brouard 13385: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 13386: Fixed[k]= 0;
13387: Dummy[k]= 0;
1.225 brouard 13388: ncoveff++;
1.232 brouard 13389: ncovf++;
1.234 brouard 13390: nsd++;
13391: modell[k].maintype= FTYPE;
13392: TvarsD[nsd]=Tvar[k];
13393: TvarsDind[nsd]=k;
1.330 brouard 13394: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 13395: TvarF[ncovf]=Tvar[k];
13396: TvarFind[ncovf]=k;
13397: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13398: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 13399: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
1.240 brouard 13400: }else if( Tvar[k] <=ncovcol+nqv && Typevar[k]==0){/* Remind that product Vn*Vm are added in k Only simple fixed quantitative variable */
1.227 brouard 13401: Fixed[k]= 0;
13402: Dummy[k]= 1;
1.230 brouard 13403: nqfveff++;
1.234 brouard 13404: modell[k].maintype= FTYPE;
13405: modell[k].subtype= FQ;
13406: nsq++;
1.334 brouard 13407: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
13408: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 13409: ncovf++;
1.234 brouard 13410: TvarF[ncovf]=Tvar[k];
13411: TvarFind[ncovf]=k;
1.231 brouard 13412: TvarFQ[nqfveff]=Tvar[k]-ncovcol; /* TvarFQ[1]=V2-1=1st in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1.230 brouard 13413: TvarFQind[nqfveff]=k; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1.242 brouard 13414: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 13415: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13416: /* model V1+V3+age*V1+age*V3+V1*V3 */
13417: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13418: ncovvt++;
13419: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
13420: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
13421:
1.227 brouard 13422: Fixed[k]= 1;
13423: Dummy[k]= 0;
1.225 brouard 13424: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 13425: modell[k].maintype= VTYPE;
13426: modell[k].subtype= VD;
13427: nsd++;
13428: TvarsD[nsd]=Tvar[k];
13429: TvarsDind[nsd]=k;
1.330 brouard 13430: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 13431: ncovv++; /* Only simple time varying variables */
13432: TvarV[ncovv]=Tvar[k];
1.242 brouard 13433: TvarVind[ncovv]=k; /* TvarVind[2]=2 TvarVind[3]=3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */
1.231 brouard 13434: TvarVD[ntveff]=Tvar[k]; /* TvarVD[1]=V4 TvarVD[2]=V3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */
13435: TvarVDind[ntveff]=k; /* TvarVDind[1]=2 TvarVDind[2]=3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */
1.228 brouard 13436: printf("Quasi Tmodelind[%d]=%d,Tvar[Tmodelind[%d]]=V%d, ncovcol=%d, nqv=%d,Tvar[k]- ncovcol-nqv=%d\n",ntveff,k,ntveff,Tvar[k], ncovcol, nqv,Tvar[k]- ncovcol-nqv);
13437: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 13438: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 13439: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13440: /* model V1+V3+age*V1+age*V3+V1*V3 */
13441: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13442: ncovvt++;
13443: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
13444: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
13445:
1.234 brouard 13446: Fixed[k]= 1;
13447: Dummy[k]= 1;
13448: nqtveff++;
13449: modell[k].maintype= VTYPE;
13450: modell[k].subtype= VQ;
13451: ncovv++; /* Only simple time varying variables */
13452: nsq++;
1.334 brouard 13453: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */ /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary here) */
13454: TvarsQind[nsq]=k; /* For single quantitative covariate gives the model position of each single quantitative covariate *//* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.234 brouard 13455: TvarV[ncovv]=Tvar[k];
1.242 brouard 13456: TvarVind[ncovv]=k; /* TvarVind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */
1.231 brouard 13457: TvarVQ[nqtveff]=Tvar[k]; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
13458: TvarVQind[nqtveff]=k; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1.234 brouard 13459: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
13460: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 13461: /* printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%Ad,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv); */
1.342 brouard 13462: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 13463: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 13464: ncova++;
13465: TvarA[ncova]=Tvar[k];
13466: TvarAind[ncova]=k;
1.349 brouard 13467: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13468: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.231 brouard 13469: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 13470: Fixed[k]= 2;
13471: Dummy[k]= 2;
13472: modell[k].maintype= ATYPE;
13473: modell[k].subtype= APFD;
1.349 brouard 13474: ncovta++;
13475: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
13476: TvarAVVAind[ncovta]=k;
1.240 brouard 13477: /* ncoveff++; */
1.227 brouard 13478: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 13479: Fixed[k]= 2;
13480: Dummy[k]= 3;
13481: modell[k].maintype= ATYPE;
13482: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 13483: ncovta++;
13484: TvarAVVA[ncovta]=Tvar[k]; /* */
13485: TvarAVVAind[ncovta]=k;
1.240 brouard 13486: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 13487: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 13488: Fixed[k]= 3;
13489: Dummy[k]= 2;
13490: modell[k].maintype= ATYPE;
13491: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 13492: ncovva++;
13493: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
13494: TvarVVAind[ncovva]=k;
13495: ncovta++;
13496: TvarAVVA[ncovta]=Tvar[k]; /* */
13497: TvarAVVAind[ncovta]=k;
1.240 brouard 13498: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 13499: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 13500: Fixed[k]= 3;
13501: Dummy[k]= 3;
13502: modell[k].maintype= ATYPE;
13503: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 13504: ncovva++;
13505: TvarVVA[ncovva]=Tvar[k]; /* */
13506: TvarVVAind[ncovva]=k;
13507: ncovta++;
13508: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
13509: TvarAVVAind[ncovta]=k;
1.240 brouard 13510: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 13511: }
1.349 brouard 13512: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
13513: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
13514: if(FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol V3*V2 */
13515: printf("MEMORY ERRORR k=%d Tvardk[k][1]=%d, Tvardk[k][2]=%d, FixedV[Tvardk[k][1]]=%d,FixedV[Tvardk[k][2]]=%d\n ",k,Tvardk[k][1],Tvardk[k][2],FixedV[Tvardk[k][1]],FixedV[Tvardk[k][2]]);
13516: Fixed[k]= 0;
13517: Dummy[k]= 0;
13518: ncoveff++;
13519: ncovf++;
13520: /* ncovv++; */
13521: /* TvarVV[ncovv]=Tvardk[k][1]; */
13522: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13523: /* ncovv++; */
13524: /* TvarVV[ncovv]=Tvardk[k][2]; */
13525: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13526: modell[k].maintype= FTYPE;
13527: TvarF[ncovf]=Tvar[k];
13528: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
13529: TvarFind[ncovf]=k;
13530: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13531: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13532: }else{/* product varying Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
13533: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13534: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
13535: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13536: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
13537: ncovvt++;
13538: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
13539: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13540: ncovvt++;
13541: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
13542: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13543:
13544: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13545: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
13546:
13547: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
13548: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
13549: Fixed[k]= 1;
13550: Dummy[k]= 0;
13551: modell[k].maintype= FTYPE;
13552: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
13553: ncovf++; /* Fixed variables without age */
13554: TvarF[ncovf]=Tvar[k];
13555: TvarFind[ncovf]=k;
13556: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
13557: Fixed[k]= 0; /* Fixed product */
13558: Dummy[k]= 1;
13559: modell[k].maintype= FTYPE;
13560: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
13561: ncovf++; /* Varying variables without age */
13562: TvarF[ncovf]=Tvar[k];
13563: TvarFind[ncovf]=k;
13564: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
13565: Fixed[k]= 1;
13566: Dummy[k]= 0;
13567: modell[k].maintype= VTYPE;
13568: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
13569: ncovv++; /* Varying variables without age */
13570: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
13571: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
13572: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
13573: Fixed[k]= 1;
13574: Dummy[k]= 1;
13575: modell[k].maintype= VTYPE;
13576: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
13577: ncovv++; /* Varying variables without age */
13578: TvarV[ncovv]=Tvar[k];
13579: TvarVind[ncovv]=k;
13580: }
13581: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
13582: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
13583: Fixed[k]= 0; /* Fixed product */
13584: Dummy[k]= 1;
13585: modell[k].maintype= FTYPE;
13586: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
13587: ncovf++; /* Fixed variables without age */
13588: TvarF[ncovf]=Tvar[k];
13589: TvarFind[ncovf]=k;
13590: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
13591: Fixed[k]= 1;
13592: Dummy[k]= 1;
13593: modell[k].maintype= VTYPE;
13594: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
13595: ncovv++; /* Varying variables without age */
13596: TvarV[ncovv]=Tvar[k];
13597: TvarVind[ncovv]=k;
13598: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
13599: Fixed[k]= 1;
13600: Dummy[k]= 1;
13601: modell[k].maintype= VTYPE;
13602: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
13603: ncovv++; /* Varying variables without age */
13604: TvarV[ncovv]=Tvar[k];
13605: TvarVind[ncovv]=k;
13606: ncovv++; /* Varying variables without age */
13607: TvarV[ncovv]=Tvar[k];
13608: TvarVind[ncovv]=k;
13609: }
13610: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
13611: if(Tvard[k1][2] <=ncovcol){
13612: Fixed[k]= 1;
13613: Dummy[k]= 1;
13614: modell[k].maintype= VTYPE;
13615: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
13616: ncovv++; /* Varying variables without age */
13617: TvarV[ncovv]=Tvar[k];
13618: TvarVind[ncovv]=k;
13619: }else if(Tvard[k1][2] <=ncovcol+nqv){
13620: Fixed[k]= 1;
13621: Dummy[k]= 1;
13622: modell[k].maintype= VTYPE;
13623: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
13624: ncovv++; /* Varying variables without age */
13625: TvarV[ncovv]=Tvar[k];
13626: TvarVind[ncovv]=k;
13627: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
13628: Fixed[k]= 1;
13629: Dummy[k]= 0;
13630: modell[k].maintype= VTYPE;
13631: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
13632: ncovv++; /* Varying variables without age */
13633: TvarV[ncovv]=Tvar[k];
13634: TvarVind[ncovv]=k;
13635: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
13636: Fixed[k]= 1;
13637: Dummy[k]= 1;
13638: modell[k].maintype= VTYPE;
13639: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
13640: ncovv++; /* Varying variables without age */
13641: TvarV[ncovv]=Tvar[k];
13642: TvarVind[ncovv]=k;
13643: }
13644: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
13645: if(Tvard[k1][2] <=ncovcol){
13646: Fixed[k]= 1;
13647: Dummy[k]= 1;
13648: modell[k].maintype= VTYPE;
13649: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
13650: ncovv++; /* Varying variables without age */
13651: TvarV[ncovv]=Tvar[k];
13652: TvarVind[ncovv]=k;
13653: }else if(Tvard[k1][2] <=ncovcol+nqv){
13654: Fixed[k]= 1;
13655: Dummy[k]= 1;
13656: modell[k].maintype= VTYPE;
13657: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
13658: ncovv++; /* Varying variables without age */
13659: TvarV[ncovv]=Tvar[k];
13660: TvarVind[ncovv]=k;
13661: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
13662: Fixed[k]= 1;
13663: Dummy[k]= 1;
13664: modell[k].maintype= VTYPE;
13665: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
13666: ncovv++; /* Varying variables without age */
13667: TvarV[ncovv]=Tvar[k];
13668: TvarVind[ncovv]=k;
13669: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
13670: Fixed[k]= 1;
13671: Dummy[k]= 1;
13672: modell[k].maintype= VTYPE;
13673: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
13674: ncovv++; /* Varying variables without age */
13675: TvarV[ncovv]=Tvar[k];
13676: TvarVind[ncovv]=k;
13677: }
13678: }else{
13679: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13680: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13681: } /*end k1*/
13682: }
13683: }else if(Typevar[k] == 3){ /* product Vn * Vm with age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
1.339 brouard 13684: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 13685: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
13686: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13687: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
13688: ncova++;
13689: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
13690: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13691: ncova++;
13692: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
13693: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 13694:
1.349 brouard 13695: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13696: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
13697: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
13698: ncovta++;
13699: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13700: TvarAVVAind[ncovta]=k;
13701: ncovta++;
13702: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13703: TvarAVVAind[ncovta]=k;
13704: }else{
13705: ncovva++; /* HERY reached */
13706: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13707: TvarVVAind[ncovva]=k;
13708: ncovva++;
13709: TvarVVA[ncovva]=Tvard[k1][2]; /* */
13710: TvarVVAind[ncovva]=k;
13711: ncovta++;
13712: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13713: TvarAVVAind[ncovta]=k;
13714: ncovta++;
13715: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13716: TvarAVVAind[ncovta]=k;
13717: }
1.339 brouard 13718: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
13719: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 13720: Fixed[k]= 2;
13721: Dummy[k]= 2;
1.240 brouard 13722: modell[k].maintype= FTYPE;
13723: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 13724: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
13725: /* TvarFind[ncova]=k; */
1.339 brouard 13726: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 13727: Fixed[k]= 2; /* Fixed product */
13728: Dummy[k]= 3;
1.240 brouard 13729: modell[k].maintype= FTYPE;
13730: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 13731: /* TvarF[ncova]=Tvar[k]; */
13732: /* TvarFind[ncova]=k; */
1.339 brouard 13733: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 13734: Fixed[k]= 3;
13735: Dummy[k]= 2;
1.240 brouard 13736: modell[k].maintype= VTYPE;
13737: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 13738: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
13739: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 13740: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 13741: Fixed[k]= 3;
13742: Dummy[k]= 3;
1.240 brouard 13743: modell[k].maintype= VTYPE;
13744: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 13745: /* ncovv++; /\* Varying variables without age *\/ */
13746: /* TvarV[ncovv]=Tvar[k]; */
13747: /* TvarVind[ncovv]=k; */
1.240 brouard 13748: }
1.339 brouard 13749: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
13750: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 13751: Fixed[k]= 2; /* Fixed product */
13752: Dummy[k]= 2;
1.240 brouard 13753: modell[k].maintype= FTYPE;
13754: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 13755: /* ncova++; /\* Fixed variables with age *\/ */
13756: /* TvarF[ncovf]=Tvar[k]; */
13757: /* TvarFind[ncovf]=k; */
1.339 brouard 13758: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 13759: Fixed[k]= 2;
13760: Dummy[k]= 3;
1.240 brouard 13761: modell[k].maintype= VTYPE;
13762: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 13763: /* ncova++; /\* Varying variables with age *\/ */
13764: /* TvarV[ncova]=Tvar[k]; */
13765: /* TvarVind[ncova]=k; */
1.339 brouard 13766: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 13767: Fixed[k]= 3;
13768: Dummy[k]= 2;
1.240 brouard 13769: modell[k].maintype= VTYPE;
13770: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 13771: ncova++; /* Varying variables without age */
13772: TvarV[ncova]=Tvar[k];
13773: TvarVind[ncova]=k;
13774: /* ncova++; /\* Varying variables without age *\/ */
13775: /* TvarV[ncova]=Tvar[k]; */
13776: /* TvarVind[ncova]=k; */
1.240 brouard 13777: }
1.339 brouard 13778: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 13779: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 13780: Fixed[k]= 2;
13781: Dummy[k]= 2;
1.240 brouard 13782: modell[k].maintype= VTYPE;
13783: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 13784: /* ncova++; /\* Varying variables with age *\/ */
13785: /* TvarV[ncova]=Tvar[k]; */
13786: /* TvarVind[ncova]=k; */
1.240 brouard 13787: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 13788: Fixed[k]= 2;
13789: Dummy[k]= 3;
1.240 brouard 13790: modell[k].maintype= VTYPE;
13791: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 13792: /* ncova++; /\* Varying variables with age *\/ */
13793: /* TvarV[ncova]=Tvar[k]; */
13794: /* TvarVind[ncova]=k; */
1.240 brouard 13795: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 13796: Fixed[k]= 3;
13797: Dummy[k]= 2;
1.240 brouard 13798: modell[k].maintype= VTYPE;
13799: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 13800: /* ncova++; /\* Varying variables with age *\/ */
13801: /* TvarV[ncova]=Tvar[k]; */
13802: /* TvarVind[ncova]=k; */
1.240 brouard 13803: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 13804: Fixed[k]= 3;
13805: Dummy[k]= 3;
1.240 brouard 13806: modell[k].maintype= VTYPE;
13807: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 13808: /* ncova++; /\* Varying variables with age *\/ */
13809: /* TvarV[ncova]=Tvar[k]; */
13810: /* TvarVind[ncova]=k; */
1.240 brouard 13811: }
1.339 brouard 13812: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 13813: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 13814: Fixed[k]= 2;
13815: Dummy[k]= 2;
1.240 brouard 13816: modell[k].maintype= VTYPE;
13817: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 13818: /* ncova++; /\* Varying variables with age *\/ */
13819: /* TvarV[ncova]=Tvar[k]; */
13820: /* TvarVind[ncova]=k; */
1.240 brouard 13821: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 13822: Fixed[k]= 2;
13823: Dummy[k]= 3;
1.240 brouard 13824: modell[k].maintype= VTYPE;
13825: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 13826: /* ncova++; /\* Varying variables with age *\/ */
13827: /* TvarV[ncova]=Tvar[k]; */
13828: /* TvarVind[ncova]=k; */
1.240 brouard 13829: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 13830: Fixed[k]= 3;
13831: Dummy[k]= 2;
1.240 brouard 13832: modell[k].maintype= VTYPE;
13833: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 13834: /* ncova++; /\* Varying variables with age *\/ */
13835: /* TvarV[ncova]=Tvar[k]; */
13836: /* TvarVind[ncova]=k; */
1.240 brouard 13837: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 13838: Fixed[k]= 3;
13839: Dummy[k]= 3;
1.240 brouard 13840: modell[k].maintype= VTYPE;
13841: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 13842: /* ncova++; /\* Varying variables with age *\/ */
13843: /* TvarV[ncova]=Tvar[k]; */
13844: /* TvarVind[ncova]=k; */
1.240 brouard 13845: }
1.227 brouard 13846: }else{
1.240 brouard 13847: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13848: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13849: } /*end k1*/
1.349 brouard 13850: } else{
1.226 brouard 13851: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
13852: fprintf(ficlog,"Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
1.225 brouard 13853: }
1.342 brouard 13854: /* printf("Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[k],Dummy[k]); */
13855: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 13856: fprintf(ficlog,"Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[k],Dummy[k]);
13857: }
1.349 brouard 13858: ncovvta=ncovva;
1.227 brouard 13859: /* Searching for doublons in the model */
13860: for(k1=1; k1<= cptcovt;k1++){
13861: for(k2=1; k2 <k1;k2++){
1.285 brouard 13862: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
13863: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 13864: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
13865: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 13866: printf("Error duplication in the model=1+age+%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]);
13867: fprintf(ficlog,"Error duplication in the model=1+age+%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]); fflush(ficlog);
1.234 brouard 13868: return(1);
13869: }
13870: }else if (Typevar[k1] ==2){
13871: k3=Tposprod[k1];
13872: k4=Tposprod[k2];
13873: if( ((Tvard[k3][1]== Tvard[k4][1])&&(Tvard[k3][2]== Tvard[k4][2])) || ((Tvard[k3][1]== Tvard[k4][2])&&(Tvard[k3][2]== Tvard[k4][1])) ){
1.338 brouard 13874: printf("Error duplication in the model=1+age+%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]);
13875: fprintf(ficlog,"Error duplication in the model=1+age+%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog);
1.234 brouard 13876: return(1);
13877: }
13878: }
1.227 brouard 13879: }
13880: }
1.225 brouard 13881: }
13882: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
13883: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 13884: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
13885: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 13886:
13887: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 13888: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 13889: /*endread:*/
1.225 brouard 13890: printf("Exiting decodemodel: ");
13891: return (1);
1.136 brouard 13892: }
13893:
1.169 brouard 13894: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 13895: {/* Check ages at death */
1.136 brouard 13896: int i, m;
1.218 brouard 13897: int firstone=0;
13898:
1.136 brouard 13899: for (i=1; i<=imx; i++) {
13900: for(m=2; (m<= maxwav); m++) {
13901: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
13902: anint[m][i]=9999;
1.216 brouard 13903: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
13904: s[m][i]=-1;
1.136 brouard 13905: }
13906: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 13907: *nberr = *nberr + 1;
1.218 brouard 13908: if(firstone == 0){
13909: firstone=1;
1.260 brouard 13910: printf("Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\nOther similar cases in log file\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
1.218 brouard 13911: }
1.262 brouard 13912: fprintf(ficlog,"Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
1.260 brouard 13913: s[m][i]=-1; /* Droping the death status */
1.136 brouard 13914: }
13915: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 13916: (*nberr)++;
1.259 brouard 13917: printf("Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\nOther similar cases in log file\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
1.262 brouard 13918: fprintf(ficlog,"Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
1.259 brouard 13919: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 13920: }
13921: }
13922: }
13923:
13924: for (i=1; i<=imx; i++) {
13925: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
13926: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 13927: if(s[m][i] >0 || s[m][i]==-1 || s[m][i]==-2 || s[m][i]==-4 || s[m][i]==-5){ /* What if s[m][i]=-1 */
1.136 brouard 13928: if (s[m][i] >= nlstate+1) {
1.169 brouard 13929: if(agedc[i]>0){
13930: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 13931: agev[m][i]=agedc[i];
1.214 brouard 13932: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 13933: }else {
1.136 brouard 13934: if ((int)andc[i]!=9999){
13935: nbwarn++;
13936: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
13937: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
13938: agev[m][i]=-1;
13939: }
13940: }
1.169 brouard 13941: } /* agedc > 0 */
1.214 brouard 13942: } /* end if */
1.136 brouard 13943: else if(s[m][i] !=9){ /* Standard case, age in fractional
13944: years but with the precision of a month */
13945: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
13946: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
13947: agev[m][i]=1;
13948: else if(agev[m][i] < *agemin){
13949: *agemin=agev[m][i];
13950: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
13951: }
13952: else if(agev[m][i] >*agemax){
13953: *agemax=agev[m][i];
1.156 brouard 13954: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 13955: }
13956: /*agev[m][i]=anint[m][i]-annais[i];*/
13957: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 13958: } /* en if 9*/
1.136 brouard 13959: else { /* =9 */
1.214 brouard 13960: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 13961: agev[m][i]=1;
13962: s[m][i]=-1;
13963: }
13964: }
1.214 brouard 13965: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 13966: agev[m][i]=1;
1.214 brouard 13967: else{
13968: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
13969: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
13970: agev[m][i]=0;
13971: }
13972: } /* End for lastpass */
13973: }
1.136 brouard 13974:
13975: for (i=1; i<=imx; i++) {
13976: for(m=firstpass; (m<=lastpass); m++){
13977: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 13978: (*nberr)++;
1.136 brouard 13979: printf("Error: on wave %d of individual %d status %d > (nlstate+ndeath)=(%d+%d)=%d\n",m,i,s[m][i],nlstate, ndeath, nlstate+ndeath);
13980: fprintf(ficlog,"Error: on wave %d of individual %d status %d > (nlstate+ndeath)=(%d+%d)=%d\n",m,i,s[m][i],nlstate, ndeath, nlstate+ndeath);
13981: return 1;
13982: }
13983: }
13984: }
13985:
13986: /*for (i=1; i<=imx; i++){
13987: for (m=firstpass; (m<lastpass); m++){
13988: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
13989: }
13990:
13991: }*/
13992:
13993:
1.139 brouard 13994: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
13995: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 13996:
13997: return (0);
1.164 brouard 13998: /* endread:*/
1.136 brouard 13999: printf("Exiting calandcheckages: ");
14000: return (1);
14001: }
14002:
1.172 brouard 14003: #if defined(_MSC_VER)
14004: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
14005: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
14006: //#include "stdafx.h"
14007: //#include <stdio.h>
14008: //#include <tchar.h>
14009: //#include <windows.h>
14010: //#include <iostream>
14011: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
14012:
14013: LPFN_ISWOW64PROCESS fnIsWow64Process;
14014:
14015: BOOL IsWow64()
14016: {
14017: BOOL bIsWow64 = FALSE;
14018:
14019: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
14020: // (HANDLE, PBOOL);
14021:
14022: //LPFN_ISWOW64PROCESS fnIsWow64Process;
14023:
14024: HMODULE module = GetModuleHandle(_T("kernel32"));
14025: const char funcName[] = "IsWow64Process";
14026: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
14027: GetProcAddress(module, funcName);
14028:
14029: if (NULL != fnIsWow64Process)
14030: {
14031: if (!fnIsWow64Process(GetCurrentProcess(),
14032: &bIsWow64))
14033: //throw std::exception("Unknown error");
14034: printf("Unknown error\n");
14035: }
14036: return bIsWow64 != FALSE;
14037: }
14038: #endif
1.177 brouard 14039:
1.191 brouard 14040: void syscompilerinfo(int logged)
1.292 brouard 14041: {
14042: #include <stdint.h>
14043:
14044: /* #include "syscompilerinfo.h"*/
1.185 brouard 14045: /* command line Intel compiler 32bit windows, XP compatible:*/
14046: /* /GS /W3 /Gy
14047: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
14048: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
14049: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 14050: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
14051: */
14052: /* 64 bits */
1.185 brouard 14053: /*
14054: /GS /W3 /Gy
14055: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
14056: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
14057: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
14058: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
14059: /* Optimization are useless and O3 is slower than O2 */
14060: /*
14061: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
14062: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
14063: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
14064: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
14065: */
1.186 brouard 14066: /* Link is */ /* /OUT:"visual studio
1.185 brouard 14067: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
14068: /PDB:"visual studio
14069: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
14070: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
14071: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
14072: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
14073: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
14074: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
14075: uiAccess='false'"
14076: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
14077: /NOLOGO /TLBID:1
14078: */
1.292 brouard 14079:
14080:
1.177 brouard 14081: #if defined __INTEL_COMPILER
1.178 brouard 14082: #if defined(__GNUC__)
14083: struct utsname sysInfo; /* For Intel on Linux and OS/X */
14084: #endif
1.177 brouard 14085: #elif defined(__GNUC__)
1.179 brouard 14086: #ifndef __APPLE__
1.174 brouard 14087: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 14088: #endif
1.177 brouard 14089: struct utsname sysInfo;
1.178 brouard 14090: int cross = CROSS;
14091: if (cross){
14092: printf("Cross-");
1.191 brouard 14093: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 14094: }
1.174 brouard 14095: #endif
14096:
1.191 brouard 14097: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 14098: #if defined(__clang__)
1.191 brouard 14099: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 14100: #endif
14101: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 14102: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 14103: #endif
14104: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 14105: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 14106: #endif
14107: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 14108: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 14109: #endif
14110: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 14111: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 14112: #endif
14113: #if defined(_MSC_VER)
1.191 brouard 14114: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 14115: #endif
14116: #if defined(__PGI)
1.191 brouard 14117: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 14118: #endif
14119: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 14120: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 14121: #endif
1.191 brouard 14122: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 14123:
1.167 brouard 14124: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
14125: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
14126: // Windows (x64 and x86)
1.191 brouard 14127: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 14128: #elif __unix__ // all unices, not all compilers
14129: // Unix
1.191 brouard 14130: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 14131: #elif __linux__
14132: // linux
1.191 brouard 14133: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 14134: #elif __APPLE__
1.174 brouard 14135: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 14136: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 14137: #endif
14138:
14139: /* __MINGW32__ */
14140: /* __CYGWIN__ */
14141: /* __MINGW64__ */
14142: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
14143: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
14144: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
14145: /* _WIN64 // Defined for applications for Win64. */
14146: /* _M_X64 // Defined for compilations that target x64 processors. */
14147: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 14148:
1.167 brouard 14149: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 14150: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 14151: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 14152: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 14153: #else
1.191 brouard 14154: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 14155: #endif
14156:
1.169 brouard 14157: #if defined(__GNUC__)
14158: # if defined(__GNUC_PATCHLEVEL__)
14159: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
14160: + __GNUC_MINOR__ * 100 \
14161: + __GNUC_PATCHLEVEL__)
14162: # else
14163: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
14164: + __GNUC_MINOR__ * 100)
14165: # endif
1.174 brouard 14166: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 14167: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 14168:
14169: if (uname(&sysInfo) != -1) {
14170: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 14171: if(logged) fprintf(ficlog,"Running on: %s %s %s %s %s\n ",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.176 brouard 14172: }
14173: else
14174: perror("uname() error");
1.179 brouard 14175: //#ifndef __INTEL_COMPILER
14176: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 14177: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 14178: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 14179: #endif
1.169 brouard 14180: #endif
1.172 brouard 14181:
1.286 brouard 14182: // void main ()
1.172 brouard 14183: // {
1.169 brouard 14184: #if defined(_MSC_VER)
1.174 brouard 14185: if (IsWow64()){
1.191 brouard 14186: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
14187: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 14188: }
14189: else{
1.191 brouard 14190: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
14191: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 14192: }
1.172 brouard 14193: // printf("\nPress Enter to continue...");
14194: // getchar();
14195: // }
14196:
1.169 brouard 14197: #endif
14198:
1.167 brouard 14199:
1.219 brouard 14200: }
1.136 brouard 14201:
1.219 brouard 14202: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 14203: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 14204: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 14205: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 14206: /* double ftolpl = 1.e-10; */
1.180 brouard 14207: double age, agebase, agelim;
1.203 brouard 14208: double tot;
1.180 brouard 14209:
1.202 brouard 14210: strcpy(filerespl,"PL_");
14211: strcat(filerespl,fileresu);
14212: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 14213: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
14214: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 14215: }
1.288 brouard 14216: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
14217: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 14218: pstamp(ficrespl);
1.288 brouard 14219: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 14220: fprintf(ficrespl,"#Age ");
14221: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
14222: fprintf(ficrespl,"\n");
1.180 brouard 14223:
1.219 brouard 14224: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 14225:
1.219 brouard 14226: agebase=ageminpar;
14227: agelim=agemaxpar;
1.180 brouard 14228:
1.227 brouard 14229: /* i1=pow(2,ncoveff); */
1.234 brouard 14230: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 14231: if (cptcovn < 1){i1=1;}
1.180 brouard 14232:
1.337 brouard 14233: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 14234: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 14235: k=TKresult[nres];
1.338 brouard 14236: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14237: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
14238: /* continue; */
1.235 brouard 14239:
1.238 brouard 14240: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14241: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
14242: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
14243: /* k=k+1; */
14244: /* to clean */
1.332 brouard 14245: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 14246: fprintf(ficrespl,"#******");
14247: printf("#******");
14248: fprintf(ficlog,"#******");
1.337 brouard 14249: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
1.332 brouard 14250: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 14251: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14252: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14253: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14254: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14255: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14256: }
14257: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
14258: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14259: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14260: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14261: /* } */
1.238 brouard 14262: fprintf(ficrespl,"******\n");
14263: printf("******\n");
14264: fprintf(ficlog,"******\n");
14265: if(invalidvarcomb[k]){
14266: printf("\nCombination (%d) ignored because no case \n",k);
14267: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
14268: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
14269: continue;
14270: }
1.219 brouard 14271:
1.238 brouard 14272: fprintf(ficrespl,"#Age ");
1.337 brouard 14273: /* for(j=1;j<=cptcoveff;j++) { */
14274: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14275: /* } */
14276: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
14277: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14278: }
14279: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
14280: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 14281:
1.238 brouard 14282: for (age=agebase; age<=agelim; age++){
14283: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 14284: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
14285: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 14286: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 14287: /* for(j=1;j<=cptcoveff;j++) */
14288: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14289: for(j=1;j<=cptcovs;j++)
14290: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14291: tot=0.;
14292: for(i=1; i<=nlstate;i++){
14293: tot += prlim[i][i];
14294: fprintf(ficrespl," %.5f", prlim[i][i]);
14295: }
14296: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
14297: } /* Age */
14298: /* was end of cptcod */
1.337 brouard 14299: } /* nres */
14300: /* } /\* for each combination *\/ */
1.219 brouard 14301: return 0;
1.180 brouard 14302: }
14303:
1.218 brouard 14304: int back_prevalence_limit(double *p, double **bprlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp, double dateprev1,double dateprev2, int firstpass, int lastpass, int mobilavproj){
1.288 brouard 14305: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 14306:
14307: /* Computes the back prevalence limit for any combination of covariate values
14308: * at any age between ageminpar and agemaxpar
14309: */
1.235 brouard 14310: int i, j, k, i1, nres=0 ;
1.217 brouard 14311: /* double ftolpl = 1.e-10; */
14312: double age, agebase, agelim;
14313: double tot;
1.218 brouard 14314: /* double ***mobaverage; */
14315: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 14316:
14317: strcpy(fileresplb,"PLB_");
14318: strcat(fileresplb,fileresu);
14319: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 14320: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
14321: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 14322: }
1.288 brouard 14323: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
14324: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 14325: pstamp(ficresplb);
1.288 brouard 14326: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 14327: fprintf(ficresplb,"#Age ");
14328: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
14329: fprintf(ficresplb,"\n");
14330:
1.218 brouard 14331:
14332: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
14333:
14334: agebase=ageminpar;
14335: agelim=agemaxpar;
14336:
14337:
1.227 brouard 14338: i1=pow(2,cptcoveff);
1.218 brouard 14339: if (cptcovn < 1){i1=1;}
1.227 brouard 14340:
1.238 brouard 14341: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 14342: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14343: k=TKresult[nres];
14344: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
14345: /* if(i1 != 1 && TKresult[nres]!= k) */
14346: /* continue; */
14347: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 14348: fprintf(ficresplb,"#******");
14349: printf("#******");
14350: fprintf(ficlog,"#******");
1.338 brouard 14351: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
14352: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14353: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14354: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14355: }
1.338 brouard 14356: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
14357: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14358: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14359: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14360: /* } */
14361: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14362: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14363: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14364: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14365: /* } */
1.238 brouard 14366: fprintf(ficresplb,"******\n");
14367: printf("******\n");
14368: fprintf(ficlog,"******\n");
14369: if(invalidvarcomb[k]){
14370: printf("\nCombination (%d) ignored because no cases \n",k);
14371: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
14372: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
14373: continue;
14374: }
1.218 brouard 14375:
1.238 brouard 14376: fprintf(ficresplb,"#Age ");
1.338 brouard 14377: for(j=1;j<=cptcovs;j++) {
14378: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14379: }
14380: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
14381: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 14382:
14383:
1.238 brouard 14384: for (age=agebase; age<=agelim; age++){
14385: /* for (age=agebase; age<=agebase; age++){ */
14386: if(mobilavproj > 0){
14387: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
14388: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 14389: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 14390: }else if (mobilavproj == 0){
14391: printf("There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj);
14392: fprintf(ficlog,"There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj);
14393: exit(1);
14394: }else{
14395: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 14396: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 14397: /* printf("TOTOT\n"); */
14398: /* exit(1); */
1.238 brouard 14399: }
14400: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 14401: for(j=1;j<=cptcovs;j++)
14402: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14403: tot=0.;
14404: for(i=1; i<=nlstate;i++){
14405: tot += bprlim[i][i];
14406: fprintf(ficresplb," %.5f", bprlim[i][i]);
14407: }
14408: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
14409: } /* Age */
14410: /* was end of cptcod */
1.255 brouard 14411: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 14412: /* } /\* end of any combination *\/ */
1.238 brouard 14413: } /* end of nres */
1.218 brouard 14414: /* hBijx(p, bage, fage); */
14415: /* fclose(ficrespijb); */
14416:
14417: return 0;
1.217 brouard 14418: }
1.218 brouard 14419:
1.180 brouard 14420: int hPijx(double *p, int bage, int fage){
14421: /*------------- h Pij x at various ages ------------*/
1.336 brouard 14422: /* to be optimized with precov */
1.180 brouard 14423: int stepsize;
14424: int agelim;
14425: int hstepm;
14426: int nhstepm;
1.359 brouard 14427: int h, i, i1, j, k, nres=0;
1.180 brouard 14428:
14429: double agedeb;
14430: double ***p3mat;
14431:
1.337 brouard 14432: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
14433: if((ficrespij=fopen(filerespij,"w"))==NULL) {
14434: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
14435: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
14436: }
14437: printf("Computing pij: result on file '%s' \n", filerespij);
14438: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
14439:
14440: stepsize=(int) (stepm+YEARM-1)/YEARM;
14441: /*if (stepm<=24) stepsize=2;*/
14442:
14443: agelim=AGESUP;
14444: hstepm=stepsize*YEARM; /* Every year of age */
14445: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
14446:
14447: /* hstepm=1; aff par mois*/
14448: pstamp(ficrespij);
14449: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
14450: i1= pow(2,cptcoveff);
14451: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14452: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
14453: /* k=k+1; */
14454: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
14455: k=TKresult[nres];
1.338 brouard 14456: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14457: /* for(k=1; k<=i1;k++){ */
14458: /* if(i1 != 1 && TKresult[nres]!= k) */
14459: /* continue; */
14460: fprintf(ficrespij,"\n#****** ");
14461: for(j=1;j<=cptcovs;j++){
14462: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14463: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14464: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
14465: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14466: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14467: }
14468: fprintf(ficrespij,"******\n");
14469:
14470: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
14471: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
14472: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
14473:
14474: /* nhstepm=nhstepm*YEARM; aff par mois*/
14475:
14476: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14477: oldm=oldms;savm=savms;
14478: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
14479: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
14480: for(i=1; i<=nlstate;i++)
14481: for(j=1; j<=nlstate+ndeath;j++)
14482: fprintf(ficrespij," %1d-%1d",i,j);
14483: fprintf(ficrespij,"\n");
14484: for (h=0; h<=nhstepm; h++){
14485: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
14486: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 14487: for(i=1; i<=nlstate;i++)
14488: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 14489: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 14490: fprintf(ficrespij,"\n");
14491: }
1.337 brouard 14492: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14493: fprintf(ficrespij,"\n");
1.180 brouard 14494: }
1.337 brouard 14495: }
14496: /*}*/
14497: return 0;
1.180 brouard 14498: }
1.218 brouard 14499:
14500: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 14501: /*------------- h Bij x at various ages ------------*/
1.336 brouard 14502: /* To be optimized with precov */
1.217 brouard 14503: int stepsize;
1.218 brouard 14504: /* int agelim; */
14505: int ageminl;
1.217 brouard 14506: int hstepm;
14507: int nhstepm;
1.238 brouard 14508: int h, i, i1, j, k, nres;
1.218 brouard 14509:
1.217 brouard 14510: double agedeb;
14511: double ***p3mat;
1.218 brouard 14512:
14513: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
14514: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
14515: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
14516: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
14517: }
14518: printf("Computing pij back: result on file '%s' \n", filerespijb);
14519: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
14520:
14521: stepsize=(int) (stepm+YEARM-1)/YEARM;
14522: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 14523:
1.218 brouard 14524: /* agelim=AGESUP; */
1.289 brouard 14525: ageminl=AGEINF; /* was 30 */
1.218 brouard 14526: hstepm=stepsize*YEARM; /* Every year of age */
14527: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
14528:
14529: /* hstepm=1; aff par mois*/
14530: pstamp(ficrespijb);
1.255 brouard 14531: fprintf(ficrespijb,"#****** h Bij x Back probability to be in state i at age x-h being in j at x: B1j+B2j+...=1 ");
1.227 brouard 14532: i1= pow(2,cptcoveff);
1.218 brouard 14533: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14534: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
14535: /* k=k+1; */
1.238 brouard 14536: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 14537: k=TKresult[nres];
1.338 brouard 14538: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14539: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14540: /* if(i1 != 1 && TKresult[nres]!= k) */
14541: /* continue; */
14542: fprintf(ficrespijb,"\n#****** ");
14543: for(j=1;j<=cptcovs;j++){
1.338 brouard 14544: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 14545: /* for(j=1;j<=cptcoveff;j++) */
14546: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14547: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14548: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14549: }
14550: fprintf(ficrespijb,"******\n");
14551: if(invalidvarcomb[k]){ /* Is it necessary here? */
14552: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
14553: continue;
14554: }
14555:
14556: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
14557: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
14558: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
14559: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm+0.1)-1; /* Typically 20 years = 20*12/6=40 or 55*12/24=27.5-1.1=>27 */
14560: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
14561:
14562: /* nhstepm=nhstepm*YEARM; aff par mois*/
14563:
14564: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
14565: /* and memory limitations if stepm is small */
14566:
14567: /* oldm=oldms;savm=savms; */
14568: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
14569: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
14570: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
14571: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
14572: for(i=1; i<=nlstate;i++)
14573: for(j=1; j<=nlstate+ndeath;j++)
14574: fprintf(ficrespijb," %1d-%1d",i,j);
14575: fprintf(ficrespijb,"\n");
14576: for (h=0; h<=nhstepm; h++){
14577: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
14578: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
14579: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 14580: for(i=1; i<=nlstate;i++)
14581: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 14582: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 14583: fprintf(ficrespijb,"\n");
1.337 brouard 14584: }
14585: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14586: fprintf(ficrespijb,"\n");
14587: } /* end age deb */
14588: /* } /\* end combination *\/ */
1.238 brouard 14589: } /* end nres */
1.218 brouard 14590: return 0;
14591: } /* hBijx */
1.217 brouard 14592:
1.180 brouard 14593:
1.136 brouard 14594: /***********************************************/
14595: /**************** Main Program *****************/
14596: /***********************************************/
14597:
14598: int main(int argc, char *argv[])
14599: {
14600: #ifdef GSL
14601: const gsl_multimin_fminimizer_type *T;
14602: size_t iteri = 0, it;
14603: int rval = GSL_CONTINUE;
14604: int status = GSL_SUCCESS;
14605: double ssval;
14606: #endif
14607: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 14608: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
14609: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 14610: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 14611: int jj, ll, li, lj, lk;
1.136 brouard 14612: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 14613: int num_filled;
1.136 brouard 14614: int itimes;
14615: int NDIM=2;
14616: int vpopbased=0;
1.235 brouard 14617: int nres=0;
1.258 brouard 14618: int endishere=0;
1.277 brouard 14619: int noffset=0;
1.274 brouard 14620: int ncurrv=0; /* Temporary variable */
14621:
1.164 brouard 14622: char ca[32], cb[32];
1.136 brouard 14623: /* FILE *fichtm; *//* Html File */
14624: /* FILE *ficgp;*/ /*Gnuplot File */
14625: struct stat info;
1.191 brouard 14626: double agedeb=0.;
1.194 brouard 14627:
14628: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 14629: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 14630:
1.361 ! brouard 14631: double stdpercent; /* for computing the std error of percent e.i: e.i/e.. */
1.165 brouard 14632: double fret;
1.191 brouard 14633: double dum=0.; /* Dummy variable */
1.359 brouard 14634: /* double*** p3mat;*/
1.218 brouard 14635: /* double ***mobaverage; */
1.319 brouard 14636: double wald;
1.164 brouard 14637:
1.351 brouard 14638: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 14639: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
14640:
1.234 brouard 14641: char modeltemp[MAXLINE];
1.332 brouard 14642: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 14643:
1.136 brouard 14644: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 14645: char *tok, *val; /* pathtot */
1.334 brouard 14646: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.359 brouard 14647: int c, h; /* c2; */
1.191 brouard 14648: int jl=0;
14649: int i1, j1, jk, stepsize=0;
1.194 brouard 14650: int count=0;
14651:
1.164 brouard 14652: int *tab;
1.136 brouard 14653: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 14654: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
14655: /* double anprojf, mprojf, jprojf; */
14656: /* double jintmean,mintmean,aintmean; */
14657: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
14658: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
14659: double yrfproj= 10.0; /* Number of years of forward projections */
14660: double yrbproj= 10.0; /* Number of years of backward projections */
14661: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 14662: int mobilav=0,popforecast=0;
1.191 brouard 14663: int hstepm=0, nhstepm=0;
1.136 brouard 14664: int agemortsup;
14665: float sumlpop=0.;
14666: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
14667: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
14668:
1.191 brouard 14669: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 14670: double ftolpl=FTOL;
14671: double **prlim;
1.217 brouard 14672: double **bprlim;
1.317 brouard 14673: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
14674: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 14675: double ***paramstart; /* Matrix of starting parameter values */
14676: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 14677: double **matcov; /* Matrix of covariance */
1.203 brouard 14678: double **hess; /* Hessian matrix */
1.136 brouard 14679: double ***delti3; /* Scale */
14680: double *delti; /* Scale */
14681: double ***eij, ***vareij;
1.359 brouard 14682: //double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 14683:
1.136 brouard 14684: double *epj, vepp;
1.164 brouard 14685:
1.273 brouard 14686: double dateprev1, dateprev2;
1.296 brouard 14687: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
14688: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
14689:
1.217 brouard 14690:
1.136 brouard 14691: double **ximort;
1.145 brouard 14692: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 14693: int *dcwave;
14694:
1.164 brouard 14695: char z[1]="c";
1.136 brouard 14696:
14697: /*char *strt;*/
14698: char strtend[80];
1.126 brouard 14699:
1.164 brouard 14700:
1.126 brouard 14701: /* setlocale (LC_ALL, ""); */
14702: /* bindtextdomain (PACKAGE, LOCALEDIR); */
14703: /* textdomain (PACKAGE); */
14704: /* setlocale (LC_CTYPE, ""); */
14705: /* setlocale (LC_MESSAGES, ""); */
14706:
14707: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 14708: rstart_time = time(NULL);
14709: /* (void) gettimeofday(&start_time,&tzp);*/
14710: start_time = *localtime(&rstart_time);
1.126 brouard 14711: curr_time=start_time;
1.157 brouard 14712: /*tml = *localtime(&start_time.tm_sec);*/
14713: /* strcpy(strstart,asctime(&tml)); */
14714: strcpy(strstart,asctime(&start_time));
1.126 brouard 14715:
14716: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 14717: /* tp.tm_sec = tp.tm_sec +86400; */
14718: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 14719: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
14720: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
14721: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 14722: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 14723: /* strt=asctime(&tmg); */
14724: /* printf("Time(after) =%s",strstart); */
14725: /* (void) time (&time_value);
14726: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
14727: * tm = *localtime(&time_value);
14728: * strstart=asctime(&tm);
14729: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
14730: */
14731:
14732: nberr=0; /* Number of errors and warnings */
14733: nbwarn=0;
1.184 brouard 14734: #ifdef WIN32
14735: _getcwd(pathcd, size);
14736: #else
1.126 brouard 14737: getcwd(pathcd, size);
1.184 brouard 14738: #endif
1.191 brouard 14739: syscompilerinfo(0);
1.359 brouard 14740: printf("\nIMaCh prax version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 14741: if(argc <=1){
14742: printf("\nEnter the parameter file name: ");
1.205 brouard 14743: if(!fgets(pathr,FILENAMELENGTH,stdin)){
14744: printf("ERROR Empty parameter file name\n");
14745: goto end;
14746: }
1.126 brouard 14747: i=strlen(pathr);
14748: if(pathr[i-1]=='\n')
14749: pathr[i-1]='\0';
1.156 brouard 14750: i=strlen(pathr);
1.205 brouard 14751: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 14752: pathr[i-1]='\0';
1.205 brouard 14753: }
14754: i=strlen(pathr);
14755: if( i==0 ){
14756: printf("ERROR Empty parameter file name\n");
14757: goto end;
14758: }
14759: for (tok = pathr; tok != NULL; ){
1.126 brouard 14760: printf("Pathr |%s|\n",pathr);
14761: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
14762: printf("val= |%s| pathr=%s\n",val,pathr);
14763: strcpy (pathtot, val);
14764: if(pathr[0] == '\0') break; /* Dirty */
14765: }
14766: }
1.281 brouard 14767: else if (argc<=2){
14768: strcpy(pathtot,argv[1]);
14769: }
1.126 brouard 14770: else{
14771: strcpy(pathtot,argv[1]);
1.281 brouard 14772: strcpy(z,argv[2]);
14773: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 14774: }
14775: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
14776: /*cygwin_split_path(pathtot,path,optionfile);
14777: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
14778: /* cutv(path,optionfile,pathtot,'\\');*/
14779:
14780: /* Split argv[0], imach program to get pathimach */
14781: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
14782: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
14783: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
14784: /* strcpy(pathimach,argv[0]); */
14785: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
14786: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
14787: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 14788: #ifdef WIN32
14789: _chdir(path); /* Can be a relative path */
14790: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
14791: #else
1.126 brouard 14792: chdir(path); /* Can be a relative path */
1.184 brouard 14793: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
14794: #endif
14795: printf("Current directory %s!\n",pathcd);
1.126 brouard 14796: strcpy(command,"mkdir ");
14797: strcat(command,optionfilefiname);
14798: if((outcmd=system(command)) != 0){
1.169 brouard 14799: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 14800: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
14801: /* fclose(ficlog); */
14802: /* exit(1); */
14803: }
14804: /* if((imk=mkdir(optionfilefiname))<0){ */
14805: /* perror("mkdir"); */
14806: /* } */
14807:
14808: /*-------- arguments in the command line --------*/
14809:
1.186 brouard 14810: /* Main Log file */
1.126 brouard 14811: strcat(filelog, optionfilefiname);
14812: strcat(filelog,".log"); /* */
14813: if((ficlog=fopen(filelog,"w"))==NULL) {
14814: printf("Problem with logfile %s\n",filelog);
14815: goto end;
14816: }
14817: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 14818: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 14819: fprintf(ficlog,"\nEnter the parameter file name: \n");
14820: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
14821: path=%s \n\
14822: optionfile=%s\n\
14823: optionfilext=%s\n\
1.156 brouard 14824: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 14825:
1.197 brouard 14826: syscompilerinfo(1);
1.167 brouard 14827:
1.126 brouard 14828: printf("Local time (at start):%s",strstart);
14829: fprintf(ficlog,"Local time (at start): %s",strstart);
14830: fflush(ficlog);
14831: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 14832: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 14833:
14834: /* */
14835: strcpy(fileres,"r");
14836: strcat(fileres, optionfilefiname);
1.201 brouard 14837: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 14838: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 14839: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 14840:
1.186 brouard 14841: /* Main ---------arguments file --------*/
1.126 brouard 14842:
14843: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 14844: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
14845: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 14846: fflush(ficlog);
1.149 brouard 14847: /* goto end; */
14848: exit(70);
1.126 brouard 14849: }
14850:
14851: strcpy(filereso,"o");
1.201 brouard 14852: strcat(filereso,fileresu);
1.126 brouard 14853: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
14854: printf("Problem with Output resultfile: %s\n", filereso);
14855: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
14856: fflush(ficlog);
14857: goto end;
14858: }
1.278 brouard 14859: /*-------- Rewriting parameter file ----------*/
14860: strcpy(rfileres,"r"); /* "Rparameterfile */
14861: strcat(rfileres,optionfilefiname); /* Parameter file first name */
14862: strcat(rfileres,"."); /* */
14863: strcat(rfileres,optionfilext); /* Other files have txt extension */
14864: if((ficres =fopen(rfileres,"w"))==NULL) {
14865: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
14866: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
14867: fflush(ficlog);
14868: goto end;
14869: }
14870: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 14871:
1.278 brouard 14872:
1.126 brouard 14873: /* Reads comments: lines beginning with '#' */
14874: numlinepar=0;
1.277 brouard 14875: /* Is it a BOM UTF-8 Windows file? */
14876: /* First parameter line */
1.197 brouard 14877: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 14878: noffset=0;
14879: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
14880: {
14881: noffset=noffset+3;
14882: printf("# File is an UTF8 Bom.\n"); // 0xBF
14883: }
1.302 brouard 14884: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
14885: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 14886: {
14887: noffset=noffset+2;
14888: printf("# File is an UTF16BE BOM file\n");
14889: }
14890: else if( line[0] == 0 && line[1] == 0)
14891: {
14892: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
14893: noffset=noffset+4;
14894: printf("# File is an UTF16BE BOM file\n");
14895: }
14896: } else{
14897: ;/*printf(" Not a BOM file\n");*/
14898: }
14899:
1.197 brouard 14900: /* If line starts with a # it is a comment */
1.277 brouard 14901: if (line[noffset] == '#') {
1.197 brouard 14902: numlinepar++;
14903: fputs(line,stdout);
14904: fputs(line,ficparo);
1.278 brouard 14905: fputs(line,ficres);
1.197 brouard 14906: fputs(line,ficlog);
14907: continue;
14908: }else
14909: break;
14910: }
14911: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
14912: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
14913: if (num_filled != 5) {
14914: printf("Should be 5 parameters\n");
1.283 brouard 14915: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 14916: }
1.126 brouard 14917: numlinepar++;
1.197 brouard 14918: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 14919: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
14920: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
14921: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 14922: }
14923: /* Second parameter line */
14924: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 14925: /* while(fscanf(ficpar,"%[^\n]", line)) { */
14926: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 14927: if (line[0] == '#') {
14928: numlinepar++;
1.283 brouard 14929: printf("%s",line);
14930: fprintf(ficres,"%s",line);
14931: fprintf(ficparo,"%s",line);
14932: fprintf(ficlog,"%s",line);
1.197 brouard 14933: continue;
14934: }else
14935: break;
14936: }
1.223 brouard 14937: if((num_filled=sscanf(line,"ftol=%lf stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n", \
14938: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
14939: if (num_filled != 11) {
14940: printf("Not 11 parameters, for example:ftol=1.e-8 stepm=12 ncovcol=2 nqv=1 ntv=2 nqtv=1 nlstate=2 ndeath=1 maxwav=3 mle=1 weight=1\n");
1.209 brouard 14941: printf("but line=%s\n",line);
1.283 brouard 14942: fprintf(ficlog,"Not 11 parameters, for example:ftol=1.e-8 stepm=12 ncovcol=2 nqv=1 ntv=2 nqtv=1 nlstate=2 ndeath=1 maxwav=3 mle=1 weight=1\n");
14943: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 14944: }
1.286 brouard 14945: if( lastpass > maxwav){
14946: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
14947: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
14948: fflush(ficlog);
14949: goto end;
14950: }
14951: printf("ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.283 brouard 14952: fprintf(ficparo,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.286 brouard 14953: fprintf(ficres,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, 0, weightopt);
1.283 brouard 14954: fprintf(ficlog,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.126 brouard 14955: }
1.203 brouard 14956: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 14957: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 14958: /* Third parameter line */
14959: while(fgets(line, MAXLINE, ficpar)) {
14960: /* If line starts with a # it is a comment */
14961: if (line[0] == '#') {
14962: numlinepar++;
1.283 brouard 14963: printf("%s",line);
14964: fprintf(ficres,"%s",line);
14965: fprintf(ficparo,"%s",line);
14966: fprintf(ficlog,"%s",line);
1.197 brouard 14967: continue;
14968: }else
14969: break;
14970: }
1.351 brouard 14971: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
14972: if (num_filled != 1){
14973: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
14974: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
14975: model[0]='\0';
14976: goto end;
14977: }else{
14978: trimbtab(linetmp,line); /* Trims multiple blanks in line */
14979: strcpy(line, linetmp);
14980: }
14981: }
14982: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 14983: if (num_filled != 1){
1.302 brouard 14984: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
14985: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 14986: model[0]='\0';
14987: goto end;
14988: }
14989: else{
14990: if (model[0]=='+'){
14991: for(i=1; i<=strlen(model);i++)
14992: modeltemp[i-1]=model[i];
1.201 brouard 14993: strcpy(model,modeltemp);
1.197 brouard 14994: }
14995: }
1.338 brouard 14996: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 14997: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 14998: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
14999: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
15000: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 15001: }
15002: /* fscanf(ficpar,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%lf stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d model=1+age+%s\n",title, datafile, &lastobs, &firstpass,&lastpass,&ftol, &stepm, &ncovcol, &nlstate,&ndeath, &maxwav, &mle, &weightopt,model); */
15003: /* numlinepar=numlinepar+3; /\* In general *\/ */
15004: /* printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nlstate,ndeath, maxwav, mle, weightopt,model); */
1.283 brouard 15005: /* fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol,stepm,ncovcol, nqv, ntv, nqtv, nlstate,ndeath,maxwav, mle, weightopt,model); */
15006: /* fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol,stepm,ncovcol, nqv, ntv, nqtv, nlstate,ndeath,maxwav, mle, weightopt,model); */
1.126 brouard 15007: fflush(ficlog);
1.190 brouard 15008: /* if(model[0]=='#'|| model[0]== '\0'){ */
15009: if(model[0]=='#'){
1.279 brouard 15010: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
15011: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
15012: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 15013: if(mle != -1){
1.279 brouard 15014: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter vectors and subdiagonal covariance matrix.\n");
1.187 brouard 15015: exit(1);
15016: }
15017: }
1.126 brouard 15018: while((c=getc(ficpar))=='#' && c!= EOF){
15019: ungetc(c,ficpar);
15020: fgets(line, MAXLINE, ficpar);
15021: numlinepar++;
1.195 brouard 15022: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
15023: z[0]=line[1];
1.342 brouard 15024: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 15025: debugILK=1;printf("DebugILK\n");
1.195 brouard 15026: }
15027: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 15028: fputs(line, stdout);
15029: //puts(line);
1.126 brouard 15030: fputs(line,ficparo);
15031: fputs(line,ficlog);
15032: }
15033: ungetc(c,ficpar);
15034:
15035:
1.290 brouard 15036: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
15037: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
15038: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 15039: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
15040: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 15041: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
15042: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
15043: v1+v2*age+v2*v3 makes cptcovn = 3
15044: */
15045: if (strlen(model)>1)
1.187 brouard 15046: ncovmodel=2+nbocc(model,'+')+1; /*Number of variables including intercept and age = cptcovn + intercept + age : v1+v2+v3+v2*v4+v5*age makes 5+2=7,age*age makes 3*/
1.145 brouard 15047: else
1.187 brouard 15048: ncovmodel=2; /* Constant and age */
1.133 brouard 15049: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
15050: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 15051: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
15052: printf("Too complex model for current IMaCh: npar=(nlstate+ndeath-1)*nlstate*ncovmodel=%d >= %d(MAXPARM) or nlstate=%d >= %d(NLSTATEMAX) or ndeath=%d >= %d(NDEATHMAX) or ncovmodel=(k+age+#of+signs)=%d(NCOVMAX) >= %d\n",npar, MAXPARM, nlstate, NLSTATEMAX, ndeath, NDEATHMAX, ncovmodel, NCOVMAX);
15053: fprintf(ficlog,"Too complex model for current IMaCh: %d >=%d(MAXPARM) or %d >=%d(NLSTATEMAX) or %d >=%d(NDEATHMAX) or %d(NCOVMAX) >=%d\n",npar, MAXPARM, nlstate, NLSTATEMAX, ndeath, NDEATHMAX, ncovmodel, NCOVMAX);
15054: fflush(stdout);
15055: fclose (ficlog);
15056: goto end;
15057: }
1.126 brouard 15058: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
15059: delti=delti3[1][1];
15060: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
15061: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 15062: /* We could also provide initial parameters values giving by simple logistic regression
15063: * only one way, that is without matrix product. We will have nlstate maximizations */
15064: /* for(i=1;i<nlstate;i++){ */
15065: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
15066: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
15067: /* } */
1.126 brouard 15068: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 15069: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
15070: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 15071: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15072: fclose (ficparo);
15073: fclose (ficlog);
15074: goto end;
15075: exit(0);
1.220 brouard 15076: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 15077: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 15078: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
15079: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 15080: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
15081: matcov=matrix(1,npar,1,npar);
1.203 brouard 15082: hess=matrix(1,npar,1,npar);
1.220 brouard 15083: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 15084: /* Read guessed parameters */
1.126 brouard 15085: /* Reads comments: lines beginning with '#' */
15086: while((c=getc(ficpar))=='#' && c!= EOF){
15087: ungetc(c,ficpar);
15088: fgets(line, MAXLINE, ficpar);
15089: numlinepar++;
1.141 brouard 15090: fputs(line,stdout);
1.126 brouard 15091: fputs(line,ficparo);
15092: fputs(line,ficlog);
15093: }
15094: ungetc(c,ficpar);
15095:
15096: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 15097: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 15098: for(i=1; i <=nlstate; i++){
1.234 brouard 15099: j=0;
1.126 brouard 15100: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 15101: if(jj==i) continue;
15102: j++;
1.292 brouard 15103: while((c=getc(ficpar))=='#' && c!= EOF){
15104: ungetc(c,ficpar);
15105: fgets(line, MAXLINE, ficpar);
15106: numlinepar++;
15107: fputs(line,stdout);
15108: fputs(line,ficparo);
15109: fputs(line,ficlog);
15110: }
15111: ungetc(c,ficpar);
1.234 brouard 15112: fscanf(ficpar,"%1d%1d",&i1,&j1);
15113: if ((i1 != i) || (j1 != jj)){
15114: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 15115: It might be a problem of design; if ncovcol and the model are correct\n \
15116: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 15117: exit(1);
15118: }
15119: fprintf(ficparo,"%1d%1d",i1,j1);
15120: if(mle==1)
15121: printf("%1d%1d",i,jj);
15122: fprintf(ficlog,"%1d%1d",i,jj);
15123: for(k=1; k<=ncovmodel;k++){
15124: fscanf(ficpar," %lf",¶m[i][j][k]);
15125: if(mle==1){
15126: printf(" %lf",param[i][j][k]);
15127: fprintf(ficlog," %lf",param[i][j][k]);
15128: }
15129: else
15130: fprintf(ficlog," %lf",param[i][j][k]);
15131: fprintf(ficparo," %lf",param[i][j][k]);
15132: }
15133: fscanf(ficpar,"\n");
15134: numlinepar++;
15135: if(mle==1)
15136: printf("\n");
15137: fprintf(ficlog,"\n");
15138: fprintf(ficparo,"\n");
1.126 brouard 15139: }
15140: }
15141: fflush(ficlog);
1.234 brouard 15142:
1.251 brouard 15143: /* Reads parameters values */
1.126 brouard 15144: p=param[1][1];
1.251 brouard 15145: pstart=paramstart[1][1];
1.126 brouard 15146:
15147: /* Reads comments: lines beginning with '#' */
15148: while((c=getc(ficpar))=='#' && c!= EOF){
15149: ungetc(c,ficpar);
15150: fgets(line, MAXLINE, ficpar);
15151: numlinepar++;
1.141 brouard 15152: fputs(line,stdout);
1.126 brouard 15153: fputs(line,ficparo);
15154: fputs(line,ficlog);
15155: }
15156: ungetc(c,ficpar);
15157:
15158: for(i=1; i <=nlstate; i++){
15159: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 15160: fscanf(ficpar,"%1d%1d",&i1,&j1);
15161: if ( (i1-i) * (j1-j) != 0){
15162: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
15163: exit(1);
15164: }
15165: printf("%1d%1d",i,j);
15166: fprintf(ficparo,"%1d%1d",i1,j1);
15167: fprintf(ficlog,"%1d%1d",i1,j1);
15168: for(k=1; k<=ncovmodel;k++){
15169: fscanf(ficpar,"%le",&delti3[i][j][k]);
15170: printf(" %le",delti3[i][j][k]);
15171: fprintf(ficparo," %le",delti3[i][j][k]);
15172: fprintf(ficlog," %le",delti3[i][j][k]);
15173: }
15174: fscanf(ficpar,"\n");
15175: numlinepar++;
15176: printf("\n");
15177: fprintf(ficparo,"\n");
15178: fprintf(ficlog,"\n");
1.126 brouard 15179: }
15180: }
15181: fflush(ficlog);
1.234 brouard 15182:
1.145 brouard 15183: /* Reads covariance matrix */
1.126 brouard 15184: delti=delti3[1][1];
1.220 brouard 15185:
15186:
1.126 brouard 15187: /* free_ma3x(delti3,1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */ /* Hasn't to to freed here otherwise delti is no more allocated */
1.220 brouard 15188:
1.126 brouard 15189: /* Reads comments: lines beginning with '#' */
15190: while((c=getc(ficpar))=='#' && c!= EOF){
15191: ungetc(c,ficpar);
15192: fgets(line, MAXLINE, ficpar);
15193: numlinepar++;
1.141 brouard 15194: fputs(line,stdout);
1.126 brouard 15195: fputs(line,ficparo);
15196: fputs(line,ficlog);
15197: }
15198: ungetc(c,ficpar);
1.220 brouard 15199:
1.126 brouard 15200: matcov=matrix(1,npar,1,npar);
1.203 brouard 15201: hess=matrix(1,npar,1,npar);
1.131 brouard 15202: for(i=1; i <=npar; i++)
15203: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 15204:
1.194 brouard 15205: /* Scans npar lines */
1.126 brouard 15206: for(i=1; i <=npar; i++){
1.226 brouard 15207: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 15208: if(count != 3){
1.226 brouard 15209: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 15210: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
15211: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 15212: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 15213: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
15214: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 15215: exit(1);
1.220 brouard 15216: }else{
1.226 brouard 15217: if(mle==1)
15218: printf("%1d%1d%d",i1,j1,jk);
15219: }
15220: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
15221: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 15222: for(j=1; j <=i; j++){
1.226 brouard 15223: fscanf(ficpar," %le",&matcov[i][j]);
15224: if(mle==1){
15225: printf(" %.5le",matcov[i][j]);
15226: }
15227: fprintf(ficlog," %.5le",matcov[i][j]);
15228: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 15229: }
15230: fscanf(ficpar,"\n");
15231: numlinepar++;
15232: if(mle==1)
1.220 brouard 15233: printf("\n");
1.126 brouard 15234: fprintf(ficlog,"\n");
15235: fprintf(ficparo,"\n");
15236: }
1.194 brouard 15237: /* End of read covariance matrix npar lines */
1.126 brouard 15238: for(i=1; i <=npar; i++)
15239: for(j=i+1;j<=npar;j++)
1.226 brouard 15240: matcov[i][j]=matcov[j][i];
1.126 brouard 15241:
15242: if(mle==1)
15243: printf("\n");
15244: fprintf(ficlog,"\n");
15245:
15246: fflush(ficlog);
15247:
15248: } /* End of mle != -3 */
1.218 brouard 15249:
1.186 brouard 15250: /* Main data
15251: */
1.290 brouard 15252: nobs=lastobs-firstobs+1; /* was = lastobs;*/
15253: /* num=lvector(1,n); */
15254: /* moisnais=vector(1,n); */
15255: /* annais=vector(1,n); */
15256: /* moisdc=vector(1,n); */
15257: /* andc=vector(1,n); */
15258: /* weight=vector(1,n); */
15259: /* agedc=vector(1,n); */
15260: /* cod=ivector(1,n); */
15261: /* for(i=1;i<=n;i++){ */
15262: num=lvector(firstobs,lastobs);
15263: moisnais=vector(firstobs,lastobs);
15264: annais=vector(firstobs,lastobs);
15265: moisdc=vector(firstobs,lastobs);
15266: andc=vector(firstobs,lastobs);
15267: weight=vector(firstobs,lastobs);
15268: agedc=vector(firstobs,lastobs);
15269: cod=ivector(firstobs,lastobs);
15270: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 15271: num[i]=0;
15272: moisnais[i]=0;
15273: annais[i]=0;
15274: moisdc[i]=0;
15275: andc[i]=0;
15276: agedc[i]=0;
15277: cod[i]=0;
15278: weight[i]=1.0; /* Equal weights, 1 by default */
15279: }
1.290 brouard 15280: mint=matrix(1,maxwav,firstobs,lastobs);
15281: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 15282: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 15283: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 15284: tab=ivector(1,NCOVMAX);
1.144 brouard 15285: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 15286: ncodemaxwundef=ivector(1,NCOVMAX); /* Number of code per covariate; if - 1 O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.126 brouard 15287:
1.136 brouard 15288: /* Reads data from file datafile */
15289: if (readdata(datafile, firstobs, lastobs, &imx)==1)
15290: goto end;
15291:
15292: /* Calculation of the number of parameters from char model */
1.234 brouard 15293: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 15294: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
15295: k=3 V4 Tvar[k=3]= 4 (from V4)
15296: k=2 V1 Tvar[k=2]= 1 (from V1)
15297: k=1 Tvar[1]=2 (from V2)
1.234 brouard 15298: */
15299:
15300: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
15301: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 15302: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 15303: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 15304: TvarsD=ivector(1,NCOVMAX); /* */
15305: TvarsQind=ivector(1,NCOVMAX); /* */
15306: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 15307: TvarF=ivector(1,NCOVMAX); /* */
15308: TvarFind=ivector(1,NCOVMAX); /* */
15309: TvarV=ivector(1,NCOVMAX); /* */
15310: TvarVind=ivector(1,NCOVMAX); /* */
15311: TvarA=ivector(1,NCOVMAX); /* */
15312: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 15313: TvarFD=ivector(1,NCOVMAX); /* */
15314: TvarFDind=ivector(1,NCOVMAX); /* */
15315: TvarFQ=ivector(1,NCOVMAX); /* */
15316: TvarFQind=ivector(1,NCOVMAX); /* */
15317: TvarVD=ivector(1,NCOVMAX); /* */
15318: TvarVDind=ivector(1,NCOVMAX); /* */
15319: TvarVQ=ivector(1,NCOVMAX); /* */
15320: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 15321: TvarVV=ivector(1,NCOVMAX); /* */
15322: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 15323: TvarVVA=ivector(1,NCOVMAX); /* */
15324: TvarVVAind=ivector(1,NCOVMAX); /* */
15325: TvarAVVA=ivector(1,NCOVMAX); /* */
15326: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 15327:
1.230 brouard 15328: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 15329: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 15330: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
15331: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
15332: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 15333: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
15334: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
15335:
1.137 brouard 15336: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
15337: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
15338: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
15339: */
15340: /* For model-covariate k tells which data-covariate to use but
15341: because this model-covariate is a construction we invent a new column
15342: ncovcol + k1
15343: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
15344: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 15345: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
15346: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 15347: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
15348: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 15349: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 15350: */
1.145 brouard 15351: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
15352: Tvard=imatrix(1,NCOVMAX,1,2); /* n=Tvard[k1][1] and m=Tvard[k1][2] gives the couple n,m of the k1 th product Vn*Vm
1.141 brouard 15353: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
15354: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 15355: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 15356: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 15357: 4 covariates (3 plus signs)
15358: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 15359: */
15360: for(i=1;i<NCOVMAX;i++)
15361: Tage[i]=0;
1.230 brouard 15362: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 15363: * individual dummy, fixed or varying:
15364: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
15365: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 15366: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
15367: * V1 df, V2 qf, V3 & V4 dv, V5 qv
15368: * Tmodelind[1]@9={9,0,3,2,}*/
15369: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
15370: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 15371: * individual quantitative, fixed or varying:
15372: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
15373: * 3, 1, 0, 0, 0, 0, 0, 0},
15374: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 15375:
15376: /* Probably useless zeroes */
15377: for(i=1;i<NCOVMAX;i++){
15378: DummyV[i]=0;
15379: FixedV[i]=0;
15380: }
15381:
15382: for(i=1; i <=ncovcol;i++){
15383: DummyV[i]=0;
15384: FixedV[i]=0;
15385: }
15386: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
15387: DummyV[i]=1;
15388: FixedV[i]=0;
15389: }
15390: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
15391: DummyV[i]=0;
15392: FixedV[i]=1;
15393: }
15394: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
15395: DummyV[i]=1;
15396: FixedV[i]=1;
15397: }
15398: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
15399: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
15400: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
15401: }
15402:
15403:
15404:
1.186 brouard 15405: /* Main decodemodel */
15406:
1.187 brouard 15407:
1.223 brouard 15408: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 15409: goto end;
15410:
1.137 brouard 15411: if((double)(lastobs-imx)/(double)imx > 1.10){
15412: nbwarn++;
15413: printf("Warning: The value of parameter lastobs=%d is big compared to the \n effective number of cases imx=%d, please adjust, \n otherwise you are allocating more memory than necessary.\n",lastobs, imx);
15414: fprintf(ficlog,"Warning: The value of parameter lastobs=%d is big compared to the \n effective number of cases imx=%d, please adjust, \n otherwise you are allocating more memory than necessary.\n",lastobs, imx);
15415: }
1.136 brouard 15416: /* if(mle==1){*/
1.137 brouard 15417: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
15418: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 15419: }
15420:
15421: /*-calculation of age at interview from date of interview and age at death -*/
15422: agev=matrix(1,maxwav,1,imx);
15423:
15424: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
15425: goto end;
15426:
1.126 brouard 15427:
1.136 brouard 15428: agegomp=(int)agemin;
1.290 brouard 15429: free_vector(moisnais,firstobs,lastobs);
15430: free_vector(annais,firstobs,lastobs);
1.126 brouard 15431: /* free_matrix(mint,1,maxwav,1,n);
15432: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 15433: /* free_vector(moisdc,1,n); */
15434: /* free_vector(andc,1,n); */
1.145 brouard 15435: /* */
15436:
1.126 brouard 15437: wav=ivector(1,imx);
1.214 brouard 15438: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
15439: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
15440: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
15441: dh=imatrix(1,lastpass-firstpass+2,1,imx); /* We are adding a wave if status is unknown at last wave but death occurs after last wave.*/
15442: bh=imatrix(1,lastpass-firstpass+2,1,imx);
15443: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 15444:
15445: /* Concatenates waves */
1.214 brouard 15446: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
15447: Death is a valid wave (if date is known).
15448: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
15449: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
15450: and mw[mi+1][i]. dh depends on stepm.
15451: */
15452:
1.126 brouard 15453: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 15454: /* Concatenates waves */
1.145 brouard 15455:
1.290 brouard 15456: free_vector(moisdc,firstobs,lastobs);
15457: free_vector(andc,firstobs,lastobs);
1.215 brouard 15458:
1.126 brouard 15459: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
15460: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
15461: ncodemax[1]=1;
1.145 brouard 15462: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 15463: cptcoveff=0;
1.220 brouard 15464: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 15465: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; as well as calculate cptcoveff or number of total effective dummy covariates*/
1.227 brouard 15466: }
15467:
15468: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 15469: invalidvarcomb=ivector(0, ncovcombmax);
15470: for(i=0;i<ncovcombmax;i++)
1.227 brouard 15471: invalidvarcomb[i]=0;
15472:
1.211 brouard 15473: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 15474: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 15475: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 15476:
1.200 brouard 15477: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 15478: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 15479: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 15480: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
15481: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
15482: * (currently 0 or 1) in the data.
15483: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
15484: * corresponding modality (h,j).
15485: */
15486:
1.145 brouard 15487: h=0;
15488: /*if (cptcovn > 0) */
1.126 brouard 15489: m=pow(2,cptcoveff);
15490:
1.144 brouard 15491: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 15492: * For k=4 covariates, h goes from 1 to m=2**k
15493: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
15494: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 15495: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
15496: *______________________________ *______________________
15497: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
15498: * 2 2 1 1 1 * 1 0 0 0 1
15499: * 3 i=2 1 2 1 1 * 2 0 0 1 0
15500: * 4 2 2 1 1 * 3 0 0 1 1
15501: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
15502: * 6 2 1 2 1 * 5 0 1 0 1
15503: * 7 i=4 1 2 2 1 * 6 0 1 1 0
15504: * 8 2 2 2 1 * 7 0 1 1 1
15505: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
15506: * 10 2 1 1 2 * 9 1 0 0 1
15507: * 11 i=6 1 2 1 2 * 10 1 0 1 0
15508: * 12 2 2 1 2 * 11 1 0 1 1
15509: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
15510: * 14 2 1 2 2 * 13 1 1 0 1
15511: * 15 i=8 1 2 2 2 * 14 1 1 1 0
15512: * 16 2 2 2 2 * 15 1 1 1 1
15513: */
1.212 brouard 15514: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 15515: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
15516: * and the value of each covariate?
15517: * V1=1, V2=1, V3=2, V4=1 ?
15518: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
15519: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
15520: * In order to get the real value in the data, we use nbcode
15521: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
15522: * We are keeping this crazy system in order to be able (in the future?)
15523: * to have more than 2 values (0 or 1) for a covariate.
15524: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
15525: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
15526: * bbbbbbbb
15527: * 76543210
15528: * h-1 00000101 (6-1=5)
1.219 brouard 15529: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 15530: * &
15531: * 1 00000001 (1)
1.219 brouard 15532: * 00000000 = 1 & ((h-1) >> (k-1))
15533: * +1= 00000001 =1
1.211 brouard 15534: *
15535: * h=14, k=3 => h'=h-1=13, k'=k-1=2
15536: * h' 1101 =2^3+2^2+0x2^1+2^0
15537: * >>k' 11
15538: * & 00000001
15539: * = 00000001
15540: * +1 = 00000010=2 = codtabm(14,3)
15541: * Reverse h=6 and m=16?
15542: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
15543: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
15544: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
15545: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
15546: * V3=decodtabm(14,3,2**4)=2
15547: * h'=13 1101 =2^3+2^2+0x2^1+2^0
15548: *(h-1) >> (j-1) 0011 =13 >> 2
15549: * &1 000000001
15550: * = 000000001
15551: * +1= 000000010 =2
15552: * 2211
15553: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
15554: * V3=2
1.220 brouard 15555: * codtabm and decodtabm are identical
1.211 brouard 15556: */
15557:
1.145 brouard 15558:
15559: free_ivector(Ndum,-1,NCOVMAX);
15560:
15561:
1.126 brouard 15562:
1.186 brouard 15563: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 15564: strcpy(optionfilegnuplot,optionfilefiname);
15565: if(mle==-3)
1.201 brouard 15566: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 15567: strcat(optionfilegnuplot,".gp");
15568:
15569: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
15570: printf("Problem with file %s",optionfilegnuplot);
15571: }
15572: else{
1.204 brouard 15573: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 15574: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 15575: //fprintf(ficgp,"set missing 'NaNq'\n");
15576: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 15577: }
15578: /* fclose(ficgp);*/
1.186 brouard 15579:
15580:
15581: /* Initialisation of --------- index.htm --------*/
1.126 brouard 15582:
15583: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
15584: if(mle==-3)
1.201 brouard 15585: strcat(optionfilehtm,"-MORT_");
1.126 brouard 15586: strcat(optionfilehtm,".htm");
15587: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 15588: printf("Problem with %s \n",optionfilehtm);
15589: exit(0);
1.126 brouard 15590: }
15591:
15592: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
15593: strcat(optionfilehtmcov,"-cov.htm");
15594: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
15595: printf("Problem with %s \n",optionfilehtmcov), exit(0);
15596: }
15597: else{
15598: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
15599: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 15600: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 15601: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
15602: }
15603:
1.335 brouard 15604: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
15605: <title>IMaCh %s</title></head>\n\
15606: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
15607: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
15608: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
15609: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
15610: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
15611:
15612: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 15613: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 15614: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 15615: This file: <a href=\"%s\">%s</a></br>Title=%s <br>Datafile=<a href=\"%s\">%s</a> Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 15616: \n\
15617: <hr size=\"2\" color=\"#EC5E5E\">\
15618: <ul><li><h4>Parameter files</h4>\n\
15619: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
15620: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
15621: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
15622: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
15623: - Date and time at start: %s</ul>\n",\
1.335 brouard 15624: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 15625: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
15626: fileres,fileres,\
15627: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
15628: fflush(fichtm);
15629:
15630: strcpy(pathr,path);
15631: strcat(pathr,optionfilefiname);
1.184 brouard 15632: #ifdef WIN32
15633: _chdir(optionfilefiname); /* Move to directory named optionfile */
15634: #else
1.126 brouard 15635: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 15636: #endif
15637:
1.126 brouard 15638:
1.220 brouard 15639: /* Calculates basic frequencies. Computes observed prevalence at single age
15640: and for any valid combination of covariates
1.126 brouard 15641: and prints on file fileres'p'. */
1.359 brouard 15642: freqsummary(fileres, p, pstart, (double)agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 15643: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 15644:
15645: fprintf(fichtm,"\n");
1.286 brouard 15646: fprintf(fichtm,"<h4>Parameter line 2</h4><ul><li>Tolerance for the convergence of the likelihood: ftol=%g \n<li>Interval for the elementary matrix (in month): stepm=%d",\
1.274 brouard 15647: ftol, stepm);
15648: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
15649: ncurrv=1;
15650: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
15651: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
15652: ncurrv=i;
15653: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 15654: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 15655: ncurrv=i;
15656: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 15657: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 15658: ncurrv=i;
15659: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
15660: fprintf(fichtm,"\n<li>Weights column \n<br>Number of alive states: nlstate=%d <br>Number of death states (not really implemented): ndeath=%d \n<li>Number of waves: maxwav=%d \n<li>Parameter for maximization (1), using parameter values (0), for design of parameters and variance-covariance matrix: mle=%d \n<li>Does the weight column be taken into account (1), or not (0): weight=%d</ul>\n", \
15661: nlstate, ndeath, maxwav, mle, weightopt);
15662:
15663: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
15664: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
15665:
15666:
1.317 brouard 15667: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 15668: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
15669: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 15670: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 15671: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 15672: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15673: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15674: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15675: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 15676:
1.126 brouard 15677: /* For Powell, parameters are in a vector p[] starting at p[1]
15678: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
15679: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
15680:
15681: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 15682: /* For mortality only */
1.126 brouard 15683: if (mle==-3){
1.136 brouard 15684: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 15685: for(i=1;i<=NDIM;i++)
15686: for(j=1;j<=NDIM;j++)
15687: ximort[i][j]=0.;
1.186 brouard 15688: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 15689: cens=ivector(firstobs,lastobs);
15690: ageexmed=vector(firstobs,lastobs);
15691: agecens=vector(firstobs,lastobs);
15692: dcwave=ivector(firstobs,lastobs);
1.223 brouard 15693:
1.126 brouard 15694: for (i=1; i<=imx; i++){
15695: dcwave[i]=-1;
15696: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 15697: if (s[m][i]>nlstate) {
15698: dcwave[i]=m;
15699: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
15700: break;
15701: }
1.126 brouard 15702: }
1.226 brouard 15703:
1.126 brouard 15704: for (i=1; i<=imx; i++) {
15705: if (wav[i]>0){
1.226 brouard 15706: ageexmed[i]=agev[mw[1][i]][i];
15707: j=wav[i];
15708: agecens[i]=1.;
15709:
15710: if (ageexmed[i]> 1 && wav[i] > 0){
15711: agecens[i]=agev[mw[j][i]][i];
15712: cens[i]= 1;
15713: }else if (ageexmed[i]< 1)
15714: cens[i]= -1;
15715: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
15716: cens[i]=0 ;
1.126 brouard 15717: }
15718: else cens[i]=-1;
15719: }
15720:
15721: for (i=1;i<=NDIM;i++) {
15722: for (j=1;j<=NDIM;j++)
1.226 brouard 15723: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 15724: }
15725:
1.302 brouard 15726: p[1]=0.0268; p[NDIM]=0.083;
15727: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 15728:
15729:
1.136 brouard 15730: #ifdef GSL
15731: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 15732: #else
1.359 brouard 15733: printf("Powell-mort\n"); fprintf(ficlog,"Powell-mort\n");
1.136 brouard 15734: #endif
1.201 brouard 15735: strcpy(filerespow,"POW-MORT_");
15736: strcat(filerespow,fileresu);
1.126 brouard 15737: if((ficrespow=fopen(filerespow,"w"))==NULL) {
15738: printf("Problem with resultfile: %s\n", filerespow);
15739: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
15740: }
1.136 brouard 15741: #ifdef GSL
15742: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 15743: #else
1.126 brouard 15744: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 15745: #endif
1.126 brouard 15746: /* for (i=1;i<=nlstate;i++)
15747: for(j=1;j<=nlstate+ndeath;j++)
15748: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
15749: */
15750: fprintf(ficrespow,"\n");
1.136 brouard 15751: #ifdef GSL
15752: /* gsl starts here */
15753: T = gsl_multimin_fminimizer_nmsimplex;
15754: gsl_multimin_fminimizer *sfm = NULL;
15755: gsl_vector *ss, *x;
15756: gsl_multimin_function minex_func;
15757:
15758: /* Initial vertex size vector */
15759: ss = gsl_vector_alloc (NDIM);
15760:
15761: if (ss == NULL){
15762: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
15763: }
15764: /* Set all step sizes to 1 */
15765: gsl_vector_set_all (ss, 0.001);
15766:
15767: /* Starting point */
1.126 brouard 15768:
1.136 brouard 15769: x = gsl_vector_alloc (NDIM);
15770:
15771: if (x == NULL){
15772: gsl_vector_free(ss);
15773: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
15774: }
15775:
15776: /* Initialize method and iterate */
15777: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 15778: /* gsl_vector_set(x, 0, 0.0268); */
15779: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 15780: gsl_vector_set(x, 0, p[1]);
15781: gsl_vector_set(x, 1, p[2]);
15782:
15783: minex_func.f = &gompertz_f;
15784: minex_func.n = NDIM;
15785: minex_func.params = (void *)&p; /* ??? */
15786:
15787: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
15788: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
15789:
15790: printf("Iterations beginning .....\n\n");
15791: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
15792:
15793: iteri=0;
15794: while (rval == GSL_CONTINUE){
15795: iteri++;
15796: status = gsl_multimin_fminimizer_iterate(sfm);
15797:
15798: if (status) printf("error: %s\n", gsl_strerror (status));
15799: fflush(0);
15800:
15801: if (status)
15802: break;
15803:
15804: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
15805: ssval = gsl_multimin_fminimizer_size (sfm);
15806:
15807: if (rval == GSL_SUCCESS)
15808: printf ("converged to a local maximum at\n");
15809:
15810: printf("%5d ", iteri);
15811: for (it = 0; it < NDIM; it++){
15812: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
15813: }
15814: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
15815: }
15816:
15817: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
15818:
15819: gsl_vector_free(x); /* initial values */
15820: gsl_vector_free(ss); /* inital step size */
15821: for (it=0; it<NDIM; it++){
15822: p[it+1]=gsl_vector_get(sfm->x,it);
15823: fprintf(ficrespow," %.12lf", p[it]);
15824: }
15825: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
15826: #endif
15827: #ifdef POWELL
1.361 ! brouard 15828: #ifdef LINMINORIGINAL
! 15829: #else /* LINMINORIGINAL */
! 15830:
! 15831: flatdir=ivector(1,npar);
! 15832: for (j=1;j<=npar;j++) flatdir[j]=0;
! 15833: #endif /*LINMINORIGINAL */
1.136 brouard 15834: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
15835: #endif
1.126 brouard 15836: fclose(ficrespow);
1.361 ! brouard 15837: #ifdef LINMINORIGINAL
! 15838: #else
! 15839: free_ivector(flatdir,1,npar);
! 15840: #endif /* LINMINORIGINAL*/
1.126 brouard 15841:
1.203 brouard 15842: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 15843:
15844: for(i=1; i <=NDIM; i++)
15845: for(j=i+1;j<=NDIM;j++)
1.359 brouard 15846: matcov[i][j]=matcov[j][i];
1.126 brouard 15847:
15848: printf("\nCovariance matrix\n ");
1.203 brouard 15849: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 15850: for(i=1; i <=NDIM; i++) {
15851: for(j=1;j<=NDIM;j++){
1.220 brouard 15852: printf("%f ",matcov[i][j]);
15853: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 15854: }
1.203 brouard 15855: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 15856: }
15857:
15858: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 15859: for (i=1;i<=NDIM;i++) {
1.126 brouard 15860: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 15861: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
15862: }
1.302 brouard 15863: lsurv=vector(agegomp,AGESUP);
15864: lpop=vector(agegomp,AGESUP);
15865: tpop=vector(agegomp,AGESUP);
1.126 brouard 15866: lsurv[agegomp]=100000;
15867:
15868: for (k=agegomp;k<=AGESUP;k++) {
15869: agemortsup=k;
15870: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
15871: }
15872:
15873: for (k=agegomp;k<agemortsup;k++)
15874: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
15875:
15876: for (k=agegomp;k<agemortsup;k++){
15877: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
15878: sumlpop=sumlpop+lpop[k];
15879: }
15880:
15881: tpop[agegomp]=sumlpop;
15882: for (k=agegomp;k<(agemortsup-3);k++){
15883: /* tpop[k+1]=2;*/
15884: tpop[k+1]=tpop[k]-lpop[k];
15885: }
15886:
15887:
15888: printf("\nAge lx qx dx Lx Tx e(x)\n");
15889: for (k=agegomp;k<(agemortsup-2);k++)
15890: printf("%d %.0lf %lf %.0lf %.0lf %.0lf %lf\n",k,lsurv[k],p[1]*exp(p[2]*(k-agegomp)),(p[1]*exp(p[2]*(k-agegomp)))*lsurv[k],lpop[k],tpop[k],tpop[k]/lsurv[k]);
15891:
15892:
15893: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 15894: ageminpar=50;
15895: agemaxpar=100;
1.194 brouard 15896: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
15897: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
15898: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
15899: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
15900: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
15901: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
15902: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 15903: }else{
15904: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
15905: fprintf(ficlog,"Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
1.201 brouard 15906: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 15907: }
1.201 brouard 15908: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 15909: stepm, weightopt,\
15910: model,imx,p,matcov,agemortsup);
15911:
1.302 brouard 15912: free_vector(lsurv,agegomp,AGESUP);
15913: free_vector(lpop,agegomp,AGESUP);
15914: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 15915: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 15916: free_ivector(dcwave,firstobs,lastobs);
15917: free_vector(agecens,firstobs,lastobs);
15918: free_vector(ageexmed,firstobs,lastobs);
15919: free_ivector(cens,firstobs,lastobs);
1.220 brouard 15920: #ifdef GSL
1.136 brouard 15921: #endif
1.186 brouard 15922: } /* Endof if mle==-3 mortality only */
1.205 brouard 15923: /* Standard */
15924: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
15925: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
15926: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 15927: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 15928: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
15929: for (k=1; k<=npar;k++)
15930: printf(" %d %8.5f",k,p[k]);
15931: printf("\n");
1.205 brouard 15932: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
15933: /* mlikeli uses func not funcone */
1.247 brouard 15934: /* for(i=1;i<nlstate;i++){ */
15935: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
15936: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
15937: /* } */
1.205 brouard 15938: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
15939: }
15940: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
15941: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
15942: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
15943: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
15944: }
15945: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 15946: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
15947: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 15948: /* exit(0); */
1.126 brouard 15949: for (k=1; k<=npar;k++)
15950: printf(" %d %8.5f",k,p[k]);
15951: printf("\n");
15952:
15953: /*--------- results files --------------*/
1.283 brouard 15954: /* fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle= 0 weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, weightopt,model); */
1.126 brouard 15955:
15956:
15957: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 15958: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 15959: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 15960:
15961: printf("#model= 1 + age ");
15962: fprintf(ficres,"#model= 1 + age ");
15963: fprintf(ficlog,"#model= 1 + age ");
15964: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
15965: </ul>", model);
15966:
15967: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
15968: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
15969: if(nagesqr==1){
15970: printf(" + age*age ");
15971: fprintf(ficres," + age*age ");
15972: fprintf(ficlog," + age*age ");
15973: fprintf(fichtm, "<th>+ age*age</th>");
15974: }
15975: for(j=1;j <=ncovmodel-2;j++){
15976: if(Typevar[j]==0) {
15977: printf(" + V%d ",Tvar[j]);
15978: fprintf(ficres," + V%d ",Tvar[j]);
15979: fprintf(ficlog," + V%d ",Tvar[j]);
15980: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
15981: }else if(Typevar[j]==1) {
15982: printf(" + V%d*age ",Tvar[j]);
15983: fprintf(ficres," + V%d*age ",Tvar[j]);
15984: fprintf(ficlog," + V%d*age ",Tvar[j]);
15985: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
15986: }else if(Typevar[j]==2) {
15987: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
15988: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
15989: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
15990: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 15991: }else if(Typevar[j]==3) { /* TO VERIFY */
15992: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
15993: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
15994: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
15995: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 15996: }
15997: }
15998: printf("\n");
15999: fprintf(ficres,"\n");
16000: fprintf(ficlog,"\n");
16001: fprintf(fichtm, "</tr>");
16002: fprintf(fichtm, "\n");
16003:
16004:
1.126 brouard 16005: for(i=1,jk=1; i <=nlstate; i++){
16006: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 16007: if (k != i) {
1.319 brouard 16008: fprintf(fichtm, "<tr>");
1.225 brouard 16009: printf("%d%d ",i,k);
16010: fprintf(ficlog,"%d%d ",i,k);
16011: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 16012: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 16013: for(j=1; j <=ncovmodel; j++){
16014: printf("%12.7f ",p[jk]);
16015: fprintf(ficlog,"%12.7f ",p[jk]);
16016: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 16017: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 16018: jk++;
16019: }
16020: printf("\n");
16021: fprintf(ficlog,"\n");
16022: fprintf(ficres,"\n");
1.319 brouard 16023: fprintf(fichtm, "</tr>\n");
1.225 brouard 16024: }
1.126 brouard 16025: }
16026: }
1.319 brouard 16027: /* fprintf(fichtm,"</tr>\n"); */
16028: fprintf(fichtm,"</table>\n");
16029: fprintf(fichtm, "\n");
16030:
1.203 brouard 16031: if(mle != 0){
16032: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 16033: ftolhess=ftol; /* Usually correct */
1.203 brouard 16034: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
16035: printf("Parameters and 95%% confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W .\n But be careful that parameters are highly correlated because incidence of disability is highly correlated to incidence of recovery.\n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n");
16036: fprintf(ficlog, "Parameters, Wald tests and Wald-based confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W \n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n");
1.322 brouard 16037: fprintf(fichtm, "\n<p>The Wald test results are output only if the maximimzation of the Likelihood is performed (mle=1)\n</br>Parameters, Wald tests and Wald-based confidence intervals\n</br> W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n</br> And Wald-based confidence intervals plus and minus 1.96 * W \n </br> It might be better to visualize the covariance matrix. See the page '<a href=\"%s\">Matrix of variance-covariance of one-step probabilities and its graphs</a>'.\n</br>",optionfilehtmcov);
1.319 brouard 16038: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
16039: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
16040: if(nagesqr==1){
16041: printf(" + age*age ");
16042: fprintf(ficres," + age*age ");
16043: fprintf(ficlog," + age*age ");
16044: fprintf(fichtm, "<th>+ age*age</th>");
16045: }
16046: for(j=1;j <=ncovmodel-2;j++){
16047: if(Typevar[j]==0) {
16048: printf(" + V%d ",Tvar[j]);
16049: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
16050: }else if(Typevar[j]==1) {
16051: printf(" + V%d*age ",Tvar[j]);
16052: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
16053: }else if(Typevar[j]==2) {
16054: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 16055: }else if(Typevar[j]==3) { /* TO VERIFY */
16056: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 16057: }
16058: }
16059: fprintf(fichtm, "</tr>\n");
16060:
1.203 brouard 16061: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 16062: for(k=1; k <=(nlstate+ndeath); k++){
16063: if (k != i) {
1.319 brouard 16064: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 16065: printf("%d%d ",i,k);
16066: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 16067: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 16068: for(j=1; j <=ncovmodel; j++){
1.319 brouard 16069: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 16070: printf("%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
16071: fprintf(ficlog,"%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.319 brouard 16072: if(fabs(wald) > 1.96){
1.321 brouard 16073: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 16074: }else{
16075: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
16076: }
1.324 brouard 16077: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 16078: fprintf(fichtm,"[%12.7f;%12.7f]</br></td>", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.225 brouard 16079: jk++;
16080: }
16081: printf("\n");
16082: fprintf(ficlog,"\n");
1.319 brouard 16083: fprintf(fichtm, "</tr>\n");
1.225 brouard 16084: }
16085: }
1.193 brouard 16086: }
1.203 brouard 16087: } /* end of hesscov and Wald tests */
1.319 brouard 16088: fprintf(fichtm,"</table>\n");
1.225 brouard 16089:
1.203 brouard 16090: /* */
1.126 brouard 16091: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
16092: printf("# Scales (for hessian or gradient estimation)\n");
16093: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
16094: for(i=1,jk=1; i <=nlstate; i++){
16095: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 16096: if (j!=i) {
16097: fprintf(ficres,"%1d%1d",i,j);
16098: printf("%1d%1d",i,j);
16099: fprintf(ficlog,"%1d%1d",i,j);
16100: for(k=1; k<=ncovmodel;k++){
16101: printf(" %.5e",delti[jk]);
16102: fprintf(ficlog," %.5e",delti[jk]);
16103: fprintf(ficres," %.5e",delti[jk]);
16104: jk++;
16105: }
16106: printf("\n");
16107: fprintf(ficlog,"\n");
16108: fprintf(ficres,"\n");
16109: }
1.126 brouard 16110: }
16111: }
16112:
16113: fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
1.349 brouard 16114: if(mle >= 1) /* Too big for the screen */
1.126 brouard 16115: printf("# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
16116: fprintf(ficlog,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
16117: /* # 121 Var(a12)\n\ */
16118: /* # 122 Cov(b12,a12) Var(b12)\n\ */
16119: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
16120: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
16121: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
16122: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
16123: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
16124: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
16125:
16126:
16127: /* Just to have a covariance matrix which will be more understandable
16128: even is we still don't want to manage dictionary of variables
16129: */
16130: for(itimes=1;itimes<=2;itimes++){
16131: jj=0;
16132: for(i=1; i <=nlstate; i++){
1.225 brouard 16133: for(j=1; j <=nlstate+ndeath; j++){
16134: if(j==i) continue;
16135: for(k=1; k<=ncovmodel;k++){
16136: jj++;
16137: ca[0]= k+'a'-1;ca[1]='\0';
16138: if(itimes==1){
16139: if(mle>=1)
16140: printf("#%1d%1d%d",i,j,k);
16141: fprintf(ficlog,"#%1d%1d%d",i,j,k);
16142: fprintf(ficres,"#%1d%1d%d",i,j,k);
16143: }else{
16144: if(mle>=1)
16145: printf("%1d%1d%d",i,j,k);
16146: fprintf(ficlog,"%1d%1d%d",i,j,k);
16147: fprintf(ficres,"%1d%1d%d",i,j,k);
16148: }
16149: ll=0;
16150: for(li=1;li <=nlstate; li++){
16151: for(lj=1;lj <=nlstate+ndeath; lj++){
16152: if(lj==li) continue;
16153: for(lk=1;lk<=ncovmodel;lk++){
16154: ll++;
16155: if(ll<=jj){
16156: cb[0]= lk +'a'-1;cb[1]='\0';
16157: if(ll<jj){
16158: if(itimes==1){
16159: if(mle>=1)
16160: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16161: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16162: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16163: }else{
16164: if(mle>=1)
16165: printf(" %.5e",matcov[jj][ll]);
16166: fprintf(ficlog," %.5e",matcov[jj][ll]);
16167: fprintf(ficres," %.5e",matcov[jj][ll]);
16168: }
16169: }else{
16170: if(itimes==1){
16171: if(mle>=1)
16172: printf(" Var(%s%1d%1d)",ca,i,j);
16173: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
16174: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
16175: }else{
16176: if(mle>=1)
16177: printf(" %.7e",matcov[jj][ll]);
16178: fprintf(ficlog," %.7e",matcov[jj][ll]);
16179: fprintf(ficres," %.7e",matcov[jj][ll]);
16180: }
16181: }
16182: }
16183: } /* end lk */
16184: } /* end lj */
16185: } /* end li */
16186: if(mle>=1)
16187: printf("\n");
16188: fprintf(ficlog,"\n");
16189: fprintf(ficres,"\n");
16190: numlinepar++;
16191: } /* end k*/
16192: } /*end j */
1.126 brouard 16193: } /* end i */
16194: } /* end itimes */
16195:
16196: fflush(ficlog);
16197: fflush(ficres);
1.225 brouard 16198: while(fgets(line, MAXLINE, ficpar)) {
16199: /* If line starts with a # it is a comment */
16200: if (line[0] == '#') {
16201: numlinepar++;
16202: fputs(line,stdout);
16203: fputs(line,ficparo);
16204: fputs(line,ficlog);
1.299 brouard 16205: fputs(line,ficres);
1.225 brouard 16206: continue;
16207: }else
16208: break;
16209: }
16210:
1.209 brouard 16211: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
16212: /* ungetc(c,ficpar); */
16213: /* fgets(line, MAXLINE, ficpar); */
16214: /* fputs(line,stdout); */
16215: /* fputs(line,ficparo); */
16216: /* } */
16217: /* ungetc(c,ficpar); */
1.126 brouard 16218:
16219: estepm=0;
1.209 brouard 16220: if((num_filled=sscanf(line,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm, &ftolpl)) !=EOF){
1.225 brouard 16221:
16222: if (num_filled != 6) {
16223: printf("Error: Not 6 parameters in line, for example:agemin=60 agemax=95 bage=55 fage=95 estepm=24 ftolpl=6e-4\n, your line=%s . Probably you are running an older format.\n",line);
16224: fprintf(ficlog,"Error: Not 6 parameters in line, for example:agemin=60 agemax=95 bage=55 fage=95 estepm=24 ftolpl=6e-4\n, your line=%s . Probably you are running an older format.\n",line);
16225: goto end;
16226: }
16227: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
16228: }
16229: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
16230: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
16231:
1.209 brouard 16232: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 16233: if (estepm==0 || estepm < stepm) estepm=stepm;
16234: if (fage <= 2) {
16235: bage = ageminpar;
16236: fage = agemaxpar;
16237: }
16238:
16239: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 16240: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
16241: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 16242:
1.186 brouard 16243: /* Other stuffs, more or less useful */
1.254 brouard 16244: while(fgets(line, MAXLINE, ficpar)) {
16245: /* If line starts with a # it is a comment */
16246: if (line[0] == '#') {
16247: numlinepar++;
16248: fputs(line,stdout);
16249: fputs(line,ficparo);
16250: fputs(line,ficlog);
1.299 brouard 16251: fputs(line,ficres);
1.254 brouard 16252: continue;
16253: }else
16254: break;
16255: }
16256:
16257: if((num_filled=sscanf(line,"begin-prev-date=%lf/%lf/%lf end-prev-date=%lf/%lf/%lf mov_average=%d\n",&jprev1, &mprev1,&anprev1,&jprev2, &mprev2,&anprev2,&mobilav)) !=EOF){
16258:
16259: if (num_filled != 7) {
16260: printf("Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
16261: fprintf(ficlog,"Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
16262: goto end;
16263: }
16264: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
16265: fprintf(ficparo,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
16266: fprintf(ficres,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
16267: fprintf(ficlog,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
1.126 brouard 16268: }
1.254 brouard 16269:
16270: while(fgets(line, MAXLINE, ficpar)) {
16271: /* If line starts with a # it is a comment */
16272: if (line[0] == '#') {
16273: numlinepar++;
16274: fputs(line,stdout);
16275: fputs(line,ficparo);
16276: fputs(line,ficlog);
1.299 brouard 16277: fputs(line,ficres);
1.254 brouard 16278: continue;
16279: }else
16280: break;
1.126 brouard 16281: }
16282:
16283:
16284: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
16285: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
16286:
1.254 brouard 16287: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
16288: if (num_filled != 1) {
16289: printf("Error: Not 1 (data)parameters in line but %d, for example:pop_based=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
16290: fprintf(ficlog,"Error: Not 1 (data)parameters in line but %d, for example: pop_based=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
16291: goto end;
16292: }
16293: printf("pop_based=%d\n",popbased);
16294: fprintf(ficlog,"pop_based=%d\n",popbased);
16295: fprintf(ficparo,"pop_based=%d\n",popbased);
16296: fprintf(ficres,"pop_based=%d\n",popbased);
16297: }
16298:
1.258 brouard 16299: /* Results */
1.359 brouard 16300: /* Value of covariate in each resultine will be computed (if product) and sorted according to model rank */
1.332 brouard 16301: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
16302: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 16303: endishere=0;
1.258 brouard 16304: nresult=0;
1.308 brouard 16305: parameterline=0;
1.258 brouard 16306: do{
16307: if(!fgets(line, MAXLINE, ficpar)){
16308: endishere=1;
1.308 brouard 16309: parameterline=15;
1.258 brouard 16310: }else if (line[0] == '#') {
16311: /* If line starts with a # it is a comment */
1.254 brouard 16312: numlinepar++;
16313: fputs(line,stdout);
16314: fputs(line,ficparo);
16315: fputs(line,ficlog);
1.299 brouard 16316: fputs(line,ficres);
1.254 brouard 16317: continue;
1.258 brouard 16318: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
16319: parameterline=11;
1.296 brouard 16320: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 16321: parameterline=12;
1.307 brouard 16322: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 16323: parameterline=13;
1.307 brouard 16324: }
1.258 brouard 16325: else{
16326: parameterline=14;
1.254 brouard 16327: }
1.308 brouard 16328: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 16329: case 11:
1.296 brouard 16330: if((num_filled=sscanf(line,"prevforecast=%d starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf mobil_average=%d\n",&prevfcast,&jproj1,&mproj1,&anproj1,&jproj2,&mproj2,&anproj2,&mobilavproj)) !=EOF && (num_filled == 8)){
16331: fprintf(ficparo,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
1.258 brouard 16332: printf("prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
16333: fprintf(ficlog,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
16334: fprintf(ficres,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
16335: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 16336: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
16337: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 16338: prvforecast = 1;
16339: }
16340: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 16341: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
16342: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
16343: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 16344: prvforecast = 2;
16345: }
16346: else {
16347: printf("Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevforecast=1 yearsfproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
16348: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevforecast=1 yearproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
16349: goto end;
1.258 brouard 16350: }
1.254 brouard 16351: break;
1.258 brouard 16352: case 12:
1.296 brouard 16353: if((num_filled=sscanf(line,"prevbackcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&prevbcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj)) !=EOF && (num_filled == 8)){
16354: fprintf(ficparo,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
16355: printf("prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
16356: fprintf(ficlog,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
16357: fprintf(ficres,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
16358: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 16359: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
16360: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 16361: prvbackcast = 1;
16362: }
16363: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 16364: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
16365: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
16366: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 16367: prvbackcast = 2;
16368: }
16369: else {
16370: printf("Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearsbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
16371: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
16372: goto end;
1.258 brouard 16373: }
1.230 brouard 16374: break;
1.258 brouard 16375: case 13:
1.332 brouard 16376: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 16377: nresult++; /* Sum of resultlines */
1.342 brouard 16378: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 16379: /* removefirstspace(&resultlineori); */
16380:
16381: if(strstr(resultlineori,"v") !=0){
16382: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
16383: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
16384: return 1;
16385: }
16386: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 16387: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 16388: if(nresult > MAXRESULTLINESPONE-1){
16389: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
16390: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
1.307 brouard 16391: goto end;
16392: }
1.332 brouard 16393:
1.310 brouard 16394: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 16395: fprintf(ficparo,"result: %s\n",resultline);
16396: fprintf(ficres,"result: %s\n",resultline);
16397: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 16398: } else
16399: goto end;
1.307 brouard 16400: break;
16401: case 14:
16402: printf("Error: Unknown command '%s'\n",line);
16403: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 16404: if(line[0] == ' ' || line[0] == '\n'){
16405: printf("It should not be an empty line '%s'\n",line);
16406: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
16407: }
1.307 brouard 16408: if(ncovmodel >=2 && nresult==0 ){
16409: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
16410: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 16411: }
1.307 brouard 16412: /* goto end; */
16413: break;
1.308 brouard 16414: case 15:
16415: printf("End of resultlines.\n");
16416: fprintf(ficlog,"End of resultlines.\n");
16417: break;
16418: default: /* parameterline =0 */
1.307 brouard 16419: nresult=1;
16420: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 16421: } /* End switch parameterline */
16422: }while(endishere==0); /* End do */
1.126 brouard 16423:
1.230 brouard 16424: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 16425: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 16426:
16427: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 16428: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 16429: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 16430: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
16431: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 16432: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 16433: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
16434: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 16435: }else{
1.270 brouard 16436: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 16437: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
16438: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
16439: if(prvforecast==1){
16440: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
16441: jprojd=jproj1;
16442: mprojd=mproj1;
16443: anprojd=anproj1;
16444: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
16445: jprojf=jproj2;
16446: mprojf=mproj2;
16447: anprojf=anproj2;
16448: } else if(prvforecast == 2){
16449: dateprojd=dateintmean;
16450: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
16451: dateprojf=dateintmean+yrfproj;
16452: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
16453: }
16454: if(prvbackcast==1){
16455: datebackd=(jback1+12*mback1+365*anback1)/365;
16456: jbackd=jback1;
16457: mbackd=mback1;
16458: anbackd=anback1;
16459: datebackf=(jback2+12*mback2+365*anback2)/365;
16460: jbackf=jback2;
16461: mbackf=mback2;
16462: anbackf=anback2;
16463: } else if(prvbackcast == 2){
16464: datebackd=dateintmean;
16465: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
16466: datebackf=dateintmean-yrbproj;
16467: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
16468: }
16469:
1.350 brouard 16470: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 16471: }
16472: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 16473: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
16474: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 16475:
1.225 brouard 16476: /*------------ free_vector -------------*/
16477: /* chdir(path); */
1.220 brouard 16478:
1.215 brouard 16479: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
16480: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
16481: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
16482: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 16483: free_lvector(num,firstobs,lastobs);
16484: free_vector(agedc,firstobs,lastobs);
1.126 brouard 16485: /*free_matrix(covar,0,NCOVMAX,1,n);*/
16486: /*free_matrix(covar,1,NCOVMAX,1,n);*/
16487: fclose(ficparo);
16488: fclose(ficres);
1.220 brouard 16489:
16490:
1.186 brouard 16491: /* Other results (useful)*/
1.220 brouard 16492:
16493:
1.126 brouard 16494: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 16495: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
16496: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 16497: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 16498: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 16499: fclose(ficrespl);
16500:
16501: /*------------- h Pij x at various ages ------------*/
1.180 brouard 16502: /*#include "hpijx.h"*/
1.332 brouard 16503: /** h Pij x Probability to be in state j at age x+h being in i at x, for each combination k of dummies in the model line or to nres?*/
16504: /* calls hpxij with combination k */
1.180 brouard 16505: hPijx(p, bage, fage);
1.145 brouard 16506: fclose(ficrespij);
1.227 brouard 16507:
1.220 brouard 16508: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 16509: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 16510: k=1;
1.126 brouard 16511: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 16512:
1.269 brouard 16513: /* Prevalence for each covariate combination in probs[age][status][cov] */
16514: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
16515: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 16516: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 16517: for(k=1;k<=ncovcombmax;k++)
16518: probs[i][j][k]=0.;
1.269 brouard 16519: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
16520: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 16521: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 16522: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
16523: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 16524: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 16525: for(k=1;k<=ncovcombmax;k++)
16526: mobaverages[i][j][k]=0.;
1.219 brouard 16527: mobaverage=mobaverages;
16528: if (mobilav!=0) {
1.235 brouard 16529: printf("Movingaveraging observed prevalence\n");
1.258 brouard 16530: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 16531: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
16532: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
16533: printf(" Error in movingaverage mobilav=%d\n",mobilav);
16534: }
1.269 brouard 16535: } else if (mobilavproj !=0) {
1.235 brouard 16536: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 16537: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 16538: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
16539: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
16540: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
16541: }
1.269 brouard 16542: }else{
16543: printf("Internal error moving average\n");
16544: fflush(stdout);
16545: exit(1);
1.219 brouard 16546: }
16547: }/* end if moving average */
1.227 brouard 16548:
1.126 brouard 16549: /*---------- Forecasting ------------------*/
1.296 brouard 16550: if(prevfcast==1){
16551: /* /\* if(stepm ==1){*\/ */
16552: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
16553: /*This done previously after freqsummary.*/
16554: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
16555: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
16556:
16557: /* } else if (prvforecast==2){ */
16558: /* /\* if(stepm ==1){*\/ */
16559: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
16560: /* } */
16561: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
16562: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 16563: }
1.269 brouard 16564:
1.296 brouard 16565: /* Prevbcasting */
16566: if(prevbcast==1){
1.219 brouard 16567: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16568: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16569: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16570:
16571: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
16572:
16573: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 16574:
1.219 brouard 16575: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
16576: fclose(ficresplb);
16577:
1.222 brouard 16578: hBijx(p, bage, fage, mobaverage);
16579: fclose(ficrespijb);
1.219 brouard 16580:
1.296 brouard 16581: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
16582: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
16583: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
16584: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
16585: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
16586: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
16587:
16588:
1.269 brouard 16589: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 16590:
16591:
1.269 brouard 16592: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 16593: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
16594: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
16595: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 16596: } /* end Prevbcasting */
1.268 brouard 16597:
1.186 brouard 16598:
16599: /* ------ Other prevalence ratios------------ */
1.126 brouard 16600:
1.215 brouard 16601: free_ivector(wav,1,imx);
16602: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
16603: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
16604: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 16605:
16606:
1.127 brouard 16607: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 16608:
1.201 brouard 16609: strcpy(filerese,"E_");
16610: strcat(filerese,fileresu);
1.126 brouard 16611: if((ficreseij=fopen(filerese,"w"))==NULL) {
16612: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
16613: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
16614: }
1.208 brouard 16615: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
16616: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 16617:
16618: pstamp(ficreseij);
1.219 brouard 16619:
1.351 brouard 16620: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
16621: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 16622:
1.351 brouard 16623: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
16624: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
16625: /* if(i1 != 1 && TKresult[nres]!= k) */
16626: /* continue; */
1.219 brouard 16627: fprintf(ficreseij,"\n#****** ");
1.235 brouard 16628: printf("\n#****** ");
1.351 brouard 16629: for(j=1;j<=cptcovs;j++){
16630: /* for(j=1;j<=cptcoveff;j++) { */
16631: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16632: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
16633: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
16634: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 16635: }
16636: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 16637: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
16638: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 16639: }
16640: fprintf(ficreseij,"******\n");
1.235 brouard 16641: printf("******\n");
1.219 brouard 16642:
16643: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16644: oldm=oldms;savm=savms;
1.330 brouard 16645: /* printf("HELLO Entering evsij bage=%d fage=%d k=%d estepm=%d nres=%d\n",(int) bage, (int)fage, k, estepm, nres); */
1.235 brouard 16646: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 16647:
1.219 brouard 16648: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 16649: }
16650: fclose(ficreseij);
1.208 brouard 16651: printf("done evsij\n");fflush(stdout);
16652: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 16653:
1.218 brouard 16654:
1.227 brouard 16655: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 16656: /* Should be moved in a function */
1.201 brouard 16657: strcpy(filerest,"T_");
16658: strcat(filerest,fileresu);
1.127 brouard 16659: if((ficrest=fopen(filerest,"w"))==NULL) {
16660: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
16661: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
16662: }
1.208 brouard 16663: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
16664: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 16665: strcpy(fileresstde,"STDE_");
16666: strcat(fileresstde,fileresu);
1.126 brouard 16667: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 16668: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
16669: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 16670: }
1.227 brouard 16671: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
16672: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 16673:
1.201 brouard 16674: strcpy(filerescve,"CVE_");
16675: strcat(filerescve,fileresu);
1.126 brouard 16676: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 16677: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
16678: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 16679: }
1.227 brouard 16680: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
16681: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 16682:
1.201 brouard 16683: strcpy(fileresv,"V_");
16684: strcat(fileresv,fileresu);
1.126 brouard 16685: if((ficresvij=fopen(fileresv,"w"))==NULL) {
16686: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
16687: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
16688: }
1.227 brouard 16689: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
16690: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 16691:
1.235 brouard 16692: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
16693: if (cptcovn < 1){i1=1;}
16694:
1.334 brouard 16695: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
16696: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
16697: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
16698: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
16699: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
16700: /* */
16701: if(i1 != 1 && TKresult[nres]!= k) /* TKresult[nres] is the combination of this nres resultline. All the i1 combinations are not output */
1.235 brouard 16702: continue;
1.359 brouard 16703: printf("\n# model=1+age+%s \n#****** Result for:", model); /* HERE model is empty */
16704: fprintf(ficrest,"\n# model=1+age+%s \n#****** Result for:", model);
16705: fprintf(ficlog,"\n# model=1+age+%s \n#****** Result for:", model);
1.334 brouard 16706: /* It might not be a good idea to mix dummies and quantitative */
16707: /* for(j=1;j<=cptcoveff;j++){ /\* j=resultpos. Could be a loop on cptcovs: number of single dummy covariate in the result line as well as in the model *\/ */
16708: for(j=1;j<=cptcovs;j++){ /* j=resultpos. Could be a loop on cptcovs: number of single covariate (dummy or quantitative) in the result line as well as in the model */
16709: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
16710: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
16711: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
16712: * (V5 is quanti) V4 and V3 are dummies
16713: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
16714: * l=1 l=2
16715: * k=1 1 1 0 0
16716: * k=2 2 1 1 0
16717: * k=3 [1] [2] 0 1
16718: * k=4 2 2 1 1
16719: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
16720: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
16721: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
16722: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
16723: */
16724: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
16725: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
16726: /* We give up with the combinations!! */
1.342 brouard 16727: /* if(debugILK) */
16728: /* printf("\n j=%d In computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d Fixed[modelresult[nres][j]]=%d\n", j, nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff,Fixed[modelresult[nres][j]]); /\* end if dummy or quanti *\/ */
1.334 brouard 16729:
16730: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
1.344 brouard 16731: /* printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /\* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline *\/ */ /* TinvDoQresult[nres][Name of the variable] */
16732: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordered by the covariate values in the resultline */
16733: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
16734: fprintf(ficrest,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
1.334 brouard 16735: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
16736: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
16737: }else{
16738: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
16739: }
16740: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16741: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16742: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
16743: /* For each selected (single) quantitative value */
1.337 brouard 16744: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
16745: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
16746: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 16747: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
16748: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
16749: }else{
16750: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
16751: }
16752: }else{
16753: printf("Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff); /* end if dummy or quanti */
16754: fprintf(ficlog,"Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff); /* end if dummy or quanti */
16755: exit(1);
16756: }
1.335 brouard 16757: } /* End loop for each variable in the resultline */
1.334 brouard 16758: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
16759: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
16760: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
16761: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
16762: /* } */
1.208 brouard 16763: fprintf(ficrest,"******\n");
1.227 brouard 16764: fprintf(ficlog,"******\n");
16765: printf("******\n");
1.208 brouard 16766:
16767: fprintf(ficresstdeij,"\n#****** ");
16768: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 16769: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
16770: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 16771: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 16772: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
16773: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16774: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16775: }
16776: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value, TvarsQind gives the position of a quantitative in model equation */
1.337 brouard 16777: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
16778: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 16779: }
1.208 brouard 16780: fprintf(ficresstdeij,"******\n");
16781: fprintf(ficrescveij,"******\n");
16782:
16783: fprintf(ficresvij,"\n#****** ");
1.238 brouard 16784: /* pstamp(ficresvij); */
1.225 brouard 16785: for(j=1;j<=cptcoveff;j++)
1.335 brouard 16786: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
16787: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 16788: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 16789: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 16790: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 16791: }
1.208 brouard 16792: fprintf(ficresvij,"******\n");
16793:
16794: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16795: oldm=oldms;savm=savms;
1.235 brouard 16796: printf(" cvevsij ");
16797: fprintf(ficlog, " cvevsij ");
16798: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 16799: printf(" end cvevsij \n ");
16800: fprintf(ficlog, " end cvevsij \n ");
16801:
16802: /*
16803: */
16804: /* goto endfree; */
16805:
16806: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16807: pstamp(ficrest);
16808:
1.269 brouard 16809: epj=vector(1,nlstate+1);
1.208 brouard 16810: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 16811: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
16812: cptcod= 0; /* To be deleted */
1.360 brouard 16813: printf("varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased);
16814: fprintf(ficlog, "varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased);
1.361 ! brouard 16815: /* Call to varevsij to get cov(e.i, e.j)= vareij[i][j][(int)age]=sum_h sum_k trgrad(h_p.i) V(theta) grad(k_p.k) Equation 20 */
! 16816: /* Depending of popbased which changes the prevalences, either cross-sectional or period */
1.235 brouard 16817: varevsij(optionfilefiname, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, &ncvyear, k, estepm, cptcov,cptcod,vpopbased,mobilav, strstart, nres); /* cptcod not initialized Intel */
1.360 brouard 16818: fprintf(ficrest,"# Total life expectancy with std error and decomposition into time to be expected in each state\n\
16819: # (these are weighted average of eij where weights are ");
1.227 brouard 16820: if(vpopbased==1)
1.360 brouard 16821: fprintf(ficrest,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally)\n in each health state (popbased=1) (mobilav=%d)\n",mobilav);
1.227 brouard 16822: else
1.360 brouard 16823: fprintf(ficrest,"the age specific forward period (stable) prevalences in each state) \n");
16824: fprintf(ficrest,"# with proportions of time spent in each state with standard error (on the right of the table.\n ");
1.335 brouard 16825: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 16826: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
1.360 brouard 16827: for (i=1;i<=nlstate;i++) fprintf(ficrest," %% e.%d/e.. (std) ",i);
1.227 brouard 16828: fprintf(ficrest,"\n");
16829: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 16830: printf("Computing age specific forward period (stable) prevalences in each health state \n");
16831: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 16832: for(age=bage; age <=fage ;age++){
1.235 brouard 16833: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 16834: if (vpopbased==1) {
16835: if(mobilav ==0){
16836: for(i=1; i<=nlstate;i++)
16837: prlim[i][i]=probs[(int)age][i][k];
16838: }else{ /* mobilav */
16839: for(i=1; i<=nlstate;i++)
16840: prlim[i][i]=mobaverage[(int)age][i][k];
16841: }
16842: }
1.219 brouard 16843:
1.227 brouard 16844: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
16845: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
16846: /* printf(" age %4.0f ",age); */
16847: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
16848: for(i=1, epj[j]=0.;i <=nlstate;i++) {
16849: epj[j] += prlim[i][i]*eij[i][j][(int)age];
16850: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
16851: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
16852: }
1.361 ! brouard 16853: epj[nlstate+1] +=epj[j]; /* epp=sum_j epj = sum_j sum_i w_i e_ij */
1.227 brouard 16854: }
16855: /* printf(" age %4.0f \n",age); */
1.219 brouard 16856:
1.361 ! brouard 16857: for(i=1, vepp=0.;i <=nlstate;i++) /* Variance of total life expectancy e.. */
1.227 brouard 16858: for(j=1;j <=nlstate;j++)
1.361 ! brouard 16859: vepp += vareij[i][j][(int)age]; /* sum_i sum_j cov(e.i, e.j) = var(e..) */
1.227 brouard 16860: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
1.361 ! brouard 16861: /* vareij[i][j] is the covariance cov(e.i, e.j) and vareij[j][j] is the variance of e.j */
1.227 brouard 16862: for(j=1;j <=nlstate;j++){
16863: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
16864: }
1.360 brouard 16865: /* And proportion of time spent in state j */
16866: /* $$ E[r(X,Y)-E(r(X,Y))]^2=[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]' Var(X,Y)[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]$$ */
1.361 ! brouard 16867: /* \frac{\mu_x^2}{\mu_y^2} ( \frac{\sigma^2_x}{\mu_x^2}-2\frac{\sigma_{xy}}{\mu_x\mu_y} +\frac{\sigma^2_y}{\mu_y^2}) */
! 16868: /* \frac{e_{.i}^2}{e_{..}^2} ( \frac{\Var e_{.i}}{e_{.i}^2}-2\frac{\Var e_{.i} + \sum_{j\ne i} \Cov e_{.j},e_{.i}}{e_{.i}e_{..}} +\frac{\Var e_{..}}{e_{..}^2})*/
! 16869: /*\mu_x = epj[j], \sigma^2_x = vareij[j][j][(int)age] and \mu_y=epj[nlstate+1], \sigma^2_y=vepp \sigmaxy= */
! 16870: /* vareij[j][j][(int)age]/epj[nlstate+1]^2 + vepp/epj[nlstate+1]^4 */
1.360 brouard 16871: for(j=1;j <=nlstate;j++){
16872: /* fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt( vareij[j][j][(int)age]/epj[j]/epj[j] + vepp/epj[j]/epj[j]/epj[j]/epj[j] )); */
1.361 ! brouard 16873: /* fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt( vareij[j][j][(int)age]/epj[j]/epj[j] + vepp/epj[j]/epj[j]/epj[j]/epj[j] )); */
! 16874:
! 16875: for(i=1,stdpercent=0.;i<=nlstate;i++){ /* Computing cov(e..,e.j)=cov(sum_i e.i,e.j)=sum_i cov(e.i, e.j) */
! 16876: stdpercent += vareij[i][j][(int)age];
! 16877: }
! 16878: stdpercent= epj[j]*epj[j]/epj[nlstate+1]/epj[nlstate+1]* (vareij[j][j][(int)age]/epj[j]/epj[j]-2.*stdpercent/epj[j]/epj[nlstate+1]+ vepp/epj[nlstate+1]/epj[nlstate+1]);
! 16879: /* stdpercent= epj[j]*epj[j]/epj[nlstate+1]/epj[nlstate+1]*(vareij[j][j][(int)age]/epj[j]/epj[j] + vepp/epj[nlstate+1]/epj[nlstate+1]); */ /* Without covariance */
! 16880: /* fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt( vareij[j][j][(int)age]/epj[nlstate+1]/epj[nlstate+1] + epj[j]*epj[j]*vepp/epj[nlstate+1]/epj[nlstate+1]/epj[nlstate+1]/epj[nlstate+1] )); */
! 16881: fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt(stdpercent));
1.360 brouard 16882: }
1.227 brouard 16883: fprintf(ficrest,"\n");
16884: }
1.208 brouard 16885: } /* End vpopbased */
1.269 brouard 16886: free_vector(epj,1,nlstate+1);
1.208 brouard 16887: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
16888: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 16889: printf("done selection\n");fflush(stdout);
16890: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 16891:
1.335 brouard 16892: } /* End k selection or end covariate selection for nres */
1.227 brouard 16893:
16894: printf("done State-specific expectancies\n");fflush(stdout);
16895: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
16896:
1.335 brouard 16897: /* variance-covariance of forward period prevalence */
1.269 brouard 16898: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 16899:
1.227 brouard 16900:
1.290 brouard 16901: free_vector(weight,firstobs,lastobs);
1.351 brouard 16902: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 16903: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 16904: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
16905: free_matrix(anint,1,maxwav,firstobs,lastobs);
16906: free_matrix(mint,1,maxwav,firstobs,lastobs);
16907: free_ivector(cod,firstobs,lastobs);
1.227 brouard 16908: free_ivector(tab,1,NCOVMAX);
16909: fclose(ficresstdeij);
16910: fclose(ficrescveij);
16911: fclose(ficresvij);
16912: fclose(ficrest);
16913: fclose(ficpar);
16914:
16915:
1.126 brouard 16916: /*---------- End : free ----------------*/
1.219 brouard 16917: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 16918: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
16919: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 16920: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
16921: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 16922: } /* mle==-3 arrives here for freeing */
1.227 brouard 16923: /* endfree:*/
1.359 brouard 16924: if(mle!=-3) free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
1.227 brouard 16925: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
16926: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
16927: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 16928: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
16929: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 16930: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
16931: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
16932: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 16933: free_matrix(matcov,1,npar,1,npar);
16934: free_matrix(hess,1,npar,1,npar);
16935: /*free_vector(delti,1,npar);*/
16936: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
16937: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 16938: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 16939: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
16940:
16941: free_ivector(ncodemax,1,NCOVMAX);
16942: free_ivector(ncodemaxwundef,1,NCOVMAX);
16943: free_ivector(Dummy,-1,NCOVMAX);
16944: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 16945: free_ivector(DummyV,-1,NCOVMAX);
16946: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 16947: free_ivector(Typevar,-1,NCOVMAX);
16948: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 16949: free_ivector(TvarsQ,1,NCOVMAX);
16950: free_ivector(TvarsQind,1,NCOVMAX);
16951: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 16952: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 16953: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 16954: free_ivector(TvarFD,1,NCOVMAX);
16955: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 16956: free_ivector(TvarF,1,NCOVMAX);
16957: free_ivector(TvarFind,1,NCOVMAX);
16958: free_ivector(TvarV,1,NCOVMAX);
16959: free_ivector(TvarVind,1,NCOVMAX);
16960: free_ivector(TvarA,1,NCOVMAX);
16961: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 16962: free_ivector(TvarFQ,1,NCOVMAX);
16963: free_ivector(TvarFQind,1,NCOVMAX);
16964: free_ivector(TvarVD,1,NCOVMAX);
16965: free_ivector(TvarVDind,1,NCOVMAX);
16966: free_ivector(TvarVQ,1,NCOVMAX);
16967: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 16968: free_ivector(TvarAVVA,1,NCOVMAX);
16969: free_ivector(TvarAVVAind,1,NCOVMAX);
16970: free_ivector(TvarVVA,1,NCOVMAX);
16971: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 16972: free_ivector(TvarVV,1,NCOVMAX);
16973: free_ivector(TvarVVind,1,NCOVMAX);
16974:
1.230 brouard 16975: free_ivector(Tvarsel,1,NCOVMAX);
16976: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 16977: free_ivector(Tposprod,1,NCOVMAX);
16978: free_ivector(Tprod,1,NCOVMAX);
16979: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 16980: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 16981: free_ivector(Tage,1,NCOVMAX);
16982: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 16983: free_ivector(TmodelInvind,1,NCOVMAX);
16984: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 16985:
1.359 brouard 16986: /* free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /\* Could be elsewhere ?*\/ */
1.332 brouard 16987:
1.227 brouard 16988: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
16989: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 16990: fflush(fichtm);
16991: fflush(ficgp);
16992:
1.227 brouard 16993:
1.126 brouard 16994: if((nberr >0) || (nbwarn>0)){
1.216 brouard 16995: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
16996: fprintf(ficlog,"End of Imach with %d errors and/or warnings %d. Please look at the log file for details.\n",nberr,nbwarn);
1.126 brouard 16997: }else{
16998: printf("End of Imach\n");
16999: fprintf(ficlog,"End of Imach\n");
17000: }
17001: printf("See log file on %s\n",filelog);
17002: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 17003: /*(void) gettimeofday(&end_time,&tzp);*/
17004: rend_time = time(NULL);
17005: end_time = *localtime(&rend_time);
17006: /* tml = *localtime(&end_time.tm_sec); */
17007: strcpy(strtend,asctime(&end_time));
1.126 brouard 17008: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
17009: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 17010: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 17011:
1.157 brouard 17012: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
17013: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
17014: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 17015: /* printf("Total time was %d uSec.\n", total_usecs);*/
17016: /* if(fileappend(fichtm,optionfilehtm)){ */
17017: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
17018: fclose(fichtm);
17019: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
17020: fclose(fichtmcov);
17021: fclose(ficgp);
17022: fclose(ficlog);
17023: /*------ End -----------*/
1.227 brouard 17024:
1.281 brouard 17025:
17026: /* Executes gnuplot */
1.227 brouard 17027:
17028: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 17029: #ifdef WIN32
1.227 brouard 17030: if (_chdir(pathcd) != 0)
17031: printf("Can't move to directory %s!\n",path);
17032: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 17033: #else
1.227 brouard 17034: if(chdir(pathcd) != 0)
17035: printf("Can't move to directory %s!\n", path);
17036: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 17037: #endif
1.126 brouard 17038: printf("Current directory %s!\n",pathcd);
17039: /*strcat(plotcmd,CHARSEPARATOR);*/
17040: sprintf(plotcmd,"gnuplot");
1.157 brouard 17041: #ifdef _WIN32
1.126 brouard 17042: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
17043: #endif
17044: if(!stat(plotcmd,&info)){
1.158 brouard 17045: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 17046: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 17047: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 17048: }else
17049: strcpy(pplotcmd,plotcmd);
1.157 brouard 17050: #ifdef __unix
1.126 brouard 17051: strcpy(plotcmd,GNUPLOTPROGRAM);
17052: if(!stat(plotcmd,&info)){
1.158 brouard 17053: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 17054: }else
17055: strcpy(pplotcmd,plotcmd);
17056: #endif
17057: }else
17058: strcpy(pplotcmd,plotcmd);
17059:
17060: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 17061: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 17062: strcpy(pplotcmd,plotcmd);
1.227 brouard 17063:
1.126 brouard 17064: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 17065: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 17066: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 17067: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 17068: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 17069: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 17070: strcpy(plotcmd,pplotcmd);
17071: }
1.126 brouard 17072: }
1.158 brouard 17073: printf(" Successful, please wait...");
1.126 brouard 17074: while (z[0] != 'q') {
17075: /* chdir(path); */
1.154 brouard 17076: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 17077: scanf("%s",z);
17078: /* if (z[0] == 'c') system("./imach"); */
17079: if (z[0] == 'e') {
1.158 brouard 17080: #ifdef __APPLE__
1.152 brouard 17081: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 17082: #elif __linux
17083: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 17084: #else
1.152 brouard 17085: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 17086: #endif
17087: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
17088: system(pplotcmd);
1.126 brouard 17089: }
17090: else if (z[0] == 'g') system(plotcmd);
17091: else if (z[0] == 'q') exit(0);
17092: }
1.227 brouard 17093: end:
1.126 brouard 17094: while (z[0] != 'q') {
1.195 brouard 17095: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 17096: scanf("%s",z);
17097: }
1.283 brouard 17098: printf("End\n");
1.282 brouard 17099: exit(0);
1.126 brouard 17100: }
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