Annotation of imach/src/imach.c, revision 1.356
1.356 ! brouard 1: /* $Id: imach.c,v 1.355 2023/05/22 17:03:18 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.356 ! brouard 4: Revision 1.355 2023/05/22 17:03:18 brouard
! 5: Summary: 0.99r46
! 6:
! 7: * imach.c (Module): In the ILK....txt file, the number of columns
! 8: before the covariates values is dependent of the number of states (16+nlstate): 0.99r46
! 9:
1.355 brouard 10: Revision 1.354 2023/05/21 05:05:17 brouard
11: Summary: Temporary change for imachprax
12:
1.354 brouard 13: Revision 1.353 2023/05/08 18:48:22 brouard
14: *** empty log message ***
15:
1.353 brouard 16: Revision 1.352 2023/04/29 10:46:21 brouard
17: *** empty log message ***
18:
1.352 brouard 19: Revision 1.351 2023/04/29 10:43:47 brouard
20: Summary: 099r45
21:
1.351 brouard 22: Revision 1.350 2023/04/24 11:38:06 brouard
23: *** empty log message ***
24:
1.350 brouard 25: Revision 1.349 2023/01/31 09:19:37 brouard
26: Summary: Improvements in models with age*Vn*Vm
27:
1.348 brouard 28: Revision 1.347 2022/09/18 14:36:44 brouard
29: Summary: version 0.99r42
30:
1.347 brouard 31: Revision 1.346 2022/09/16 13:52:36 brouard
32: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
33:
1.346 brouard 34: Revision 1.345 2022/09/16 13:40:11 brouard
35: Summary: Version 0.99r41
36:
37: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
38:
1.345 brouard 39: Revision 1.344 2022/09/14 19:33:30 brouard
40: Summary: version 0.99r40
41:
42: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
43:
1.344 brouard 44: Revision 1.343 2022/09/14 14:22:16 brouard
45: Summary: version 0.99r39
46:
47: * imach.c (Module): Version 0.99r39 with colored dummy covariates
48: (fixed or time varying), using new last columns of
49: ILK_parameter.txt file.
50:
1.343 brouard 51: Revision 1.342 2022/09/11 19:54:09 brouard
52: Summary: 0.99r38
53:
54: * imach.c (Module): Adding timevarying products of any kinds,
55: should work before shifting cotvar from ncovcol+nqv columns in
56: order to have a correspondance between the column of cotvar and
57: the id of column.
58: (Module): Some cleaning and adding covariates in ILK.txt
59:
1.342 brouard 60: Revision 1.341 2022/09/11 07:58:42 brouard
61: Summary: Version 0.99r38
62:
63: After adding change in cotvar.
64:
1.341 brouard 65: Revision 1.340 2022/09/11 07:53:11 brouard
66: Summary: Version imach 0.99r37
67:
68: * imach.c (Module): Adding timevarying products of any kinds,
69: should work before shifting cotvar from ncovcol+nqv columns in
70: order to have a correspondance between the column of cotvar and
71: the id of column.
72:
1.340 brouard 73: Revision 1.339 2022/09/09 17:55:22 brouard
74: Summary: version 0.99r37
75:
76: * imach.c (Module): Many improvements for fixing products of fixed
77: timevarying as well as fixed * fixed, and test with quantitative
78: covariate.
79:
1.339 brouard 80: Revision 1.338 2022/09/04 17:40:33 brouard
81: Summary: 0.99r36
82:
83: * imach.c (Module): Now the easy runs i.e. without result or
84: model=1+age only did not work. The defautl combination should be 1
85: and not 0 because everything hasn't been tranformed yet.
86:
1.338 brouard 87: Revision 1.337 2022/09/02 14:26:02 brouard
88: Summary: version 0.99r35
89:
90: * src/imach.c: Version 0.99r35 because it outputs same results with
91: 1+age+V1+V1*age for females and 1+age for females only
92: (education=1 noweight)
93:
1.337 brouard 94: Revision 1.336 2022/08/31 09:52:36 brouard
95: *** empty log message ***
96:
1.336 brouard 97: Revision 1.335 2022/08/31 08:23:16 brouard
98: Summary: improvements...
99:
1.335 brouard 100: Revision 1.334 2022/08/25 09:08:41 brouard
101: Summary: In progress for quantitative
102:
1.334 brouard 103: Revision 1.333 2022/08/21 09:10:30 brouard
104: * src/imach.c (Module): Version 0.99r33 A lot of changes in
105: reassigning covariates: my first idea was that people will always
106: use the first covariate V1 into the model but in fact they are
107: producing data with many covariates and can use an equation model
108: with some of the covariate; it means that in a model V2+V3 instead
109: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
110: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
111: the equation model is restricted to two variables only (V2, V3)
112: and the combination for V2 should be codtabm(k,1) instead of
113: (codtabm(k,2), and the code should be
114: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
115: made. All of these should be simplified once a day like we did in
116: hpxij() for example by using precov[nres] which is computed in
117: decoderesult for each nres of each resultline. Loop should be done
118: on the equation model globally by distinguishing only product with
119: age (which are changing with age) and no more on type of
120: covariates, single dummies, single covariates.
121:
1.333 brouard 122: Revision 1.332 2022/08/21 09:06:25 brouard
123: Summary: Version 0.99r33
124:
125: * src/imach.c (Module): Version 0.99r33 A lot of changes in
126: reassigning covariates: my first idea was that people will always
127: use the first covariate V1 into the model but in fact they are
128: producing data with many covariates and can use an equation model
129: with some of the covariate; it means that in a model V2+V3 instead
130: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
131: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
132: the equation model is restricted to two variables only (V2, V3)
133: and the combination for V2 should be codtabm(k,1) instead of
134: (codtabm(k,2), and the code should be
135: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
136: made. All of these should be simplified once a day like we did in
137: hpxij() for example by using precov[nres] which is computed in
138: decoderesult for each nres of each resultline. Loop should be done
139: on the equation model globally by distinguishing only product with
140: age (which are changing with age) and no more on type of
141: covariates, single dummies, single covariates.
142:
1.332 brouard 143: Revision 1.331 2022/08/07 05:40:09 brouard
144: *** empty log message ***
145:
1.331 brouard 146: Revision 1.330 2022/08/06 07:18:25 brouard
147: Summary: last 0.99r31
148:
149: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
150:
1.330 brouard 151: Revision 1.329 2022/08/03 17:29:54 brouard
152: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
153:
1.329 brouard 154: Revision 1.328 2022/07/27 17:40:48 brouard
155: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
156:
1.328 brouard 157: Revision 1.327 2022/07/27 14:47:35 brouard
158: Summary: Still a problem for one-step probabilities in case of quantitative variables
159:
1.327 brouard 160: Revision 1.326 2022/07/26 17:33:55 brouard
161: Summary: some test with nres=1
162:
1.326 brouard 163: Revision 1.325 2022/07/25 14:27:23 brouard
164: Summary: r30
165:
166: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
167: coredumped, revealed by Feiuno, thank you.
168:
1.325 brouard 169: Revision 1.324 2022/07/23 17:44:26 brouard
170: *** empty log message ***
171:
1.324 brouard 172: Revision 1.323 2022/07/22 12:30:08 brouard
173: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
174:
1.323 brouard 175: Revision 1.322 2022/07/22 12:27:48 brouard
176: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
177:
1.322 brouard 178: Revision 1.321 2022/07/22 12:04:24 brouard
179: Summary: r28
180:
181: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
182:
1.321 brouard 183: Revision 1.320 2022/06/02 05:10:11 brouard
184: *** empty log message ***
185:
1.320 brouard 186: Revision 1.319 2022/06/02 04:45:11 brouard
187: * imach.c (Module): Adding the Wald tests from the log to the main
188: htm for better display of the maximum likelihood estimators.
189:
1.319 brouard 190: Revision 1.318 2022/05/24 08:10:59 brouard
191: * imach.c (Module): Some attempts to find a bug of wrong estimates
192: of confidencce intervals with product in the equation modelC
193:
1.318 brouard 194: Revision 1.317 2022/05/15 15:06:23 brouard
195: * imach.c (Module): Some minor improvements
196:
1.317 brouard 197: Revision 1.316 2022/05/11 15:11:31 brouard
198: Summary: r27
199:
1.316 brouard 200: Revision 1.315 2022/05/11 15:06:32 brouard
201: *** empty log message ***
202:
1.315 brouard 203: Revision 1.314 2022/04/13 17:43:09 brouard
204: * imach.c (Module): Adding link to text data files
205:
1.314 brouard 206: Revision 1.313 2022/04/11 15:57:42 brouard
207: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
208:
1.313 brouard 209: Revision 1.312 2022/04/05 21:24:39 brouard
210: *** empty log message ***
211:
1.312 brouard 212: Revision 1.311 2022/04/05 21:03:51 brouard
213: Summary: Fixed quantitative covariates
214:
215: Fixed covariates (dummy or quantitative)
216: with missing values have never been allowed but are ERRORS and
217: program quits. Standard deviations of fixed covariates were
218: wrongly computed. Mean and standard deviations of time varying
219: covariates are still not computed.
220:
1.311 brouard 221: Revision 1.310 2022/03/17 08:45:53 brouard
222: Summary: 99r25
223:
224: Improving detection of errors: result lines should be compatible with
225: the model.
226:
1.310 brouard 227: Revision 1.309 2021/05/20 12:39:14 brouard
228: Summary: Version 0.99r24
229:
1.309 brouard 230: Revision 1.308 2021/03/31 13:11:57 brouard
231: Summary: Version 0.99r23
232:
233:
234: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
235:
1.308 brouard 236: Revision 1.307 2021/03/08 18:11:32 brouard
237: Summary: 0.99r22 fixed bug on result:
238:
1.307 brouard 239: Revision 1.306 2021/02/20 15:44:02 brouard
240: Summary: Version 0.99r21
241:
242: * imach.c (Module): Fix bug on quitting after result lines!
243: (Module): Version 0.99r21
244:
1.306 brouard 245: Revision 1.305 2021/02/20 15:28:30 brouard
246: * imach.c (Module): Fix bug on quitting after result lines!
247:
1.305 brouard 248: Revision 1.304 2021/02/12 11:34:20 brouard
249: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
250:
1.304 brouard 251: Revision 1.303 2021/02/11 19:50:15 brouard
252: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
253:
1.303 brouard 254: Revision 1.302 2020/02/22 21:00:05 brouard
255: * (Module): imach.c Update mle=-3 (for computing Life expectancy
256: and life table from the data without any state)
257:
1.302 brouard 258: Revision 1.301 2019/06/04 13:51:20 brouard
259: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
260:
1.301 brouard 261: Revision 1.300 2019/05/22 19:09:45 brouard
262: Summary: version 0.99r19 of May 2019
263:
1.300 brouard 264: Revision 1.299 2019/05/22 18:37:08 brouard
265: Summary: Cleaned 0.99r19
266:
1.299 brouard 267: Revision 1.298 2019/05/22 18:19:56 brouard
268: *** empty log message ***
269:
1.298 brouard 270: Revision 1.297 2019/05/22 17:56:10 brouard
271: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
272:
1.297 brouard 273: Revision 1.296 2019/05/20 13:03:18 brouard
274: Summary: Projection syntax simplified
275:
276:
277: We can now start projections, forward or backward, from the mean date
278: of inteviews up to or down to a number of years of projection:
279: prevforecast=1 yearsfproj=15.3 mobil_average=0
280: or
281: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
282: or
283: prevbackcast=1 yearsbproj=12.3 mobil_average=1
284: or
285: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
286:
1.296 brouard 287: Revision 1.295 2019/05/18 09:52:50 brouard
288: Summary: doxygen tex bug
289:
1.295 brouard 290: Revision 1.294 2019/05/16 14:54:33 brouard
291: Summary: There was some wrong lines added
292:
1.294 brouard 293: Revision 1.293 2019/05/09 15:17:34 brouard
294: *** empty log message ***
295:
1.293 brouard 296: Revision 1.292 2019/05/09 14:17:20 brouard
297: Summary: Some updates
298:
1.292 brouard 299: Revision 1.291 2019/05/09 13:44:18 brouard
300: Summary: Before ncovmax
301:
1.291 brouard 302: Revision 1.290 2019/05/09 13:39:37 brouard
303: Summary: 0.99r18 unlimited number of individuals
304:
305: 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.
306:
1.290 brouard 307: Revision 1.289 2018/12/13 09:16:26 brouard
308: Summary: Bug for young ages (<-30) will be in r17
309:
1.289 brouard 310: Revision 1.288 2018/05/02 20:58:27 brouard
311: Summary: Some bugs fixed
312:
1.288 brouard 313: Revision 1.287 2018/05/01 17:57:25 brouard
314: Summary: Bug fixed by providing frequencies only for non missing covariates
315:
1.287 brouard 316: Revision 1.286 2018/04/27 14:27:04 brouard
317: Summary: some minor bugs
318:
1.286 brouard 319: Revision 1.285 2018/04/21 21:02:16 brouard
320: Summary: Some bugs fixed, valgrind tested
321:
1.285 brouard 322: Revision 1.284 2018/04/20 05:22:13 brouard
323: Summary: Computing mean and stdeviation of fixed quantitative variables
324:
1.284 brouard 325: Revision 1.283 2018/04/19 14:49:16 brouard
326: Summary: Some minor bugs fixed
327:
1.283 brouard 328: Revision 1.282 2018/02/27 22:50:02 brouard
329: *** empty log message ***
330:
1.282 brouard 331: Revision 1.281 2018/02/27 19:25:23 brouard
332: Summary: Adding second argument for quitting
333:
1.281 brouard 334: Revision 1.280 2018/02/21 07:58:13 brouard
335: Summary: 0.99r15
336:
337: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
338:
1.280 brouard 339: Revision 1.279 2017/07/20 13:35:01 brouard
340: Summary: temporary working
341:
1.279 brouard 342: Revision 1.278 2017/07/19 14:09:02 brouard
343: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
344:
1.278 brouard 345: Revision 1.277 2017/07/17 08:53:49 brouard
346: Summary: BOM files can be read now
347:
1.277 brouard 348: Revision 1.276 2017/06/30 15:48:31 brouard
349: Summary: Graphs improvements
350:
1.276 brouard 351: Revision 1.275 2017/06/30 13:39:33 brouard
352: Summary: Saito's color
353:
1.275 brouard 354: Revision 1.274 2017/06/29 09:47:08 brouard
355: Summary: Version 0.99r14
356:
1.274 brouard 357: Revision 1.273 2017/06/27 11:06:02 brouard
358: Summary: More documentation on projections
359:
1.273 brouard 360: Revision 1.272 2017/06/27 10:22:40 brouard
361: Summary: Color of backprojection changed from 6 to 5(yellow)
362:
1.272 brouard 363: Revision 1.271 2017/06/27 10:17:50 brouard
364: Summary: Some bug with rint
365:
1.271 brouard 366: Revision 1.270 2017/05/24 05:45:29 brouard
367: *** empty log message ***
368:
1.270 brouard 369: Revision 1.269 2017/05/23 08:39:25 brouard
370: Summary: Code into subroutine, cleanings
371:
1.269 brouard 372: Revision 1.268 2017/05/18 20:09:32 brouard
373: Summary: backprojection and confidence intervals of backprevalence
374:
1.268 brouard 375: Revision 1.267 2017/05/13 10:25:05 brouard
376: Summary: temporary save for backprojection
377:
1.267 brouard 378: Revision 1.266 2017/05/13 07:26:12 brouard
379: Summary: Version 0.99r13 (improvements and bugs fixed)
380:
1.266 brouard 381: Revision 1.265 2017/04/26 16:22:11 brouard
382: Summary: imach 0.99r13 Some bugs fixed
383:
1.265 brouard 384: Revision 1.264 2017/04/26 06:01:29 brouard
385: Summary: Labels in graphs
386:
1.264 brouard 387: Revision 1.263 2017/04/24 15:23:15 brouard
388: Summary: to save
389:
1.263 brouard 390: Revision 1.262 2017/04/18 16:48:12 brouard
391: *** empty log message ***
392:
1.262 brouard 393: Revision 1.261 2017/04/05 10:14:09 brouard
394: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
395:
1.261 brouard 396: Revision 1.260 2017/04/04 17:46:59 brouard
397: Summary: Gnuplot indexations fixed (humm)
398:
1.260 brouard 399: Revision 1.259 2017/04/04 13:01:16 brouard
400: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
401:
1.259 brouard 402: Revision 1.258 2017/04/03 10:17:47 brouard
403: Summary: Version 0.99r12
404:
405: Some cleanings, conformed with updated documentation.
406:
1.258 brouard 407: Revision 1.257 2017/03/29 16:53:30 brouard
408: Summary: Temp
409:
1.257 brouard 410: Revision 1.256 2017/03/27 05:50:23 brouard
411: Summary: Temporary
412:
1.256 brouard 413: Revision 1.255 2017/03/08 16:02:28 brouard
414: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
415:
1.255 brouard 416: Revision 1.254 2017/03/08 07:13:00 brouard
417: Summary: Fixing data parameter line
418:
1.254 brouard 419: Revision 1.253 2016/12/15 11:59:41 brouard
420: Summary: 0.99 in progress
421:
1.253 brouard 422: Revision 1.252 2016/09/15 21:15:37 brouard
423: *** empty log message ***
424:
1.252 brouard 425: Revision 1.251 2016/09/15 15:01:13 brouard
426: Summary: not working
427:
1.251 brouard 428: Revision 1.250 2016/09/08 16:07:27 brouard
429: Summary: continue
430:
1.250 brouard 431: Revision 1.249 2016/09/07 17:14:18 brouard
432: Summary: Starting values from frequencies
433:
1.249 brouard 434: Revision 1.248 2016/09/07 14:10:18 brouard
435: *** empty log message ***
436:
1.248 brouard 437: Revision 1.247 2016/09/02 11:11:21 brouard
438: *** empty log message ***
439:
1.247 brouard 440: Revision 1.246 2016/09/02 08:49:22 brouard
441: *** empty log message ***
442:
1.246 brouard 443: Revision 1.245 2016/09/02 07:25:01 brouard
444: *** empty log message ***
445:
1.245 brouard 446: Revision 1.244 2016/09/02 07:17:34 brouard
447: *** empty log message ***
448:
1.244 brouard 449: Revision 1.243 2016/09/02 06:45:35 brouard
450: *** empty log message ***
451:
1.243 brouard 452: Revision 1.242 2016/08/30 15:01:20 brouard
453: Summary: Fixing a lots
454:
1.242 brouard 455: Revision 1.241 2016/08/29 17:17:25 brouard
456: Summary: gnuplot problem in Back projection to fix
457:
1.241 brouard 458: Revision 1.240 2016/08/29 07:53:18 brouard
459: Summary: Better
460:
1.240 brouard 461: Revision 1.239 2016/08/26 15:51:03 brouard
462: Summary: Improvement in Powell output in order to copy and paste
463:
464: Author:
465:
1.239 brouard 466: Revision 1.238 2016/08/26 14:23:35 brouard
467: Summary: Starting tests of 0.99
468:
1.238 brouard 469: Revision 1.237 2016/08/26 09:20:19 brouard
470: Summary: to valgrind
471:
1.237 brouard 472: Revision 1.236 2016/08/25 10:50:18 brouard
473: *** empty log message ***
474:
1.236 brouard 475: Revision 1.235 2016/08/25 06:59:23 brouard
476: *** empty log message ***
477:
1.235 brouard 478: Revision 1.234 2016/08/23 16:51:20 brouard
479: *** empty log message ***
480:
1.234 brouard 481: Revision 1.233 2016/08/23 07:40:50 brouard
482: Summary: not working
483:
1.233 brouard 484: Revision 1.232 2016/08/22 14:20:21 brouard
485: Summary: not working
486:
1.232 brouard 487: Revision 1.231 2016/08/22 07:17:15 brouard
488: Summary: not working
489:
1.231 brouard 490: Revision 1.230 2016/08/22 06:55:53 brouard
491: Summary: Not working
492:
1.230 brouard 493: Revision 1.229 2016/07/23 09:45:53 brouard
494: Summary: Completing for func too
495:
1.229 brouard 496: Revision 1.228 2016/07/22 17:45:30 brouard
497: Summary: Fixing some arrays, still debugging
498:
1.227 brouard 499: Revision 1.226 2016/07/12 18:42:34 brouard
500: Summary: temp
501:
1.226 brouard 502: Revision 1.225 2016/07/12 08:40:03 brouard
503: Summary: saving but not running
504:
1.225 brouard 505: Revision 1.224 2016/07/01 13:16:01 brouard
506: Summary: Fixes
507:
1.224 brouard 508: Revision 1.223 2016/02/19 09:23:35 brouard
509: Summary: temporary
510:
1.223 brouard 511: Revision 1.222 2016/02/17 08:14:50 brouard
512: Summary: Probably last 0.98 stable version 0.98r6
513:
1.222 brouard 514: Revision 1.221 2016/02/15 23:35:36 brouard
515: Summary: minor bug
516:
1.220 brouard 517: Revision 1.219 2016/02/15 00:48:12 brouard
518: *** empty log message ***
519:
1.219 brouard 520: Revision 1.218 2016/02/12 11:29:23 brouard
521: Summary: 0.99 Back projections
522:
1.218 brouard 523: Revision 1.217 2015/12/23 17:18:31 brouard
524: Summary: Experimental backcast
525:
1.217 brouard 526: Revision 1.216 2015/12/18 17:32:11 brouard
527: Summary: 0.98r4 Warning and status=-2
528:
529: Version 0.98r4 is now:
530: - displaying an error when status is -1, date of interview unknown and date of death known;
531: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
532: Older changes concerning s=-2, dating from 2005 have been supersed.
533:
1.216 brouard 534: Revision 1.215 2015/12/16 08:52:24 brouard
535: Summary: 0.98r4 working
536:
1.215 brouard 537: Revision 1.214 2015/12/16 06:57:54 brouard
538: Summary: temporary not working
539:
1.214 brouard 540: Revision 1.213 2015/12/11 18:22:17 brouard
541: Summary: 0.98r4
542:
1.213 brouard 543: Revision 1.212 2015/11/21 12:47:24 brouard
544: Summary: minor typo
545:
1.212 brouard 546: Revision 1.211 2015/11/21 12:41:11 brouard
547: Summary: 0.98r3 with some graph of projected cross-sectional
548:
549: Author: Nicolas Brouard
550:
1.211 brouard 551: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 552: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 553: Summary: Adding ftolpl parameter
554: Author: N Brouard
555:
556: We had difficulties to get smoothed confidence intervals. It was due
557: to the period prevalence which wasn't computed accurately. The inner
558: parameter ftolpl is now an outer parameter of the .imach parameter
559: file after estepm. If ftolpl is small 1.e-4 and estepm too,
560: computation are long.
561:
1.209 brouard 562: Revision 1.208 2015/11/17 14:31:57 brouard
563: Summary: temporary
564:
1.208 brouard 565: Revision 1.207 2015/10/27 17:36:57 brouard
566: *** empty log message ***
567:
1.207 brouard 568: Revision 1.206 2015/10/24 07:14:11 brouard
569: *** empty log message ***
570:
1.206 brouard 571: Revision 1.205 2015/10/23 15:50:53 brouard
572: Summary: 0.98r3 some clarification for graphs on likelihood contributions
573:
1.205 brouard 574: Revision 1.204 2015/10/01 16:20:26 brouard
575: Summary: Some new graphs of contribution to likelihood
576:
1.204 brouard 577: Revision 1.203 2015/09/30 17:45:14 brouard
578: Summary: looking at better estimation of the hessian
579:
580: Also a better criteria for convergence to the period prevalence And
581: therefore adding the number of years needed to converge. (The
582: prevalence in any alive state shold sum to one
583:
1.203 brouard 584: Revision 1.202 2015/09/22 19:45:16 brouard
585: Summary: Adding some overall graph on contribution to likelihood. Might change
586:
1.202 brouard 587: Revision 1.201 2015/09/15 17:34:58 brouard
588: Summary: 0.98r0
589:
590: - Some new graphs like suvival functions
591: - Some bugs fixed like model=1+age+V2.
592:
1.201 brouard 593: Revision 1.200 2015/09/09 16:53:55 brouard
594: Summary: Big bug thanks to Flavia
595:
596: Even model=1+age+V2. did not work anymore
597:
1.200 brouard 598: Revision 1.199 2015/09/07 14:09:23 brouard
599: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
600:
1.199 brouard 601: Revision 1.198 2015/09/03 07:14:39 brouard
602: Summary: 0.98q5 Flavia
603:
1.198 brouard 604: Revision 1.197 2015/09/01 18:24:39 brouard
605: *** empty log message ***
606:
1.197 brouard 607: Revision 1.196 2015/08/18 23:17:52 brouard
608: Summary: 0.98q5
609:
1.196 brouard 610: Revision 1.195 2015/08/18 16:28:39 brouard
611: Summary: Adding a hack for testing purpose
612:
613: After reading the title, ftol and model lines, if the comment line has
614: a q, starting with #q, the answer at the end of the run is quit. It
615: permits to run test files in batch with ctest. The former workaround was
616: $ echo q | imach foo.imach
617:
1.195 brouard 618: Revision 1.194 2015/08/18 13:32:00 brouard
619: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
620:
1.194 brouard 621: Revision 1.193 2015/08/04 07:17:42 brouard
622: Summary: 0.98q4
623:
1.193 brouard 624: Revision 1.192 2015/07/16 16:49:02 brouard
625: Summary: Fixing some outputs
626:
1.192 brouard 627: Revision 1.191 2015/07/14 10:00:33 brouard
628: Summary: Some fixes
629:
1.191 brouard 630: Revision 1.190 2015/05/05 08:51:13 brouard
631: Summary: Adding digits in output parameters (7 digits instead of 6)
632:
633: Fix 1+age+.
634:
1.190 brouard 635: Revision 1.189 2015/04/30 14:45:16 brouard
636: Summary: 0.98q2
637:
1.189 brouard 638: Revision 1.188 2015/04/30 08:27:53 brouard
639: *** empty log message ***
640:
1.188 brouard 641: Revision 1.187 2015/04/29 09:11:15 brouard
642: *** empty log message ***
643:
1.187 brouard 644: Revision 1.186 2015/04/23 12:01:52 brouard
645: Summary: V1*age is working now, version 0.98q1
646:
647: Some codes had been disabled in order to simplify and Vn*age was
648: working in the optimization phase, ie, giving correct MLE parameters,
649: but, as usual, outputs were not correct and program core dumped.
650:
1.186 brouard 651: Revision 1.185 2015/03/11 13:26:42 brouard
652: Summary: Inclusion of compile and links command line for Intel Compiler
653:
1.185 brouard 654: Revision 1.184 2015/03/11 11:52:39 brouard
655: Summary: Back from Windows 8. Intel Compiler
656:
1.184 brouard 657: Revision 1.183 2015/03/10 20:34:32 brouard
658: Summary: 0.98q0, trying with directest, mnbrak fixed
659:
660: We use directest instead of original Powell test; probably no
661: incidence on the results, but better justifications;
662: We fixed Numerical Recipes mnbrak routine which was wrong and gave
663: wrong results.
664:
1.183 brouard 665: Revision 1.182 2015/02/12 08:19:57 brouard
666: Summary: Trying to keep directest which seems simpler and more general
667: Author: Nicolas Brouard
668:
1.182 brouard 669: Revision 1.181 2015/02/11 23:22:24 brouard
670: Summary: Comments on Powell added
671:
672: Author:
673:
1.181 brouard 674: Revision 1.180 2015/02/11 17:33:45 brouard
675: Summary: Finishing move from main to function (hpijx and prevalence_limit)
676:
1.180 brouard 677: Revision 1.179 2015/01/04 09:57:06 brouard
678: Summary: back to OS/X
679:
1.179 brouard 680: Revision 1.178 2015/01/04 09:35:48 brouard
681: *** empty log message ***
682:
1.178 brouard 683: Revision 1.177 2015/01/03 18:40:56 brouard
684: Summary: Still testing ilc32 on OSX
685:
1.177 brouard 686: Revision 1.176 2015/01/03 16:45:04 brouard
687: *** empty log message ***
688:
1.176 brouard 689: Revision 1.175 2015/01/03 16:33:42 brouard
690: *** empty log message ***
691:
1.175 brouard 692: Revision 1.174 2015/01/03 16:15:49 brouard
693: Summary: Still in cross-compilation
694:
1.174 brouard 695: Revision 1.173 2015/01/03 12:06:26 brouard
696: Summary: trying to detect cross-compilation
697:
1.173 brouard 698: Revision 1.172 2014/12/27 12:07:47 brouard
699: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
700:
1.172 brouard 701: Revision 1.171 2014/12/23 13:26:59 brouard
702: Summary: Back from Visual C
703:
704: Still problem with utsname.h on Windows
705:
1.171 brouard 706: Revision 1.170 2014/12/23 11:17:12 brouard
707: Summary: Cleaning some \%% back to %%
708:
709: The escape was mandatory for a specific compiler (which one?), but too many warnings.
710:
1.170 brouard 711: Revision 1.169 2014/12/22 23:08:31 brouard
712: Summary: 0.98p
713:
714: Outputs some informations on compiler used, OS etc. Testing on different platforms.
715:
1.169 brouard 716: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 717: Summary: update
1.169 brouard 718:
1.168 brouard 719: Revision 1.167 2014/12/22 13:50:56 brouard
720: Summary: Testing uname and compiler version and if compiled 32 or 64
721:
722: Testing on Linux 64
723:
1.167 brouard 724: Revision 1.166 2014/12/22 11:40:47 brouard
725: *** empty log message ***
726:
1.166 brouard 727: Revision 1.165 2014/12/16 11:20:36 brouard
728: Summary: After compiling on Visual C
729:
730: * imach.c (Module): Merging 1.61 to 1.162
731:
1.165 brouard 732: Revision 1.164 2014/12/16 10:52:11 brouard
733: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
734:
735: * imach.c (Module): Merging 1.61 to 1.162
736:
1.164 brouard 737: Revision 1.163 2014/12/16 10:30:11 brouard
738: * imach.c (Module): Merging 1.61 to 1.162
739:
1.163 brouard 740: Revision 1.162 2014/09/25 11:43:39 brouard
741: Summary: temporary backup 0.99!
742:
1.162 brouard 743: Revision 1.1 2014/09/16 11:06:58 brouard
744: Summary: With some code (wrong) for nlopt
745:
746: Author:
747:
748: Revision 1.161 2014/09/15 20:41:41 brouard
749: Summary: Problem with macro SQR on Intel compiler
750:
1.161 brouard 751: Revision 1.160 2014/09/02 09:24:05 brouard
752: *** empty log message ***
753:
1.160 brouard 754: Revision 1.159 2014/09/01 10:34:10 brouard
755: Summary: WIN32
756: Author: Brouard
757:
1.159 brouard 758: Revision 1.158 2014/08/27 17:11:51 brouard
759: *** empty log message ***
760:
1.158 brouard 761: Revision 1.157 2014/08/27 16:26:55 brouard
762: Summary: Preparing windows Visual studio version
763: Author: Brouard
764:
765: In order to compile on Visual studio, time.h is now correct and time_t
766: and tm struct should be used. difftime should be used but sometimes I
767: just make the differences in raw time format (time(&now).
768: Trying to suppress #ifdef LINUX
769: Add xdg-open for __linux in order to open default browser.
770:
1.157 brouard 771: Revision 1.156 2014/08/25 20:10:10 brouard
772: *** empty log message ***
773:
1.156 brouard 774: Revision 1.155 2014/08/25 18:32:34 brouard
775: Summary: New compile, minor changes
776: Author: Brouard
777:
1.155 brouard 778: Revision 1.154 2014/06/20 17:32:08 brouard
779: Summary: Outputs now all graphs of convergence to period prevalence
780:
1.154 brouard 781: Revision 1.153 2014/06/20 16:45:46 brouard
782: Summary: If 3 live state, convergence to period prevalence on same graph
783: Author: Brouard
784:
1.153 brouard 785: Revision 1.152 2014/06/18 17:54:09 brouard
786: Summary: open browser, use gnuplot on same dir than imach if not found in the path
787:
1.152 brouard 788: Revision 1.151 2014/06/18 16:43:30 brouard
789: *** empty log message ***
790:
1.151 brouard 791: Revision 1.150 2014/06/18 16:42:35 brouard
792: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
793: Author: brouard
794:
1.150 brouard 795: Revision 1.149 2014/06/18 15:51:14 brouard
796: Summary: Some fixes in parameter files errors
797: Author: Nicolas Brouard
798:
1.149 brouard 799: Revision 1.148 2014/06/17 17:38:48 brouard
800: Summary: Nothing new
801: Author: Brouard
802:
803: Just a new packaging for OS/X version 0.98nS
804:
1.148 brouard 805: Revision 1.147 2014/06/16 10:33:11 brouard
806: *** empty log message ***
807:
1.147 brouard 808: Revision 1.146 2014/06/16 10:20:28 brouard
809: Summary: Merge
810: Author: Brouard
811:
812: Merge, before building revised version.
813:
1.146 brouard 814: Revision 1.145 2014/06/10 21:23:15 brouard
815: Summary: Debugging with valgrind
816: Author: Nicolas Brouard
817:
818: Lot of changes in order to output the results with some covariates
819: After the Edimburgh REVES conference 2014, it seems mandatory to
820: improve the code.
821: No more memory valgrind error but a lot has to be done in order to
822: continue the work of splitting the code into subroutines.
823: Also, decodemodel has been improved. Tricode is still not
824: optimal. nbcode should be improved. Documentation has been added in
825: the source code.
826:
1.144 brouard 827: Revision 1.143 2014/01/26 09:45:38 brouard
828: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
829:
830: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
831: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
832:
1.143 brouard 833: Revision 1.142 2014/01/26 03:57:36 brouard
834: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
835:
836: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
837:
1.142 brouard 838: Revision 1.141 2014/01/26 02:42:01 brouard
839: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
840:
1.141 brouard 841: Revision 1.140 2011/09/02 10:37:54 brouard
842: Summary: times.h is ok with mingw32 now.
843:
1.140 brouard 844: Revision 1.139 2010/06/14 07:50:17 brouard
845: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
846: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
847:
1.139 brouard 848: Revision 1.138 2010/04/30 18:19:40 brouard
849: *** empty log message ***
850:
1.138 brouard 851: Revision 1.137 2010/04/29 18:11:38 brouard
852: (Module): Checking covariates for more complex models
853: than V1+V2. A lot of change to be done. Unstable.
854:
1.137 brouard 855: Revision 1.136 2010/04/26 20:30:53 brouard
856: (Module): merging some libgsl code. Fixing computation
857: of likelione (using inter/intrapolation if mle = 0) in order to
858: get same likelihood as if mle=1.
859: Some cleaning of code and comments added.
860:
1.136 brouard 861: Revision 1.135 2009/10/29 15:33:14 brouard
862: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
863:
1.135 brouard 864: Revision 1.134 2009/10/29 13:18:53 brouard
865: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
866:
1.134 brouard 867: Revision 1.133 2009/07/06 10:21:25 brouard
868: just nforces
869:
1.133 brouard 870: Revision 1.132 2009/07/06 08:22:05 brouard
871: Many tings
872:
1.132 brouard 873: Revision 1.131 2009/06/20 16:22:47 brouard
874: Some dimensions resccaled
875:
1.131 brouard 876: Revision 1.130 2009/05/26 06:44:34 brouard
877: (Module): Max Covariate is now set to 20 instead of 8. A
878: lot of cleaning with variables initialized to 0. Trying to make
879: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
880:
1.130 brouard 881: Revision 1.129 2007/08/31 13:49:27 lievre
882: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
883:
1.129 lievre 884: Revision 1.128 2006/06/30 13:02:05 brouard
885: (Module): Clarifications on computing e.j
886:
1.128 brouard 887: Revision 1.127 2006/04/28 18:11:50 brouard
888: (Module): Yes the sum of survivors was wrong since
889: imach-114 because nhstepm was no more computed in the age
890: loop. Now we define nhstepma in the age loop.
891: (Module): In order to speed up (in case of numerous covariates) we
892: compute health expectancies (without variances) in a first step
893: and then all the health expectancies with variances or standard
894: deviation (needs data from the Hessian matrices) which slows the
895: computation.
896: In the future we should be able to stop the program is only health
897: expectancies and graph are needed without standard deviations.
898:
1.127 brouard 899: Revision 1.126 2006/04/28 17:23:28 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: Version 0.98h
904:
1.126 brouard 905: Revision 1.125 2006/04/04 15:20:31 lievre
906: Errors in calculation of health expectancies. Age was not initialized.
907: Forecasting file added.
908:
909: Revision 1.124 2006/03/22 17:13:53 lievre
910: Parameters are printed with %lf instead of %f (more numbers after the comma).
911: The log-likelihood is printed in the log file
912:
913: Revision 1.123 2006/03/20 10:52:43 brouard
914: * imach.c (Module): <title> changed, corresponds to .htm file
915: name. <head> headers where missing.
916:
917: * imach.c (Module): Weights can have a decimal point as for
918: English (a comma might work with a correct LC_NUMERIC environment,
919: otherwise the weight is truncated).
920: Modification of warning when the covariates values are not 0 or
921: 1.
922: Version 0.98g
923:
924: Revision 1.122 2006/03/20 09:45:41 brouard
925: (Module): Weights can have a decimal point as for
926: English (a comma might work with a correct LC_NUMERIC environment,
927: otherwise the weight is truncated).
928: Modification of warning when the covariates values are not 0 or
929: 1.
930: Version 0.98g
931:
932: Revision 1.121 2006/03/16 17:45:01 lievre
933: * imach.c (Module): Comments concerning covariates added
934:
935: * imach.c (Module): refinements in the computation of lli if
936: status=-2 in order to have more reliable computation if stepm is
937: not 1 month. Version 0.98f
938:
939: Revision 1.120 2006/03/16 15:10:38 lievre
940: (Module): refinements in the computation of lli if
941: status=-2 in order to have more reliable computation if stepm is
942: not 1 month. Version 0.98f
943:
944: Revision 1.119 2006/03/15 17:42:26 brouard
945: (Module): Bug if status = -2, the loglikelihood was
946: computed as likelihood omitting the logarithm. Version O.98e
947:
948: Revision 1.118 2006/03/14 18:20:07 brouard
949: (Module): varevsij Comments added explaining the second
950: table of variances if popbased=1 .
951: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
952: (Module): Function pstamp added
953: (Module): Version 0.98d
954:
955: Revision 1.117 2006/03/14 17:16:22 brouard
956: (Module): varevsij Comments added explaining the second
957: table of variances if popbased=1 .
958: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
959: (Module): Function pstamp added
960: (Module): Version 0.98d
961:
962: Revision 1.116 2006/03/06 10:29:27 brouard
963: (Module): Variance-covariance wrong links and
964: varian-covariance of ej. is needed (Saito).
965:
966: Revision 1.115 2006/02/27 12:17:45 brouard
967: (Module): One freematrix added in mlikeli! 0.98c
968:
969: Revision 1.114 2006/02/26 12:57:58 brouard
970: (Module): Some improvements in processing parameter
971: filename with strsep.
972:
973: Revision 1.113 2006/02/24 14:20:24 brouard
974: (Module): Memory leaks checks with valgrind and:
975: datafile was not closed, some imatrix were not freed and on matrix
976: allocation too.
977:
978: Revision 1.112 2006/01/30 09:55:26 brouard
979: (Module): Back to gnuplot.exe instead of wgnuplot.exe
980:
981: Revision 1.111 2006/01/25 20:38:18 brouard
982: (Module): Lots of cleaning and bugs added (Gompertz)
983: (Module): Comments can be added in data file. Missing date values
984: can be a simple dot '.'.
985:
986: Revision 1.110 2006/01/25 00:51:50 brouard
987: (Module): Lots of cleaning and bugs added (Gompertz)
988:
989: Revision 1.109 2006/01/24 19:37:15 brouard
990: (Module): Comments (lines starting with a #) are allowed in data.
991:
992: Revision 1.108 2006/01/19 18:05:42 lievre
993: Gnuplot problem appeared...
994: To be fixed
995:
996: Revision 1.107 2006/01/19 16:20:37 brouard
997: Test existence of gnuplot in imach path
998:
999: Revision 1.106 2006/01/19 13:24:36 brouard
1000: Some cleaning and links added in html output
1001:
1002: Revision 1.105 2006/01/05 20:23:19 lievre
1003: *** empty log message ***
1004:
1005: Revision 1.104 2005/09/30 16:11:43 lievre
1006: (Module): sump fixed, loop imx fixed, and simplifications.
1007: (Module): If the status is missing at the last wave but we know
1008: that the person is alive, then we can code his/her status as -2
1009: (instead of missing=-1 in earlier versions) and his/her
1010: contributions to the likelihood is 1 - Prob of dying from last
1011: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1012: the healthy state at last known wave). Version is 0.98
1013:
1014: Revision 1.103 2005/09/30 15:54:49 lievre
1015: (Module): sump fixed, loop imx fixed, and simplifications.
1016:
1017: Revision 1.102 2004/09/15 17:31:30 brouard
1018: Add the possibility to read data file including tab characters.
1019:
1020: Revision 1.101 2004/09/15 10:38:38 brouard
1021: Fix on curr_time
1022:
1023: Revision 1.100 2004/07/12 18:29:06 brouard
1024: Add version for Mac OS X. Just define UNIX in Makefile
1025:
1026: Revision 1.99 2004/06/05 08:57:40 brouard
1027: *** empty log message ***
1028:
1029: Revision 1.98 2004/05/16 15:05:56 brouard
1030: New version 0.97 . First attempt to estimate force of mortality
1031: directly from the data i.e. without the need of knowing the health
1032: state at each age, but using a Gompertz model: log u =a + b*age .
1033: This is the basic analysis of mortality and should be done before any
1034: other analysis, in order to test if the mortality estimated from the
1035: cross-longitudinal survey is different from the mortality estimated
1036: from other sources like vital statistic data.
1037:
1038: The same imach parameter file can be used but the option for mle should be -3.
1039:
1.324 brouard 1040: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1041: former routines in order to include the new code within the former code.
1042:
1043: The output is very simple: only an estimate of the intercept and of
1044: the slope with 95% confident intervals.
1045:
1046: Current limitations:
1047: A) Even if you enter covariates, i.e. with the
1048: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1049: B) There is no computation of Life Expectancy nor Life Table.
1050:
1051: Revision 1.97 2004/02/20 13:25:42 lievre
1052: Version 0.96d. Population forecasting command line is (temporarily)
1053: suppressed.
1054:
1055: Revision 1.96 2003/07/15 15:38:55 brouard
1056: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1057: rewritten within the same printf. Workaround: many printfs.
1058:
1059: Revision 1.95 2003/07/08 07:54:34 brouard
1060: * imach.c (Repository):
1061: (Repository): Using imachwizard code to output a more meaningful covariance
1062: matrix (cov(a12,c31) instead of numbers.
1063:
1064: Revision 1.94 2003/06/27 13:00:02 brouard
1065: Just cleaning
1066:
1067: Revision 1.93 2003/06/25 16:33:55 brouard
1068: (Module): On windows (cygwin) function asctime_r doesn't
1069: exist so I changed back to asctime which exists.
1070: (Module): Version 0.96b
1071:
1072: Revision 1.92 2003/06/25 16:30:45 brouard
1073: (Module): On windows (cygwin) function asctime_r doesn't
1074: exist so I changed back to asctime which exists.
1075:
1076: Revision 1.91 2003/06/25 15:30:29 brouard
1077: * imach.c (Repository): Duplicated warning errors corrected.
1078: (Repository): Elapsed time after each iteration is now output. It
1079: helps to forecast when convergence will be reached. Elapsed time
1080: is stamped in powell. We created a new html file for the graphs
1081: concerning matrix of covariance. It has extension -cov.htm.
1082:
1083: Revision 1.90 2003/06/24 12:34:15 brouard
1084: (Module): Some bugs corrected for windows. Also, when
1085: mle=-1 a template is output in file "or"mypar.txt with the design
1086: of the covariance matrix to be input.
1087:
1088: Revision 1.89 2003/06/24 12:30:52 brouard
1089: (Module): Some bugs corrected for windows. Also, when
1090: mle=-1 a template is output in file "or"mypar.txt with the design
1091: of the covariance matrix to be input.
1092:
1093: Revision 1.88 2003/06/23 17:54:56 brouard
1094: * 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.
1095:
1096: Revision 1.87 2003/06/18 12:26:01 brouard
1097: Version 0.96
1098:
1099: Revision 1.86 2003/06/17 20:04:08 brouard
1100: (Module): Change position of html and gnuplot routines and added
1101: routine fileappend.
1102:
1103: Revision 1.85 2003/06/17 13:12:43 brouard
1104: * imach.c (Repository): Check when date of death was earlier that
1105: current date of interview. It may happen when the death was just
1106: prior to the death. In this case, dh was negative and likelihood
1107: was wrong (infinity). We still send an "Error" but patch by
1108: assuming that the date of death was just one stepm after the
1109: interview.
1110: (Repository): Because some people have very long ID (first column)
1111: we changed int to long in num[] and we added a new lvector for
1112: memory allocation. But we also truncated to 8 characters (left
1113: truncation)
1114: (Repository): No more line truncation errors.
1115:
1116: Revision 1.84 2003/06/13 21:44:43 brouard
1117: * imach.c (Repository): Replace "freqsummary" at a correct
1118: place. It differs from routine "prevalence" which may be called
1119: many times. Probs is memory consuming and must be used with
1120: parcimony.
1121: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1122:
1123: Revision 1.83 2003/06/10 13:39:11 lievre
1124: *** empty log message ***
1125:
1126: Revision 1.82 2003/06/05 15:57:20 brouard
1127: Add log in imach.c and fullversion number is now printed.
1128:
1129: */
1130: /*
1131: Interpolated Markov Chain
1132:
1133: Short summary of the programme:
1134:
1.227 brouard 1135: This program computes Healthy Life Expectancies or State-specific
1136: (if states aren't health statuses) Expectancies from
1137: cross-longitudinal data. Cross-longitudinal data consist in:
1138:
1139: -1- a first survey ("cross") where individuals from different ages
1140: are interviewed on their health status or degree of disability (in
1141: the case of a health survey which is our main interest)
1142:
1143: -2- at least a second wave of interviews ("longitudinal") which
1144: measure each change (if any) in individual health status. Health
1145: expectancies are computed from the time spent in each health state
1146: according to a model. More health states you consider, more time is
1147: necessary to reach the Maximum Likelihood of the parameters involved
1148: in the model. The simplest model is the multinomial logistic model
1149: where pij is the probability to be observed in state j at the second
1150: wave conditional to be observed in state i at the first
1151: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1152: etc , where 'age' is age and 'sex' is a covariate. If you want to
1153: have a more complex model than "constant and age", you should modify
1154: the program where the markup *Covariates have to be included here
1155: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1156: convergence.
1157:
1158: The advantage of this computer programme, compared to a simple
1159: multinomial logistic model, is clear when the delay between waves is not
1160: identical for each individual. Also, if a individual missed an
1161: intermediate interview, the information is lost, but taken into
1162: account using an interpolation or extrapolation.
1163:
1164: hPijx is the probability to be observed in state i at age x+h
1165: conditional to the observed state i at age x. The delay 'h' can be
1166: split into an exact number (nh*stepm) of unobserved intermediate
1167: states. This elementary transition (by month, quarter,
1168: semester or year) is modelled as a multinomial logistic. The hPx
1169: matrix is simply the matrix product of nh*stepm elementary matrices
1170: and the contribution of each individual to the likelihood is simply
1171: hPijx.
1172:
1173: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1174: of the life expectancies. It also computes the period (stable) prevalence.
1175:
1176: Back prevalence and projections:
1.227 brouard 1177:
1178: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1179: double agemaxpar, double ftolpl, int *ncvyearp, double
1180: dateprev1,double dateprev2, int firstpass, int lastpass, int
1181: mobilavproj)
1182:
1183: Computes the back prevalence limit for any combination of
1184: covariate values k at any age between ageminpar and agemaxpar and
1185: returns it in **bprlim. In the loops,
1186:
1187: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1188: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1189:
1190: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1191: Computes for any combination of covariates k and any age between bage and fage
1192: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1193: oldm=oldms;savm=savms;
1.227 brouard 1194:
1.267 brouard 1195: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1196: Computes the transition matrix starting at age 'age' over
1197: 'nhstepm*hstepm*stepm' months (i.e. until
1198: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1199: nhstepm*hstepm matrices.
1200:
1201: Returns p3mat[i][j][h] after calling
1202: p3mat[i][j][h]=matprod2(newm,
1203: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1204: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1205: oldm);
1.226 brouard 1206:
1207: Important routines
1208:
1209: - func (or funcone), computes logit (pij) distinguishing
1210: o fixed variables (single or product dummies or quantitative);
1211: o varying variables by:
1212: (1) wave (single, product dummies, quantitative),
1213: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1214: % fixed dummy (treated) or quantitative (not done because time-consuming);
1215: % varying dummy (not done) or quantitative (not done);
1216: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1217: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1218: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1219: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1220: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1221:
1.226 brouard 1222:
1223:
1.324 brouard 1224: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1225: Institut national d'études démographiques, Paris.
1.126 brouard 1226: This software have been partly granted by Euro-REVES, a concerted action
1227: from the European Union.
1228: It is copyrighted identically to a GNU software product, ie programme and
1229: software can be distributed freely for non commercial use. Latest version
1230: can be accessed at http://euroreves.ined.fr/imach .
1231:
1232: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1233: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1234:
1235: **********************************************************************/
1236: /*
1237: main
1238: read parameterfile
1239: read datafile
1240: concatwav
1241: freqsummary
1242: if (mle >= 1)
1243: mlikeli
1244: print results files
1245: if mle==1
1246: computes hessian
1247: read end of parameter file: agemin, agemax, bage, fage, estepm
1248: begin-prev-date,...
1249: open gnuplot file
1250: open html file
1.145 brouard 1251: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1252: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1253: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1254: freexexit2 possible for memory heap.
1255:
1256: h Pij x | pij_nom ficrestpij
1257: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1258: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1259: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1260:
1261: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1262: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1263: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1264: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1265: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1266:
1.126 brouard 1267: forecasting if prevfcast==1 prevforecast call prevalence()
1268: health expectancies
1269: Variance-covariance of DFLE
1270: prevalence()
1271: movingaverage()
1272: varevsij()
1273: if popbased==1 varevsij(,popbased)
1274: total life expectancies
1275: Variance of period (stable) prevalence
1276: end
1277: */
1278:
1.187 brouard 1279: /* #define DEBUG */
1280: /* #define DEBUGBRENT */
1.203 brouard 1281: /* #define DEBUGLINMIN */
1282: /* #define DEBUGHESS */
1283: #define DEBUGHESSIJ
1.224 brouard 1284: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1285: #define POWELL /* Instead of NLOPT */
1.224 brouard 1286: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1287: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1288: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1289: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1290:
1291: #include <math.h>
1292: #include <stdio.h>
1293: #include <stdlib.h>
1294: #include <string.h>
1.226 brouard 1295: #include <ctype.h>
1.159 brouard 1296:
1297: #ifdef _WIN32
1298: #include <io.h>
1.172 brouard 1299: #include <windows.h>
1300: #include <tchar.h>
1.159 brouard 1301: #else
1.126 brouard 1302: #include <unistd.h>
1.159 brouard 1303: #endif
1.126 brouard 1304:
1305: #include <limits.h>
1306: #include <sys/types.h>
1.171 brouard 1307:
1308: #if defined(__GNUC__)
1309: #include <sys/utsname.h> /* Doesn't work on Windows */
1310: #endif
1311:
1.126 brouard 1312: #include <sys/stat.h>
1313: #include <errno.h>
1.159 brouard 1314: /* extern int errno; */
1.126 brouard 1315:
1.157 brouard 1316: /* #ifdef LINUX */
1317: /* #include <time.h> */
1318: /* #include "timeval.h" */
1319: /* #else */
1320: /* #include <sys/time.h> */
1321: /* #endif */
1322:
1.126 brouard 1323: #include <time.h>
1324:
1.136 brouard 1325: #ifdef GSL
1326: #include <gsl/gsl_errno.h>
1327: #include <gsl/gsl_multimin.h>
1328: #endif
1329:
1.167 brouard 1330:
1.162 brouard 1331: #ifdef NLOPT
1332: #include <nlopt.h>
1333: typedef struct {
1334: double (* function)(double [] );
1335: } myfunc_data ;
1336: #endif
1337:
1.126 brouard 1338: /* #include <libintl.h> */
1339: /* #define _(String) gettext (String) */
1340:
1.349 brouard 1341: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1342:
1343: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1344: #define GNUPLOTVERSION 5.1
1345: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1346: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1347: #define FILENAMELENGTH 256
1.126 brouard 1348:
1349: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1350: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1351:
1.349 brouard 1352: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1353: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1354:
1355: #define NINTERVMAX 8
1.144 brouard 1356: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1357: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1358: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1359: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1360: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1361: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1362: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1363: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1364: /* #define AGESUP 130 */
1.288 brouard 1365: /* #define AGESUP 150 */
1366: #define AGESUP 200
1.268 brouard 1367: #define AGEINF 0
1.218 brouard 1368: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1369: #define AGEBASE 40
1.194 brouard 1370: #define AGEOVERFLOW 1.e20
1.164 brouard 1371: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1372: #ifdef _WIN32
1373: #define DIRSEPARATOR '\\'
1374: #define CHARSEPARATOR "\\"
1375: #define ODIRSEPARATOR '/'
1376: #else
1.126 brouard 1377: #define DIRSEPARATOR '/'
1378: #define CHARSEPARATOR "/"
1379: #define ODIRSEPARATOR '\\'
1380: #endif
1381:
1.356 ! brouard 1382: /* $Id: imach.c,v 1.355 2023/05/22 17:03:18 brouard Exp $ */
1.126 brouard 1383: /* $State: Exp $ */
1.196 brouard 1384: #include "version.h"
1385: char version[]=__IMACH_VERSION__;
1.352 brouard 1386: char copyright[]="April 2023,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 2000-2022";
1.356 ! brouard 1387: char fullversion[]="$Revision: 1.355 $ $Date: 2023/05/22 17:03:18 $";
1.126 brouard 1388: char strstart[80];
1389: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1390: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1391: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1392: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1393: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1394: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1395: 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 1396: 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 1397: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1398: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1399: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1400: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1401: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1402: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1403: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1404: 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 1405: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1406: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1407: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1408: 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 */
1409: 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 */
1410: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1411: 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 1412: int nsd=0; /**< Total number of single dummy variables (output) */
1413: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1414: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1415: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1416: int ntveff=0; /**< ntveff number of effective time varying variables */
1417: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1418: int cptcov=0; /* Working variable */
1.334 brouard 1419: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1420: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1421: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1422: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1423: int nlstate=2; /* Number of live states */
1424: int ndeath=1; /* Number of dead states */
1.130 brouard 1425: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1426: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1427: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1428: int popbased=0;
1429:
1430: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1431: int maxwav=0; /* Maxim number of waves */
1432: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1433: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1434: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1435: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1436: int mle=1, weightopt=0;
1.126 brouard 1437: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1438: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1439: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1440: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1441: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1442: int selected(int kvar); /* Is covariate kvar selected for printing results */
1443:
1.130 brouard 1444: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1445: double **matprod2(); /* test */
1.126 brouard 1446: double **oldm, **newm, **savm; /* Working pointers to matrices */
1447: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1448: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1449:
1.136 brouard 1450: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1451: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1452: FILE *ficlog, *ficrespow;
1.130 brouard 1453: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1454: double fretone; /* Only one call to likelihood */
1.130 brouard 1455: long ipmx=0; /* Number of contributions */
1.126 brouard 1456: double sw; /* Sum of weights */
1457: char filerespow[FILENAMELENGTH];
1458: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1459: FILE *ficresilk;
1460: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1461: FILE *ficresprobmorprev;
1462: FILE *fichtm, *fichtmcov; /* Html File */
1463: FILE *ficreseij;
1464: char filerese[FILENAMELENGTH];
1465: FILE *ficresstdeij;
1466: char fileresstde[FILENAMELENGTH];
1467: FILE *ficrescveij;
1468: char filerescve[FILENAMELENGTH];
1469: FILE *ficresvij;
1470: char fileresv[FILENAMELENGTH];
1.269 brouard 1471:
1.126 brouard 1472: char title[MAXLINE];
1.234 brouard 1473: char model[MAXLINE]; /**< The model line */
1.217 brouard 1474: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1475: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1476: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1477: char command[FILENAMELENGTH];
1478: int outcmd=0;
1479:
1.217 brouard 1480: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1481: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1482: char filelog[FILENAMELENGTH]; /* Log file */
1483: char filerest[FILENAMELENGTH];
1484: char fileregp[FILENAMELENGTH];
1485: char popfile[FILENAMELENGTH];
1486:
1487: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1488:
1.157 brouard 1489: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1490: /* struct timezone tzp; */
1491: /* extern int gettimeofday(); */
1492: struct tm tml, *gmtime(), *localtime();
1493:
1494: extern time_t time();
1495:
1496: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1497: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1498: time_t rlast_btime; /* raw time */
1.157 brouard 1499: struct tm tm;
1500:
1.126 brouard 1501: char strcurr[80], strfor[80];
1502:
1503: char *endptr;
1504: long lval;
1505: double dval;
1506:
1507: #define NR_END 1
1508: #define FREE_ARG char*
1509: #define FTOL 1.0e-10
1510:
1511: #define NRANSI
1.240 brouard 1512: #define ITMAX 200
1513: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1514:
1515: #define TOL 2.0e-4
1516:
1517: #define CGOLD 0.3819660
1518: #define ZEPS 1.0e-10
1519: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1520:
1521: #define GOLD 1.618034
1522: #define GLIMIT 100.0
1523: #define TINY 1.0e-20
1524:
1525: static double maxarg1,maxarg2;
1526: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1527: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1528:
1529: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1530: #define rint(a) floor(a+0.5)
1.166 brouard 1531: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1532: #define mytinydouble 1.0e-16
1.166 brouard 1533: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1534: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1535: /* static double dsqrarg; */
1536: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1537: static double sqrarg;
1538: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1539: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1540: int agegomp= AGEGOMP;
1541:
1542: int imx;
1543: int stepm=1;
1544: /* Stepm, step in month: minimum step interpolation*/
1545:
1546: int estepm;
1547: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1548:
1549: int m,nb;
1550: long *num;
1.197 brouard 1551: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1552: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1553: covariate for which somebody answered excluding
1554: undefined. Usually 2: 0 and 1. */
1555: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1556: covariate for which somebody answered including
1557: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1558: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1559: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1560: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1561: 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 1562: double *ageexmed,*agecens;
1563: double dateintmean=0;
1.296 brouard 1564: double anprojd, mprojd, jprojd; /* For eventual projections */
1565: double anprojf, mprojf, jprojf;
1.126 brouard 1566:
1.296 brouard 1567: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1568: double anbackf, mbackf, jbackf;
1569: double jintmean,mintmean,aintmean;
1.126 brouard 1570: double *weight;
1571: int **s; /* Status */
1.141 brouard 1572: double *agedc;
1.145 brouard 1573: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1574: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1575: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1576: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1577: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1578: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1579: double idx;
1580: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1581: /* Some documentation */
1582: /* Design original data
1583: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1584: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1585: * ntv=3 nqtv=1
1.330 brouard 1586: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1587: * For time varying covariate, quanti or dummies
1588: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1589: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1590: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1591: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1592: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1593: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1594: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1595: * k= 1 2 3 4 5 6 7 8 9 10 11
1596: */
1597: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1598: /* 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
1599: # States 1=Coresidence, 2 Living alone, 3 Institution
1600: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1601: */
1.349 brouard 1602: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1603: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1604: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1605: /* fixed or varying), 1 for age product, 2 for*/
1606: /* product without age, 3 for age and double product */
1607: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1608: /*(single or product without age), 2 dummy*/
1609: /* with age product, 3 quant with age product*/
1610: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1611: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1612: /*TnsdVar[Tvar] 1 2 3 */
1613: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1614: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1615: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1616: /* nsq 1 2 */ /* Counting single quantit tv */
1617: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1618: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1619: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1620: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1621: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1622: /* 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"*/
1623: /* 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 1624: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>} */
1.350 brouard 1625: /* 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}*/
1626: /* 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 1627: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1628: /* 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 1629: /* 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 1630: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1631: /* Type */
1632: /* V 1 2 3 4 5 */
1633: /* F F V V V */
1634: /* D Q D D Q */
1635: /* */
1636: int *TvarsD;
1.330 brouard 1637: int *TnsdVar;
1.234 brouard 1638: int *TvarsDind;
1639: int *TvarsQ;
1640: int *TvarsQind;
1641:
1.318 brouard 1642: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1643: int nresult=0;
1.258 brouard 1644: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1645: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1646: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1647: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1648: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1649: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1650: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1651: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1652: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1653: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1654: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1655:
1656: /* 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
1657: # States 1=Coresidence, 2 Living alone, 3 Institution
1658: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1659: */
1.234 brouard 1660: /* 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 1661: 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 */
1662: 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 */
1663: 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 */
1664: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1665: 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 */
1666: 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 1667: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1668: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1669: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1670: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1671: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1672: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1673: 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 */
1674: 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 1675: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1676: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1677: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1678: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1679: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1680: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1681: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1682: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1683: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1684: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1685: /* 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 1686: int *Tvarsel; /**< Selected covariates for output */
1687: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1688: 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 1689: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1690: 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 1691: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1692: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1693: int *Tage;
1.227 brouard 1694: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1695: 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 1696: 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*/
1697: 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 1698: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1699: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1700: int **Tvard;
1.330 brouard 1701: int **Tvardk;
1.227 brouard 1702: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1703: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1704: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1705: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1706: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1707: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1708: double *lsurv, *lpop, *tpop;
1709:
1.231 brouard 1710: #define FD 1; /* Fixed dummy covariate */
1711: #define FQ 2; /* Fixed quantitative covariate */
1712: #define FP 3; /* Fixed product covariate */
1713: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1714: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1715: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1716: #define VD 10; /* Varying dummy covariate */
1717: #define VQ 11; /* Varying quantitative covariate */
1718: #define VP 12; /* Varying product covariate */
1719: #define VPDD 13; /* Varying product dummy*dummy covariate */
1720: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1721: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1722: #define APFD 16; /* Age product * fixed dummy covariate */
1723: #define APFQ 17; /* Age product * fixed quantitative covariate */
1724: #define APVD 18; /* Age product * varying dummy covariate */
1725: #define APVQ 19; /* Age product * varying quantitative covariate */
1726:
1727: #define FTYPE 1; /* Fixed covariate */
1728: #define VTYPE 2; /* Varying covariate (loop in wave) */
1729: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1730:
1731: struct kmodel{
1732: int maintype; /* main type */
1733: int subtype; /* subtype */
1734: };
1735: struct kmodel modell[NCOVMAX];
1736:
1.143 brouard 1737: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1738: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1739:
1740: /**************** split *************************/
1741: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1742: {
1743: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1744: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1745: */
1746: char *ss; /* pointer */
1.186 brouard 1747: int l1=0, l2=0; /* length counters */
1.126 brouard 1748:
1749: l1 = strlen(path ); /* length of path */
1750: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1751: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1752: if ( ss == NULL ) { /* no directory, so determine current directory */
1753: strcpy( name, path ); /* we got the fullname name because no directory */
1754: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1755: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1756: /* get current working directory */
1757: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1758: #ifdef WIN32
1759: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1760: #else
1761: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1762: #endif
1.126 brouard 1763: return( GLOCK_ERROR_GETCWD );
1764: }
1765: /* got dirc from getcwd*/
1766: printf(" DIRC = %s \n",dirc);
1.205 brouard 1767: } else { /* strip directory from path */
1.126 brouard 1768: ss++; /* after this, the filename */
1769: l2 = strlen( ss ); /* length of filename */
1770: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1771: strcpy( name, ss ); /* save file name */
1772: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1773: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1774: printf(" DIRC2 = %s \n",dirc);
1775: }
1776: /* We add a separator at the end of dirc if not exists */
1777: l1 = strlen( dirc ); /* length of directory */
1778: if( dirc[l1-1] != DIRSEPARATOR ){
1779: dirc[l1] = DIRSEPARATOR;
1780: dirc[l1+1] = 0;
1781: printf(" DIRC3 = %s \n",dirc);
1782: }
1783: ss = strrchr( name, '.' ); /* find last / */
1784: if (ss >0){
1785: ss++;
1786: strcpy(ext,ss); /* save extension */
1787: l1= strlen( name);
1788: l2= strlen(ss)+1;
1789: strncpy( finame, name, l1-l2);
1790: finame[l1-l2]= 0;
1791: }
1792:
1793: return( 0 ); /* we're done */
1794: }
1795:
1796:
1797: /******************************************/
1798:
1799: void replace_back_to_slash(char *s, char*t)
1800: {
1801: int i;
1802: int lg=0;
1803: i=0;
1804: lg=strlen(t);
1805: for(i=0; i<= lg; i++) {
1806: (s[i] = t[i]);
1807: if (t[i]== '\\') s[i]='/';
1808: }
1809: }
1810:
1.132 brouard 1811: char *trimbb(char *out, char *in)
1.137 brouard 1812: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1813: char *s;
1814: s=out;
1815: while (*in != '\0'){
1.137 brouard 1816: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1817: in++;
1818: }
1819: *out++ = *in++;
1820: }
1821: *out='\0';
1822: return s;
1823: }
1824:
1.351 brouard 1825: char *trimbtab(char *out, char *in)
1826: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1827: char *s;
1828: s=out;
1829: while (*in != '\0'){
1830: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1831: in++;
1832: }
1833: *out++ = *in++;
1834: }
1835: *out='\0';
1836: return s;
1837: }
1838:
1.187 brouard 1839: /* char *substrchaine(char *out, char *in, char *chain) */
1840: /* { */
1841: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1842: /* char *s, *t; */
1843: /* t=in;s=out; */
1844: /* while ((*in != *chain) && (*in != '\0')){ */
1845: /* *out++ = *in++; */
1846: /* } */
1847:
1848: /* /\* *in matches *chain *\/ */
1849: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1850: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1851: /* } */
1852: /* in--; chain--; */
1853: /* while ( (*in != '\0')){ */
1854: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1855: /* *out++ = *in++; */
1856: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1857: /* } */
1858: /* *out='\0'; */
1859: /* out=s; */
1860: /* return out; */
1861: /* } */
1862: char *substrchaine(char *out, char *in, char *chain)
1863: {
1864: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1865: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1866:
1867: char *strloc;
1868:
1.349 brouard 1869: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1870: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1871: 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 1872: if(strloc != NULL){
1.349 brouard 1873: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1874: 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)*/
1875: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1876: }
1.349 brouard 1877: 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 1878: return out;
1879: }
1880:
1881:
1.145 brouard 1882: char *cutl(char *blocc, char *alocc, char *in, char occ)
1883: {
1.187 brouard 1884: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1885: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1886: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1887: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1888: */
1.160 brouard 1889: char *s, *t;
1.145 brouard 1890: t=in;s=in;
1891: while ((*in != occ) && (*in != '\0')){
1892: *alocc++ = *in++;
1893: }
1894: if( *in == occ){
1895: *(alocc)='\0';
1896: s=++in;
1897: }
1898:
1899: if (s == t) {/* occ not found */
1900: *(alocc-(in-s))='\0';
1901: in=s;
1902: }
1903: while ( *in != '\0'){
1904: *blocc++ = *in++;
1905: }
1906:
1907: *blocc='\0';
1908: return t;
1909: }
1.137 brouard 1910: char *cutv(char *blocc, char *alocc, char *in, char occ)
1911: {
1.187 brouard 1912: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1913: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1914: gives blocc="abcdef2ghi" and alocc="j".
1915: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1916: */
1917: char *s, *t;
1918: t=in;s=in;
1919: while (*in != '\0'){
1920: while( *in == occ){
1921: *blocc++ = *in++;
1922: s=in;
1923: }
1924: *blocc++ = *in++;
1925: }
1926: if (s == t) /* occ not found */
1927: *(blocc-(in-s))='\0';
1928: else
1929: *(blocc-(in-s)-1)='\0';
1930: in=s;
1931: while ( *in != '\0'){
1932: *alocc++ = *in++;
1933: }
1934:
1935: *alocc='\0';
1936: return s;
1937: }
1938:
1.126 brouard 1939: int nbocc(char *s, char occ)
1940: {
1941: int i,j=0;
1942: int lg=20;
1943: i=0;
1944: lg=strlen(s);
1945: for(i=0; i<= lg; i++) {
1.234 brouard 1946: if (s[i] == occ ) j++;
1.126 brouard 1947: }
1948: return j;
1949: }
1950:
1.349 brouard 1951: int nboccstr(char *textin, char *chain)
1952: {
1953: /* Counts the number of occurence of "chain" in string textin */
1954: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1955: char *strloc;
1956:
1957: int i,j=0;
1958:
1959: i=0;
1960:
1961: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1962: for(;;) {
1963: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1964: if(strloc != NULL){
1965: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1966: j++;
1967: }else
1968: break;
1969: }
1970: return j;
1971:
1972: }
1.137 brouard 1973: /* void cutv(char *u,char *v, char*t, char occ) */
1974: /* { */
1975: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1976: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1977: /* gives u="abcdef2ghi" and v="j" *\/ */
1978: /* int i,lg,j,p=0; */
1979: /* i=0; */
1980: /* lg=strlen(t); */
1981: /* for(j=0; j<=lg-1; j++) { */
1982: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1983: /* } */
1.126 brouard 1984:
1.137 brouard 1985: /* for(j=0; j<p; j++) { */
1986: /* (u[j] = t[j]); */
1987: /* } */
1988: /* u[p]='\0'; */
1.126 brouard 1989:
1.137 brouard 1990: /* for(j=0; j<= lg; j++) { */
1991: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1992: /* } */
1993: /* } */
1.126 brouard 1994:
1.160 brouard 1995: #ifdef _WIN32
1996: char * strsep(char **pp, const char *delim)
1997: {
1998: char *p, *q;
1999:
2000: if ((p = *pp) == NULL)
2001: return 0;
2002: if ((q = strpbrk (p, delim)) != NULL)
2003: {
2004: *pp = q + 1;
2005: *q = '\0';
2006: }
2007: else
2008: *pp = 0;
2009: return p;
2010: }
2011: #endif
2012:
1.126 brouard 2013: /********************** nrerror ********************/
2014:
2015: void nrerror(char error_text[])
2016: {
2017: fprintf(stderr,"ERREUR ...\n");
2018: fprintf(stderr,"%s\n",error_text);
2019: exit(EXIT_FAILURE);
2020: }
2021: /*********************** vector *******************/
2022: double *vector(int nl, int nh)
2023: {
2024: double *v;
2025: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2026: if (!v) nrerror("allocation failure in vector");
2027: return v-nl+NR_END;
2028: }
2029:
2030: /************************ free vector ******************/
2031: void free_vector(double*v, int nl, int nh)
2032: {
2033: free((FREE_ARG)(v+nl-NR_END));
2034: }
2035:
2036: /************************ivector *******************************/
2037: int *ivector(long nl,long nh)
2038: {
2039: int *v;
2040: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2041: if (!v) nrerror("allocation failure in ivector");
2042: return v-nl+NR_END;
2043: }
2044:
2045: /******************free ivector **************************/
2046: void free_ivector(int *v, long nl, long nh)
2047: {
2048: free((FREE_ARG)(v+nl-NR_END));
2049: }
2050:
2051: /************************lvector *******************************/
2052: long *lvector(long nl,long nh)
2053: {
2054: long *v;
2055: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2056: if (!v) nrerror("allocation failure in ivector");
2057: return v-nl+NR_END;
2058: }
2059:
2060: /******************free lvector **************************/
2061: void free_lvector(long *v, long nl, long nh)
2062: {
2063: free((FREE_ARG)(v+nl-NR_END));
2064: }
2065:
2066: /******************* imatrix *******************************/
2067: int **imatrix(long nrl, long nrh, long ncl, long nch)
2068: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2069: {
2070: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2071: int **m;
2072:
2073: /* allocate pointers to rows */
2074: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2075: if (!m) nrerror("allocation failure 1 in matrix()");
2076: m += NR_END;
2077: m -= nrl;
2078:
2079:
2080: /* allocate rows and set pointers to them */
2081: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2082: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2083: m[nrl] += NR_END;
2084: m[nrl] -= ncl;
2085:
2086: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2087:
2088: /* return pointer to array of pointers to rows */
2089: return m;
2090: }
2091:
2092: /****************** free_imatrix *************************/
2093: void free_imatrix(m,nrl,nrh,ncl,nch)
2094: int **m;
2095: long nch,ncl,nrh,nrl;
2096: /* free an int matrix allocated by imatrix() */
2097: {
2098: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2099: free((FREE_ARG) (m+nrl-NR_END));
2100: }
2101:
2102: /******************* matrix *******************************/
2103: double **matrix(long nrl, long nrh, long ncl, long nch)
2104: {
2105: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2106: double **m;
2107:
2108: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2109: if (!m) nrerror("allocation failure 1 in matrix()");
2110: m += NR_END;
2111: m -= nrl;
2112:
2113: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2114: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2115: m[nrl] += NR_END;
2116: m[nrl] -= ncl;
2117:
2118: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2119: return m;
1.145 brouard 2120: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2121: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2122: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2123: */
2124: }
2125:
2126: /*************************free matrix ************************/
2127: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2128: {
2129: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2130: free((FREE_ARG)(m+nrl-NR_END));
2131: }
2132:
2133: /******************* ma3x *******************************/
2134: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2135: {
2136: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2137: double ***m;
2138:
2139: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2140: if (!m) nrerror("allocation failure 1 in matrix()");
2141: m += NR_END;
2142: m -= nrl;
2143:
2144: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2145: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2146: m[nrl] += NR_END;
2147: m[nrl] -= ncl;
2148:
2149: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2150:
2151: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2152: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2153: m[nrl][ncl] += NR_END;
2154: m[nrl][ncl] -= nll;
2155: for (j=ncl+1; j<=nch; j++)
2156: m[nrl][j]=m[nrl][j-1]+nlay;
2157:
2158: for (i=nrl+1; i<=nrh; i++) {
2159: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2160: for (j=ncl+1; j<=nch; j++)
2161: m[i][j]=m[i][j-1]+nlay;
2162: }
2163: return m;
2164: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2165: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2166: */
2167: }
2168:
2169: /*************************free ma3x ************************/
2170: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2171: {
2172: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2173: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2174: free((FREE_ARG)(m+nrl-NR_END));
2175: }
2176:
2177: /*************** function subdirf ***********/
2178: char *subdirf(char fileres[])
2179: {
2180: /* Caution optionfilefiname is hidden */
2181: strcpy(tmpout,optionfilefiname);
2182: strcat(tmpout,"/"); /* Add to the right */
2183: strcat(tmpout,fileres);
2184: return tmpout;
2185: }
2186:
2187: /*************** function subdirf2 ***********/
2188: char *subdirf2(char fileres[], char *preop)
2189: {
1.314 brouard 2190: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2191: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2192: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2193: /* Caution optionfilefiname is hidden */
2194: strcpy(tmpout,optionfilefiname);
2195: strcat(tmpout,"/");
2196: strcat(tmpout,preop);
2197: strcat(tmpout,fileres);
2198: return tmpout;
2199: }
2200:
2201: /*************** function subdirf3 ***********/
2202: char *subdirf3(char fileres[], char *preop, char *preop2)
2203: {
2204:
2205: /* Caution optionfilefiname is hidden */
2206: strcpy(tmpout,optionfilefiname);
2207: strcat(tmpout,"/");
2208: strcat(tmpout,preop);
2209: strcat(tmpout,preop2);
2210: strcat(tmpout,fileres);
2211: return tmpout;
2212: }
1.213 brouard 2213:
2214: /*************** function subdirfext ***********/
2215: char *subdirfext(char fileres[], char *preop, char *postop)
2216: {
2217:
2218: strcpy(tmpout,preop);
2219: strcat(tmpout,fileres);
2220: strcat(tmpout,postop);
2221: return tmpout;
2222: }
1.126 brouard 2223:
1.213 brouard 2224: /*************** function subdirfext3 ***********/
2225: char *subdirfext3(char fileres[], char *preop, char *postop)
2226: {
2227:
2228: /* Caution optionfilefiname is hidden */
2229: strcpy(tmpout,optionfilefiname);
2230: strcat(tmpout,"/");
2231: strcat(tmpout,preop);
2232: strcat(tmpout,fileres);
2233: strcat(tmpout,postop);
2234: return tmpout;
2235: }
2236:
1.162 brouard 2237: char *asc_diff_time(long time_sec, char ascdiff[])
2238: {
2239: long sec_left, days, hours, minutes;
2240: days = (time_sec) / (60*60*24);
2241: sec_left = (time_sec) % (60*60*24);
2242: hours = (sec_left) / (60*60) ;
2243: sec_left = (sec_left) %(60*60);
2244: minutes = (sec_left) /60;
2245: sec_left = (sec_left) % (60);
2246: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2247: return ascdiff;
2248: }
2249:
1.126 brouard 2250: /***************** f1dim *************************/
2251: extern int ncom;
2252: extern double *pcom,*xicom;
2253: extern double (*nrfunc)(double []);
2254:
2255: double f1dim(double x)
2256: {
2257: int j;
2258: double f;
2259: double *xt;
2260:
2261: xt=vector(1,ncom);
2262: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2263: f=(*nrfunc)(xt);
2264: free_vector(xt,1,ncom);
2265: return f;
2266: }
2267:
2268: /*****************brent *************************/
2269: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2270: {
2271: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2272: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2273: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2274: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2275: * returned function value.
2276: */
1.126 brouard 2277: int iter;
2278: double a,b,d,etemp;
1.159 brouard 2279: double fu=0,fv,fw,fx;
1.164 brouard 2280: double ftemp=0.;
1.126 brouard 2281: double p,q,r,tol1,tol2,u,v,w,x,xm;
2282: double e=0.0;
2283:
2284: a=(ax < cx ? ax : cx);
2285: b=(ax > cx ? ax : cx);
2286: x=w=v=bx;
2287: fw=fv=fx=(*f)(x);
2288: for (iter=1;iter<=ITMAX;iter++) {
2289: xm=0.5*(a+b);
2290: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2291: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2292: printf(".");fflush(stdout);
2293: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2294: #ifdef DEBUGBRENT
1.126 brouard 2295: 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);
2296: 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);
2297: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2298: #endif
2299: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2300: *xmin=x;
2301: return fx;
2302: }
2303: ftemp=fu;
2304: if (fabs(e) > tol1) {
2305: r=(x-w)*(fx-fv);
2306: q=(x-v)*(fx-fw);
2307: p=(x-v)*q-(x-w)*r;
2308: q=2.0*(q-r);
2309: if (q > 0.0) p = -p;
2310: q=fabs(q);
2311: etemp=e;
2312: e=d;
2313: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2314: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2315: else {
1.224 brouard 2316: d=p/q;
2317: u=x+d;
2318: if (u-a < tol2 || b-u < tol2)
2319: d=SIGN(tol1,xm-x);
1.126 brouard 2320: }
2321: } else {
2322: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2323: }
2324: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2325: fu=(*f)(u);
2326: if (fu <= fx) {
2327: if (u >= x) a=x; else b=x;
2328: SHFT(v,w,x,u)
1.183 brouard 2329: SHFT(fv,fw,fx,fu)
2330: } else {
2331: if (u < x) a=u; else b=u;
2332: if (fu <= fw || w == x) {
1.224 brouard 2333: v=w;
2334: w=u;
2335: fv=fw;
2336: fw=fu;
1.183 brouard 2337: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2338: v=u;
2339: fv=fu;
1.183 brouard 2340: }
2341: }
1.126 brouard 2342: }
2343: nrerror("Too many iterations in brent");
2344: *xmin=x;
2345: return fx;
2346: }
2347:
2348: /****************** mnbrak ***********************/
2349:
2350: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2351: double (*func)(double))
1.183 brouard 2352: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2353: the downhill direction (defined by the function as evaluated at the initial points) and returns
2354: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2355: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2356: */
1.126 brouard 2357: double ulim,u,r,q, dum;
2358: double fu;
1.187 brouard 2359:
2360: double scale=10.;
2361: int iterscale=0;
2362:
2363: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2364: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2365:
2366:
2367: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2368: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2369: /* *bx = *ax - (*ax - *bx)/scale; */
2370: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2371: /* } */
2372:
1.126 brouard 2373: if (*fb > *fa) {
2374: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2375: SHFT(dum,*fb,*fa,dum)
2376: }
1.126 brouard 2377: *cx=(*bx)+GOLD*(*bx-*ax);
2378: *fc=(*func)(*cx);
1.183 brouard 2379: #ifdef DEBUG
1.224 brouard 2380: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2381: 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 2382: #endif
1.224 brouard 2383: 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 2384: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2385: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2386: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2387: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2388: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2389: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2390: fu=(*func)(u);
1.163 brouard 2391: #ifdef DEBUG
2392: /* f(x)=A(x-u)**2+f(u) */
2393: double A, fparabu;
2394: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2395: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2396: 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);
2397: 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 2398: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2399: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2400: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2401: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2402: #endif
1.184 brouard 2403: #ifdef MNBRAKORIGINAL
1.183 brouard 2404: #else
1.191 brouard 2405: /* if (fu > *fc) { */
2406: /* #ifdef DEBUG */
2407: /* printf("mnbrak4 fu > fc \n"); */
2408: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2409: /* #endif */
2410: /* /\* 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 *\\/ *\/ */
2411: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2412: /* dum=u; /\* Shifting c and u *\/ */
2413: /* u = *cx; */
2414: /* *cx = dum; */
2415: /* dum = fu; */
2416: /* fu = *fc; */
2417: /* *fc =dum; */
2418: /* } else { /\* end *\/ */
2419: /* #ifdef DEBUG */
2420: /* printf("mnbrak3 fu < fc \n"); */
2421: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2422: /* #endif */
2423: /* dum=u; /\* Shifting c and u *\/ */
2424: /* u = *cx; */
2425: /* *cx = dum; */
2426: /* dum = fu; */
2427: /* fu = *fc; */
2428: /* *fc =dum; */
2429: /* } */
1.224 brouard 2430: #ifdef DEBUGMNBRAK
2431: double A, fparabu;
2432: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2433: fparabu= *fa - A*(*ax-u)*(*ax-u);
2434: 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);
2435: 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 2436: #endif
1.191 brouard 2437: dum=u; /* Shifting c and u */
2438: u = *cx;
2439: *cx = dum;
2440: dum = fu;
2441: fu = *fc;
2442: *fc =dum;
1.183 brouard 2443: #endif
1.162 brouard 2444: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2445: #ifdef DEBUG
1.224 brouard 2446: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2447: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2448: #endif
1.126 brouard 2449: fu=(*func)(u);
2450: if (fu < *fc) {
1.183 brouard 2451: #ifdef DEBUG
1.224 brouard 2452: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2453: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2454: #endif
2455: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2456: SHFT(*fb,*fc,fu,(*func)(u))
2457: #ifdef DEBUG
2458: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2459: #endif
2460: }
1.162 brouard 2461: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2462: #ifdef DEBUG
1.224 brouard 2463: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2464: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2465: #endif
1.126 brouard 2466: u=ulim;
2467: fu=(*func)(u);
1.183 brouard 2468: } else { /* u could be left to b (if r > q parabola has a maximum) */
2469: #ifdef DEBUG
1.224 brouard 2470: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2471: 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 2472: #endif
1.126 brouard 2473: u=(*cx)+GOLD*(*cx-*bx);
2474: fu=(*func)(u);
1.224 brouard 2475: #ifdef DEBUG
2476: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2477: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2478: #endif
1.183 brouard 2479: } /* end tests */
1.126 brouard 2480: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2481: SHFT(*fa,*fb,*fc,fu)
2482: #ifdef DEBUG
1.224 brouard 2483: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2484: 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 2485: #endif
2486: } /* 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 2487: }
2488:
2489: /*************** linmin ************************/
1.162 brouard 2490: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2491: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2492: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2493: the value of func at the returned location p . This is actually all accomplished by calling the
2494: routines mnbrak and brent .*/
1.126 brouard 2495: int ncom;
2496: double *pcom,*xicom;
2497: double (*nrfunc)(double []);
2498:
1.224 brouard 2499: #ifdef LINMINORIGINAL
1.126 brouard 2500: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2501: #else
2502: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2503: #endif
1.126 brouard 2504: {
2505: double brent(double ax, double bx, double cx,
2506: double (*f)(double), double tol, double *xmin);
2507: double f1dim(double x);
2508: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2509: double *fc, double (*func)(double));
2510: int j;
2511: double xx,xmin,bx,ax;
2512: double fx,fb,fa;
1.187 brouard 2513:
1.203 brouard 2514: #ifdef LINMINORIGINAL
2515: #else
2516: double scale=10., axs, xxs; /* Scale added for infinity */
2517: #endif
2518:
1.126 brouard 2519: ncom=n;
2520: pcom=vector(1,n);
2521: xicom=vector(1,n);
2522: nrfunc=func;
2523: for (j=1;j<=n;j++) {
2524: pcom[j]=p[j];
1.202 brouard 2525: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2526: }
1.187 brouard 2527:
1.203 brouard 2528: #ifdef LINMINORIGINAL
2529: xx=1.;
2530: #else
2531: axs=0.0;
2532: xxs=1.;
2533: do{
2534: xx= xxs;
2535: #endif
1.187 brouard 2536: ax=0.;
2537: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2538: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2539: /* 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)) */
2540: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2541: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2542: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2543: /* 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 2544: #ifdef LINMINORIGINAL
2545: #else
2546: if (fx != fx){
1.224 brouard 2547: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2548: printf("|");
2549: fprintf(ficlog,"|");
1.203 brouard 2550: #ifdef DEBUGLINMIN
1.224 brouard 2551: 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 2552: #endif
2553: }
1.224 brouard 2554: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2555: #endif
2556:
1.191 brouard 2557: #ifdef DEBUGLINMIN
2558: 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 2559: 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 2560: #endif
1.224 brouard 2561: #ifdef LINMINORIGINAL
2562: #else
1.317 brouard 2563: if(fb == fx){ /* Flat function in the direction */
2564: xmin=xx;
1.224 brouard 2565: *flat=1;
1.317 brouard 2566: }else{
1.224 brouard 2567: *flat=0;
2568: #endif
2569: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2570: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2571: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2572: /* fmin = f(p[j] + xmin * xi[j]) */
2573: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2574: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2575: #ifdef DEBUG
1.224 brouard 2576: 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);
2577: 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);
2578: #endif
2579: #ifdef LINMINORIGINAL
2580: #else
2581: }
1.126 brouard 2582: #endif
1.191 brouard 2583: #ifdef DEBUGLINMIN
2584: printf("linmin end ");
1.202 brouard 2585: fprintf(ficlog,"linmin end ");
1.191 brouard 2586: #endif
1.126 brouard 2587: for (j=1;j<=n;j++) {
1.203 brouard 2588: #ifdef LINMINORIGINAL
2589: xi[j] *= xmin;
2590: #else
2591: #ifdef DEBUGLINMIN
2592: if(xxs <1.0)
2593: printf(" before xi[%d]=%12.8f", j,xi[j]);
2594: #endif
2595: 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) */
2596: #ifdef DEBUGLINMIN
2597: if(xxs <1.0)
2598: 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 );
2599: #endif
2600: #endif
1.187 brouard 2601: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2602: }
1.191 brouard 2603: #ifdef DEBUGLINMIN
1.203 brouard 2604: printf("\n");
1.191 brouard 2605: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2606: 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 2607: for (j=1;j<=n;j++) {
1.202 brouard 2608: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2609: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2610: if(j % ncovmodel == 0){
1.191 brouard 2611: printf("\n");
1.202 brouard 2612: fprintf(ficlog,"\n");
2613: }
1.191 brouard 2614: }
1.203 brouard 2615: #else
1.191 brouard 2616: #endif
1.126 brouard 2617: free_vector(xicom,1,n);
2618: free_vector(pcom,1,n);
2619: }
2620:
2621:
2622: /*************** powell ************************/
1.162 brouard 2623: /*
1.317 brouard 2624: Minimization of a function func of n variables. Input consists in an initial starting point
2625: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2626: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2627: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2628: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2629: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2630: */
1.224 brouard 2631: #ifdef LINMINORIGINAL
2632: #else
2633: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2634: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2635: #endif
1.126 brouard 2636: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2637: double (*func)(double []))
2638: {
1.224 brouard 2639: #ifdef LINMINORIGINAL
2640: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2641: double (*func)(double []));
1.224 brouard 2642: #else
1.241 brouard 2643: void linmin(double p[], double xi[], int n, double *fret,
2644: double (*func)(double []),int *flat);
1.224 brouard 2645: #endif
1.239 brouard 2646: int i,ibig,j,jk,k;
1.126 brouard 2647: double del,t,*pt,*ptt,*xit;
1.181 brouard 2648: double directest;
1.126 brouard 2649: double fp,fptt;
2650: double *xits;
2651: int niterf, itmp;
1.349 brouard 2652: int Bigter=0, nBigterf=1;
2653:
1.126 brouard 2654: pt=vector(1,n);
2655: ptt=vector(1,n);
2656: xit=vector(1,n);
2657: xits=vector(1,n);
2658: *fret=(*func)(p);
2659: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2660: rcurr_time = time(NULL);
2661: fp=(*fret); /* Initialisation */
1.126 brouard 2662: for (*iter=1;;++(*iter)) {
2663: ibig=0;
2664: del=0.0;
1.157 brouard 2665: rlast_time=rcurr_time;
1.349 brouard 2666: rlast_btime=rcurr_time;
1.157 brouard 2667: /* (void) gettimeofday(&curr_time,&tzp); */
2668: rcurr_time = time(NULL);
2669: curr_time = *localtime(&rcurr_time);
1.337 brouard 2670: /* 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); */
2671: /* 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); */
1.349 brouard 2672: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
2673: 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);
2674: 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);
2675: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2676: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2677: for (i=1;i<=n;i++) {
1.126 brouard 2678: fprintf(ficrespow," %.12lf", p[i]);
2679: }
1.239 brouard 2680: fprintf(ficrespow,"\n");fflush(ficrespow);
2681: printf("\n#model= 1 + age ");
2682: fprintf(ficlog,"\n#model= 1 + age ");
2683: if(nagesqr==1){
1.241 brouard 2684: printf(" + age*age ");
2685: fprintf(ficlog," + age*age ");
1.239 brouard 2686: }
2687: for(j=1;j <=ncovmodel-2;j++){
2688: if(Typevar[j]==0) {
2689: printf(" + V%d ",Tvar[j]);
2690: fprintf(ficlog," + V%d ",Tvar[j]);
2691: }else if(Typevar[j]==1) {
2692: printf(" + V%d*age ",Tvar[j]);
2693: fprintf(ficlog," + V%d*age ",Tvar[j]);
2694: }else if(Typevar[j]==2) {
2695: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2696: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 2697: }else if(Typevar[j]==3) {
2698: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2699: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2700: }
2701: }
1.126 brouard 2702: printf("\n");
1.239 brouard 2703: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2704: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2705: fprintf(ficlog,"\n");
1.239 brouard 2706: for(i=1,jk=1; i <=nlstate; i++){
2707: for(k=1; k <=(nlstate+ndeath); k++){
2708: if (k != i) {
2709: printf("%d%d ",i,k);
2710: fprintf(ficlog,"%d%d ",i,k);
2711: for(j=1; j <=ncovmodel; j++){
2712: printf("%12.7f ",p[jk]);
2713: fprintf(ficlog,"%12.7f ",p[jk]);
2714: jk++;
2715: }
2716: printf("\n");
2717: fprintf(ficlog,"\n");
2718: }
2719: }
2720: }
1.241 brouard 2721: if(*iter <=3 && *iter >1){
1.157 brouard 2722: tml = *localtime(&rcurr_time);
2723: strcpy(strcurr,asctime(&tml));
2724: rforecast_time=rcurr_time;
1.126 brouard 2725: itmp = strlen(strcurr);
2726: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2727: strcurr[itmp-1]='\0';
1.162 brouard 2728: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2729: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 2730: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
2731: niterf=nBigterf*ncovmodel;
2732: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2733: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2734: forecast_time = *localtime(&rforecast_time);
2735: strcpy(strfor,asctime(&forecast_time));
2736: itmp = strlen(strfor);
2737: if(strfor[itmp-1]=='\n')
2738: strfor[itmp-1]='\0';
1.349 brouard 2739: 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);
2740: 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 2741: }
2742: }
1.187 brouard 2743: for (i=1;i<=n;i++) { /* For each direction i */
2744: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2745: fptt=(*fret);
2746: #ifdef DEBUG
1.203 brouard 2747: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2748: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2749: #endif
1.203 brouard 2750: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2751: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2752: #ifdef LINMINORIGINAL
1.188 brouard 2753: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2754: #else
2755: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2756: flatdir[i]=flat; /* Function is vanishing in that direction i */
2757: #endif
2758: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2759: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2760: /* because that direction will be replaced unless the gain del is small */
2761: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2762: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2763: /* with the new direction. */
2764: del=fabs(fptt-(*fret));
2765: ibig=i;
1.126 brouard 2766: }
2767: #ifdef DEBUG
2768: printf("%d %.12e",i,(*fret));
2769: fprintf(ficlog,"%d %.12e",i,(*fret));
2770: for (j=1;j<=n;j++) {
1.224 brouard 2771: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2772: printf(" x(%d)=%.12e",j,xit[j]);
2773: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2774: }
2775: for(j=1;j<=n;j++) {
1.225 brouard 2776: printf(" p(%d)=%.12e",j,p[j]);
2777: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2778: }
2779: printf("\n");
2780: fprintf(ficlog,"\n");
2781: #endif
1.187 brouard 2782: } /* end loop on each direction i */
2783: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2784: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2785: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2786: for(j=1;j<=n;j++) {
2787: if(flatdir[j] >0){
2788: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2789: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2790: }
1.319 brouard 2791: /* printf("\n"); */
2792: /* fprintf(ficlog,"\n"); */
2793: }
1.243 brouard 2794: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2795: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2796: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2797: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2798: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2799: /* decreased of more than 3.84 */
2800: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2801: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2802: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2803:
1.188 brouard 2804: /* Starting the program with initial values given by a former maximization will simply change */
2805: /* the scales of the directions and the directions, because the are reset to canonical directions */
2806: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2807: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2808: #ifdef DEBUG
2809: int k[2],l;
2810: k[0]=1;
2811: k[1]=-1;
2812: printf("Max: %.12e",(*func)(p));
2813: fprintf(ficlog,"Max: %.12e",(*func)(p));
2814: for (j=1;j<=n;j++) {
2815: printf(" %.12e",p[j]);
2816: fprintf(ficlog," %.12e",p[j]);
2817: }
2818: printf("\n");
2819: fprintf(ficlog,"\n");
2820: for(l=0;l<=1;l++) {
2821: for (j=1;j<=n;j++) {
2822: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2823: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2824: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2825: }
2826: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2827: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2828: }
2829: #endif
2830:
2831: free_vector(xit,1,n);
2832: free_vector(xits,1,n);
2833: free_vector(ptt,1,n);
2834: free_vector(pt,1,n);
2835: return;
1.192 brouard 2836: } /* enough precision */
1.240 brouard 2837: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2838: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2839: ptt[j]=2.0*p[j]-pt[j];
2840: xit[j]=p[j]-pt[j];
2841: pt[j]=p[j];
2842: }
1.181 brouard 2843: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2844: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2845: if (*iter <=4) {
1.225 brouard 2846: #else
2847: #endif
1.224 brouard 2848: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2849: #else
1.161 brouard 2850: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2851: #endif
1.162 brouard 2852: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2853: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2854: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2855: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2856: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2857: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2858: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2859: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2860: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2861: /* Even if f3 <f1, directest can be negative and t >0 */
2862: /* mu² and del² are equal when f3=f1 */
2863: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2864: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2865: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2866: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2867: #ifdef NRCORIGINAL
2868: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2869: #else
2870: 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 2871: t= t- del*SQR(fp-fptt);
1.183 brouard 2872: #endif
1.202 brouard 2873: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2874: #ifdef DEBUG
1.181 brouard 2875: 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);
2876: 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 2877: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2878: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2879: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2880: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2881: 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);
2882: 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);
2883: #endif
1.183 brouard 2884: #ifdef POWELLORIGINAL
2885: if (t < 0.0) { /* Then we use it for new direction */
2886: #else
1.182 brouard 2887: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2888: 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 2889: 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 2890: 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 2891: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2892: }
1.181 brouard 2893: if (directest < 0.0) { /* Then we use it for new direction */
2894: #endif
1.191 brouard 2895: #ifdef DEBUGLINMIN
1.234 brouard 2896: printf("Before linmin in direction P%d-P0\n",n);
2897: for (j=1;j<=n;j++) {
2898: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2899: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2900: if(j % ncovmodel == 0){
2901: printf("\n");
2902: fprintf(ficlog,"\n");
2903: }
2904: }
1.224 brouard 2905: #endif
2906: #ifdef LINMINORIGINAL
1.234 brouard 2907: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2908: #else
1.234 brouard 2909: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2910: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2911: #endif
1.234 brouard 2912:
1.191 brouard 2913: #ifdef DEBUGLINMIN
1.234 brouard 2914: for (j=1;j<=n;j++) {
2915: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2916: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2917: if(j % ncovmodel == 0){
2918: printf("\n");
2919: fprintf(ficlog,"\n");
2920: }
2921: }
1.224 brouard 2922: #endif
1.234 brouard 2923: for (j=1;j<=n;j++) {
2924: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2925: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2926: }
1.224 brouard 2927: #ifdef LINMINORIGINAL
2928: #else
1.234 brouard 2929: for (j=1, flatd=0;j<=n;j++) {
2930: if(flatdir[j]>0)
2931: flatd++;
2932: }
2933: if(flatd >0){
1.255 brouard 2934: printf("%d flat directions: ",flatd);
2935: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2936: for (j=1;j<=n;j++) {
2937: if(flatdir[j]>0){
2938: printf("%d ",j);
2939: fprintf(ficlog,"%d ",j);
2940: }
2941: }
2942: printf("\n");
2943: fprintf(ficlog,"\n");
1.319 brouard 2944: #ifdef FLATSUP
2945: free_vector(xit,1,n);
2946: free_vector(xits,1,n);
2947: free_vector(ptt,1,n);
2948: free_vector(pt,1,n);
2949: return;
2950: #endif
1.234 brouard 2951: }
1.191 brouard 2952: #endif
1.234 brouard 2953: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2954: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2955:
1.126 brouard 2956: #ifdef DEBUG
1.234 brouard 2957: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2958: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2959: for(j=1;j<=n;j++){
2960: printf(" %lf",xit[j]);
2961: fprintf(ficlog," %lf",xit[j]);
2962: }
2963: printf("\n");
2964: fprintf(ficlog,"\n");
1.126 brouard 2965: #endif
1.192 brouard 2966: } /* end of t or directest negative */
1.224 brouard 2967: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2968: #else
1.234 brouard 2969: } /* end if (fptt < fp) */
1.192 brouard 2970: #endif
1.225 brouard 2971: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2972: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2973: #else
1.224 brouard 2974: #endif
1.234 brouard 2975: } /* loop iteration */
1.126 brouard 2976: }
1.234 brouard 2977:
1.126 brouard 2978: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2979:
1.235 brouard 2980: 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 2981: {
1.338 brouard 2982: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2983: * (and selected quantitative values in nres)
2984: * by left multiplying the unit
2985: * matrix by transitions matrix until convergence is reached with precision ftolpl
2986: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2987: * Wx is row vector: population in state 1, population in state 2, population dead
2988: * or prevalence in state 1, prevalence in state 2, 0
2989: * newm is the matrix after multiplications, its rows are identical at a factor.
2990: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2991: * Output is prlim.
2992: * Initial matrix pimij
2993: */
1.206 brouard 2994: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2995: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2996: /* 0, 0 , 1} */
2997: /*
2998: * and after some iteration: */
2999: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3000: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3001: /* 0, 0 , 1} */
3002: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3003: /* {0.51571254859325999, 0.4842874514067399, */
3004: /* 0.51326036147820708, 0.48673963852179264} */
3005: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 3006:
1.332 brouard 3007: int i, ii,j,k, k1;
1.209 brouard 3008: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 3009: /* double **matprod2(); */ /* test */
1.218 brouard 3010: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 3011: double **newm;
1.209 brouard 3012: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 3013: int ncvloop=0;
1.288 brouard 3014: int first=0;
1.169 brouard 3015:
1.209 brouard 3016: min=vector(1,nlstate);
3017: max=vector(1,nlstate);
3018: meandiff=vector(1,nlstate);
3019:
1.218 brouard 3020: /* Starting with matrix unity */
1.126 brouard 3021: for (ii=1;ii<=nlstate+ndeath;ii++)
3022: for (j=1;j<=nlstate+ndeath;j++){
3023: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3024: }
1.169 brouard 3025:
3026: cov[1]=1.;
3027:
3028: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 3029: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 3030: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 3031: ncvloop++;
1.126 brouard 3032: newm=savm;
3033: /* Covariates have to be included here again */
1.138 brouard 3034: cov[2]=agefin;
1.319 brouard 3035: if(nagesqr==1){
3036: cov[3]= agefin*agefin;
3037: }
1.332 brouard 3038: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3039: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3040: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3041: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3042: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3043: }else{
3044: cov[2+nagesqr+k1]=precov[nres][k1];
3045: }
3046: }/* End of loop on model equation */
3047:
3048: /* Start of old code (replaced by a loop on position in the model equation */
3049: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3050: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3051: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3052: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3053: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3054: /* * k 1 2 3 4 5 6 7 8 */
3055: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3056: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3057: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3058: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3059: /* *nsd=3 (1) (2) (3) */
3060: /* *TvarsD[nsd] [1]=2 1 3 */
3061: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3062: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3063: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3064: /* *Tvard[] [1][1]=1 [2][1]=1 */
3065: /* * [1][2]=3 [2][2]=2 */
3066: /* *Tprod[](=k) [1]=1 [2]=8 */
3067: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3068: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3069: /* *TvarsDpType */
3070: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3071: /* * nsd=1 (1) (2) */
3072: /* *TvarsD[nsd] 3 2 */
3073: /* *TnsdVar (3)=1 (2)=2 */
3074: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3075: /* *Tage[] [1]=2 [2]= 3 */
3076: /* *\/ */
3077: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3078: /* /\* 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)); *\/ */
3079: /* } */
3080: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3081: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3082: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3083: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3084: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3085: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3086: /* /\* 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]); *\/ */
3087: /* } */
3088: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3089: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3090: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3091: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3092: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3093: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3094: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3095: /* } */
3096: /* /\* 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]); *\/ */
3097: /* } */
3098: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3099: /* /\* 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]); *\/ */
3100: /* if(Dummy[Tvard[k][1]]==0){ */
3101: /* if(Dummy[Tvard[k][2]]==0){ */
3102: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3103: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3104: /* }else{ */
3105: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3106: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3107: /* } */
3108: /* }else{ */
3109: /* if(Dummy[Tvard[k][2]]==0){ */
3110: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3111: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3112: /* }else{ */
3113: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3114: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3115: /* } */
3116: /* } */
3117: /* } /\* End product without age *\/ */
3118: /* ENd of old code */
1.138 brouard 3119: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3120: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3121: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3122: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3123: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3124: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3125: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3126:
1.126 brouard 3127: savm=oldm;
3128: oldm=newm;
1.209 brouard 3129:
3130: for(j=1; j<=nlstate; j++){
3131: max[j]=0.;
3132: min[j]=1.;
3133: }
3134: for(i=1;i<=nlstate;i++){
3135: sumnew=0;
3136: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3137: for(j=1; j<=nlstate; j++){
3138: prlim[i][j]= newm[i][j]/(1-sumnew);
3139: max[j]=FMAX(max[j],prlim[i][j]);
3140: min[j]=FMIN(min[j],prlim[i][j]);
3141: }
3142: }
3143:
1.126 brouard 3144: maxmax=0.;
1.209 brouard 3145: for(j=1; j<=nlstate; j++){
3146: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3147: maxmax=FMAX(maxmax,meandiff[j]);
3148: /* 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 3149: } /* j loop */
1.203 brouard 3150: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3151: /* 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 3152: if(maxmax < ftolpl){
1.209 brouard 3153: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3154: free_vector(min,1,nlstate);
3155: free_vector(max,1,nlstate);
3156: free_vector(meandiff,1,nlstate);
1.126 brouard 3157: return prlim;
3158: }
1.288 brouard 3159: } /* agefin loop */
1.208 brouard 3160: /* After some age loop it doesn't converge */
1.288 brouard 3161: if(!first){
3162: first=1;
3163: 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 3164: 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);
3165: }else if (first >=1 && first <10){
3166: 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);
3167: first++;
3168: }else if (first ==10){
3169: 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);
3170: 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");
3171: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3172: first++;
1.288 brouard 3173: }
3174:
1.209 brouard 3175: /* 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); */
3176: free_vector(min,1,nlstate);
3177: free_vector(max,1,nlstate);
3178: free_vector(meandiff,1,nlstate);
1.208 brouard 3179:
1.169 brouard 3180: return prlim; /* should not reach here */
1.126 brouard 3181: }
3182:
1.217 brouard 3183:
3184: /**** Back Prevalence limit (stable or period prevalence) ****************/
3185:
1.218 brouard 3186: /* 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) */
3187: /* 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 3188: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3189: {
1.264 brouard 3190: /* 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 3191: matrix by transitions matrix until convergence is reached with precision ftolpl */
3192: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3193: /* Wx is row vector: population in state 1, population in state 2, population dead */
3194: /* or prevalence in state 1, prevalence in state 2, 0 */
3195: /* newm is the matrix after multiplications, its rows are identical at a factor */
3196: /* Initial matrix pimij */
3197: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3198: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3199: /* 0, 0 , 1} */
3200: /*
3201: * and after some iteration: */
3202: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3203: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3204: /* 0, 0 , 1} */
3205: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3206: /* {0.51571254859325999, 0.4842874514067399, */
3207: /* 0.51326036147820708, 0.48673963852179264} */
3208: /* If we start from prlim again, prlim tends to a constant matrix */
3209:
1.332 brouard 3210: int i, ii,j,k, k1;
1.247 brouard 3211: int first=0;
1.217 brouard 3212: double *min, *max, *meandiff, maxmax,sumnew=0.;
3213: /* double **matprod2(); */ /* test */
3214: double **out, cov[NCOVMAX+1], **bmij();
3215: double **newm;
1.218 brouard 3216: double **dnewm, **doldm, **dsavm; /* for use */
3217: double **oldm, **savm; /* for use */
3218:
1.217 brouard 3219: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3220: int ncvloop=0;
3221:
3222: min=vector(1,nlstate);
3223: max=vector(1,nlstate);
3224: meandiff=vector(1,nlstate);
3225:
1.266 brouard 3226: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3227: oldm=oldms; savm=savms;
3228:
3229: /* Starting with matrix unity */
3230: for (ii=1;ii<=nlstate+ndeath;ii++)
3231: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3232: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3233: }
3234:
3235: cov[1]=1.;
3236:
3237: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3238: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3239: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3240: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3241: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3242: ncvloop++;
1.218 brouard 3243: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3244: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3245: /* Covariates have to be included here again */
3246: cov[2]=agefin;
1.319 brouard 3247: if(nagesqr==1){
1.217 brouard 3248: cov[3]= agefin*agefin;;
1.319 brouard 3249: }
1.332 brouard 3250: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3251: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3252: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3253: }else{
1.332 brouard 3254: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3255: }
1.332 brouard 3256: }/* End of loop on model equation */
3257:
3258: /* Old code */
3259:
3260: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3261: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3262: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3263: /* /\* 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)); *\/ */
3264: /* } */
3265: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3266: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3267: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3268: /* /\* /\\* 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])]); *\\/ *\/ */
3269: /* /\* } *\/ */
3270: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3271: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3272: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3273: /* /\* 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]); *\/ */
3274: /* } */
3275: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3276: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3277: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3278: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3279: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3280: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3281: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3282: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3283: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3284: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3285: /* } */
3286: /* /\* 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]); *\/ */
3287: /* } */
3288: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3289: /* /\* 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]); *\/ */
3290: /* if(Dummy[Tvard[k][1]]==0){ */
3291: /* if(Dummy[Tvard[k][2]]==0){ */
3292: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3293: /* }else{ */
3294: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3295: /* } */
3296: /* }else{ */
3297: /* if(Dummy[Tvard[k][2]]==0){ */
3298: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3299: /* }else{ */
3300: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3301: /* } */
3302: /* } */
3303: /* } */
1.217 brouard 3304:
3305: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3306: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3307: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3308: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3309: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3310: /* ij should be linked to the correct index of cov */
3311: /* age and covariate values ij are in 'cov', but we need to pass
3312: * ij for the observed prevalence at age and status and covariate
3313: * number: prevacurrent[(int)agefin][ii][ij]
3314: */
3315: /* 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 *\/ */
3316: /* 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 *\/ */
3317: 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 3318: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3319: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3320: /* for(i=1; i<=nlstate+ndeath; i++) { */
3321: /* printf("%d newm= ",i); */
3322: /* for(j=1;j<=nlstate+ndeath;j++) { */
3323: /* printf("%f ",newm[i][j]); */
3324: /* } */
3325: /* printf("oldm * "); */
3326: /* for(j=1;j<=nlstate+ndeath;j++) { */
3327: /* printf("%f ",oldm[i][j]); */
3328: /* } */
1.268 brouard 3329: /* printf(" bmmij "); */
1.266 brouard 3330: /* for(j=1;j<=nlstate+ndeath;j++) { */
3331: /* printf("%f ",pmmij[i][j]); */
3332: /* } */
3333: /* printf("\n"); */
3334: /* } */
3335: /* } */
1.217 brouard 3336: savm=oldm;
3337: oldm=newm;
1.266 brouard 3338:
1.217 brouard 3339: for(j=1; j<=nlstate; j++){
3340: max[j]=0.;
3341: min[j]=1.;
3342: }
3343: for(j=1; j<=nlstate; j++){
3344: for(i=1;i<=nlstate;i++){
1.234 brouard 3345: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3346: bprlim[i][j]= newm[i][j];
3347: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3348: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3349: }
3350: }
1.218 brouard 3351:
1.217 brouard 3352: maxmax=0.;
3353: for(i=1; i<=nlstate; i++){
1.318 brouard 3354: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3355: maxmax=FMAX(maxmax,meandiff[i]);
3356: /* 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 3357: } /* i loop */
1.217 brouard 3358: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3359: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3360: if(maxmax < ftolpl){
1.220 brouard 3361: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3362: free_vector(min,1,nlstate);
3363: free_vector(max,1,nlstate);
3364: free_vector(meandiff,1,nlstate);
3365: return bprlim;
3366: }
1.288 brouard 3367: } /* agefin loop */
1.217 brouard 3368: /* After some age loop it doesn't converge */
1.288 brouard 3369: if(!first){
1.247 brouard 3370: first=1;
3371: 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\
3372: 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);
3373: }
3374: 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 3375: 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);
3376: /* 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); */
3377: free_vector(min,1,nlstate);
3378: free_vector(max,1,nlstate);
3379: free_vector(meandiff,1,nlstate);
3380:
3381: return bprlim; /* should not reach here */
3382: }
3383:
1.126 brouard 3384: /*************** transition probabilities ***************/
3385:
3386: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3387: {
1.138 brouard 3388: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3389: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3390: model to the ncovmodel covariates (including constant and age).
3391: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3392: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3393: ncth covariate in the global vector x is given by the formula:
3394: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3395: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3396: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3397: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3398: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3399: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3400: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3401: */
3402: double s1, lnpijopii;
1.126 brouard 3403: /*double t34;*/
1.164 brouard 3404: int i,j, nc, ii, jj;
1.126 brouard 3405:
1.223 brouard 3406: for(i=1; i<= nlstate; i++){
3407: for(j=1; j<i;j++){
3408: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3409: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3410: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3411: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3412: }
3413: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3414: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3415: }
3416: for(j=i+1; j<=nlstate+ndeath;j++){
3417: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3418: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3419: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3420: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3421: }
3422: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3423: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3424: }
3425: }
1.218 brouard 3426:
1.223 brouard 3427: for(i=1; i<= nlstate; i++){
3428: s1=0;
3429: for(j=1; j<i; j++){
1.339 brouard 3430: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3431: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3432: }
3433: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3434: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3435: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3436: }
3437: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3438: ps[i][i]=1./(s1+1.);
3439: /* Computing other pijs */
3440: for(j=1; j<i; j++)
1.325 brouard 3441: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3442: for(j=i+1; j<=nlstate+ndeath; j++)
3443: ps[i][j]= exp(ps[i][j])*ps[i][i];
3444: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3445: } /* end i */
1.218 brouard 3446:
1.223 brouard 3447: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3448: for(jj=1; jj<= nlstate+ndeath; jj++){
3449: ps[ii][jj]=0;
3450: ps[ii][ii]=1;
3451: }
3452: }
1.294 brouard 3453:
3454:
1.223 brouard 3455: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3456: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3457: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3458: /* } */
3459: /* printf("\n "); */
3460: /* } */
3461: /* printf("\n ");printf("%lf ",cov[2]);*/
3462: /*
3463: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3464: goto end;*/
1.266 brouard 3465: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3466: }
3467:
1.218 brouard 3468: /*************** backward transition probabilities ***************/
3469:
3470: /* 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 ) */
3471: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3472: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3473: {
1.302 brouard 3474: /* 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 3475: * 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 3476: */
1.218 brouard 3477: int i, ii, j,k;
1.222 brouard 3478:
3479: double **out, **pmij();
3480: double sumnew=0.;
1.218 brouard 3481: double agefin;
1.292 brouard 3482: 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 3483: double **dnewm, **dsavm, **doldm;
3484: double **bbmij;
3485:
1.218 brouard 3486: doldm=ddoldms; /* global pointers */
1.222 brouard 3487: dnewm=ddnewms;
3488: dsavm=ddsavms;
1.318 brouard 3489:
3490: /* Debug */
3491: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3492: agefin=cov[2];
1.268 brouard 3493: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3494: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3495: the observed prevalence (with this covariate ij) at beginning of transition */
3496: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3497:
3498: /* P_x */
1.325 brouard 3499: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3500: /* outputs pmmij which is a stochastic matrix in row */
3501:
3502: /* Diag(w_x) */
1.292 brouard 3503: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3504: sumnew=0.;
1.269 brouard 3505: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3506: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3507: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3508: sumnew+=prevacurrent[(int)agefin][ii][ij];
3509: }
3510: if(sumnew >0.01){ /* At least some value in the prevalence */
3511: for (ii=1;ii<=nlstate+ndeath;ii++){
3512: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3513: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3514: }
3515: }else{
3516: for (ii=1;ii<=nlstate+ndeath;ii++){
3517: for (j=1;j<=nlstate+ndeath;j++)
3518: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3519: }
3520: /* if(sumnew <0.9){ */
3521: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3522: /* } */
3523: }
3524: k3=0.0; /* We put the last diagonal to 0 */
3525: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3526: doldm[ii][ii]= k3;
3527: }
3528: /* End doldm, At the end doldm is diag[(w_i)] */
3529:
1.292 brouard 3530: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3531: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3532:
1.292 brouard 3533: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3534: /* 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 3535: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3536: sumnew=0.;
1.222 brouard 3537: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3538: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3539: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3540: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3541: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3542: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3543: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3544: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3545: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3546: /* }else */
1.268 brouard 3547: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3548: } /*End ii */
3549: } /* 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 */
3550:
1.292 brouard 3551: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3552: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3553: /* end bmij */
1.266 brouard 3554: return ps; /*pointer is unchanged */
1.218 brouard 3555: }
1.217 brouard 3556: /*************** transition probabilities ***************/
3557:
1.218 brouard 3558: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3559: {
3560: /* According to parameters values stored in x and the covariate's values stored in cov,
3561: computes the probability to be observed in state j being in state i by appying the
3562: model to the ncovmodel covariates (including constant and age).
3563: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3564: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3565: ncth covariate in the global vector x is given by the formula:
3566: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3567: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3568: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3569: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3570: Outputs ps[i][j] the probability to be observed in j being in j according to
3571: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3572: */
3573: double s1, lnpijopii;
3574: /*double t34;*/
3575: int i,j, nc, ii, jj;
3576:
1.234 brouard 3577: for(i=1; i<= nlstate; i++){
3578: for(j=1; j<i;j++){
3579: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3580: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3581: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3582: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3583: }
3584: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3585: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3586: }
3587: for(j=i+1; j<=nlstate+ndeath;j++){
3588: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3589: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3590: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3591: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3592: }
3593: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3594: }
3595: }
3596:
3597: for(i=1; i<= nlstate; i++){
3598: s1=0;
3599: for(j=1; j<i; j++){
3600: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3601: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3602: }
3603: for(j=i+1; j<=nlstate+ndeath; j++){
3604: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3605: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3606: }
3607: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3608: ps[i][i]=1./(s1+1.);
3609: /* Computing other pijs */
3610: for(j=1; j<i; j++)
3611: ps[i][j]= exp(ps[i][j])*ps[i][i];
3612: for(j=i+1; j<=nlstate+ndeath; j++)
3613: ps[i][j]= exp(ps[i][j])*ps[i][i];
3614: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3615: } /* end i */
3616:
3617: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3618: for(jj=1; jj<= nlstate+ndeath; jj++){
3619: ps[ii][jj]=0;
3620: ps[ii][ii]=1;
3621: }
3622: }
1.296 brouard 3623: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3624: for(jj=1; jj<= nlstate+ndeath; jj++){
3625: s1=0.;
3626: for(ii=1; ii<= nlstate+ndeath; ii++){
3627: s1+=ps[ii][jj];
3628: }
3629: for(ii=1; ii<= nlstate; ii++){
3630: ps[ii][jj]=ps[ii][jj]/s1;
3631: }
3632: }
3633: /* Transposition */
3634: for(jj=1; jj<= nlstate+ndeath; jj++){
3635: for(ii=jj; ii<= nlstate+ndeath; ii++){
3636: s1=ps[ii][jj];
3637: ps[ii][jj]=ps[jj][ii];
3638: ps[jj][ii]=s1;
3639: }
3640: }
3641: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3642: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3643: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3644: /* } */
3645: /* printf("\n "); */
3646: /* } */
3647: /* printf("\n ");printf("%lf ",cov[2]);*/
3648: /*
3649: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3650: goto end;*/
3651: return ps;
1.217 brouard 3652: }
3653:
3654:
1.126 brouard 3655: /**************** Product of 2 matrices ******************/
3656:
1.145 brouard 3657: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3658: {
3659: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3660: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3661: /* in, b, out are matrice of pointers which should have been initialized
3662: before: only the contents of out is modified. The function returns
3663: a pointer to pointers identical to out */
1.145 brouard 3664: int i, j, k;
1.126 brouard 3665: for(i=nrl; i<= nrh; i++)
1.145 brouard 3666: for(k=ncolol; k<=ncoloh; k++){
3667: out[i][k]=0.;
3668: for(j=ncl; j<=nch; j++)
3669: out[i][k] +=in[i][j]*b[j][k];
3670: }
1.126 brouard 3671: return out;
3672: }
3673:
3674:
3675: /************* Higher Matrix Product ***************/
3676:
1.235 brouard 3677: 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 3678: {
1.336 brouard 3679: /* Already optimized with precov.
3680: 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 3681: 'nhstepm*hstepm*stepm' months (i.e. until
3682: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3683: nhstepm*hstepm matrices.
3684: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3685: (typically every 2 years instead of every month which is too big
3686: for the memory).
3687: Model is determined by parameters x and covariates have to be
3688: included manually here.
3689:
3690: */
3691:
1.330 brouard 3692: int i, j, d, h, k, k1;
1.131 brouard 3693: double **out, cov[NCOVMAX+1];
1.126 brouard 3694: double **newm;
1.187 brouard 3695: double agexact;
1.214 brouard 3696: double agebegin, ageend;
1.126 brouard 3697:
3698: /* Hstepm could be zero and should return the unit matrix */
3699: for (i=1;i<=nlstate+ndeath;i++)
3700: for (j=1;j<=nlstate+ndeath;j++){
3701: oldm[i][j]=(i==j ? 1.0 : 0.0);
3702: po[i][j][0]=(i==j ? 1.0 : 0.0);
3703: }
3704: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3705: for(h=1; h <=nhstepm; h++){
3706: for(d=1; d <=hstepm; d++){
3707: newm=savm;
3708: /* Covariates have to be included here again */
3709: cov[1]=1.;
1.214 brouard 3710: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3711: cov[2]=agexact;
1.319 brouard 3712: if(nagesqr==1){
1.227 brouard 3713: cov[3]= agexact*agexact;
1.319 brouard 3714: }
1.330 brouard 3715: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3716: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3717: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3718: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3719: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3720: }else{
3721: cov[2+nagesqr+k1]=precov[nres][k1];
3722: }
3723: }/* End of loop on model equation */
3724: /* Old code */
3725: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3726: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3727: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3728: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3729: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3730: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3731: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3732: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3733: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3734: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3735: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3736: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3737: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3738: /* /\* 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]])); *\/ */
3739: /* 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); */
3740: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3741: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3742: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3743: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3744: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3745: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3746: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3747: /* 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]]); */
3748: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3749: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3750: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3751: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3752: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3753: /* 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]); */
3754: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3755:
3756: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3757: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3758: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3759: /* /\* *\/ */
1.330 brouard 3760: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3761: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3762: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3763: /* /\*cptcovage=2 1 2 *\/ */
3764: /* /\*Tage[k]= 5 8 *\/ */
3765: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3766: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3767: /* 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]]); */
3768: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3769: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3770: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3771: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3772: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3773: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3774: /* /\* 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); *\/ */
3775: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3776: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3777: /* /\* } *\/ */
3778: /* /\* 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]); *\/ */
3779: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3780: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3781: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3782: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3783: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3784: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3785: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3786: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3787: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3788:
1.332 brouard 3789: /* /\* 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])]); *\/ */
3790: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3791: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3792: /* 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]]); */
3793: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3794:
3795: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3796: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3797: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3798: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3799: /* /\* 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]])]; *\/ */
3800: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3801: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3802: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3803: /* /\* } *\/ */
3804: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3805: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3806: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3807: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3808: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3809: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3810: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3811: /* /\* } *\/ */
3812: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3813: /* }/\*end of products *\/ */
3814: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3815: /* for (k=1; k<=cptcovn;k++) */
3816: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3817: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3818: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3819: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3820: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3821:
3822:
1.126 brouard 3823: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3824: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3825: /* right multiplication of oldm by the current matrix */
1.126 brouard 3826: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3827: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3828: /* if((int)age == 70){ */
3829: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3830: /* for(i=1; i<=nlstate+ndeath; i++) { */
3831: /* printf("%d pmmij ",i); */
3832: /* for(j=1;j<=nlstate+ndeath;j++) { */
3833: /* printf("%f ",pmmij[i][j]); */
3834: /* } */
3835: /* printf(" oldm "); */
3836: /* for(j=1;j<=nlstate+ndeath;j++) { */
3837: /* printf("%f ",oldm[i][j]); */
3838: /* } */
3839: /* printf("\n"); */
3840: /* } */
3841: /* } */
1.126 brouard 3842: savm=oldm;
3843: oldm=newm;
3844: }
3845: for(i=1; i<=nlstate+ndeath; i++)
3846: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3847: po[i][j][h]=newm[i][j];
3848: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3849: }
1.128 brouard 3850: /*printf("h=%d ",h);*/
1.126 brouard 3851: } /* end h */
1.267 brouard 3852: /* printf("\n H=%d \n",h); */
1.126 brouard 3853: return po;
3854: }
3855:
1.217 brouard 3856: /************* Higher Back Matrix Product ***************/
1.218 brouard 3857: /* 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 3858: 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 3859: {
1.332 brouard 3860: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3861: computes the transition matrix starting at age 'age' over
1.217 brouard 3862: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3863: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3864: nhstepm*hstepm matrices.
3865: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3866: (typically every 2 years instead of every month which is too big
1.217 brouard 3867: for the memory).
1.218 brouard 3868: Model is determined by parameters x and covariates have to be
1.266 brouard 3869: included manually here. Then we use a call to bmij(x and cov)
3870: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3871: */
1.217 brouard 3872:
1.332 brouard 3873: int i, j, d, h, k, k1;
1.266 brouard 3874: double **out, cov[NCOVMAX+1], **bmij();
3875: double **newm, ***newmm;
1.217 brouard 3876: double agexact;
3877: double agebegin, ageend;
1.222 brouard 3878: double **oldm, **savm;
1.217 brouard 3879:
1.266 brouard 3880: newmm=po; /* To be saved */
3881: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3882: /* Hstepm could be zero and should return the unit matrix */
3883: for (i=1;i<=nlstate+ndeath;i++)
3884: for (j=1;j<=nlstate+ndeath;j++){
3885: oldm[i][j]=(i==j ? 1.0 : 0.0);
3886: po[i][j][0]=(i==j ? 1.0 : 0.0);
3887: }
3888: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3889: for(h=1; h <=nhstepm; h++){
3890: for(d=1; d <=hstepm; d++){
3891: newm=savm;
3892: /* Covariates have to be included here again */
3893: cov[1]=1.;
1.271 brouard 3894: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3895: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3896: /* Debug */
3897: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3898: cov[2]=agexact;
1.332 brouard 3899: if(nagesqr==1){
1.222 brouard 3900: cov[3]= agexact*agexact;
1.332 brouard 3901: }
3902: /** New code */
3903: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3904: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3905: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3906: }else{
1.332 brouard 3907: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3908: }
1.332 brouard 3909: }/* End of loop on model equation */
3910: /** End of new code */
3911: /** This was old code */
3912: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3913: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3914: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3915: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3916: /* /\* 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)); *\/ */
3917: /* } */
3918: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3919: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3920: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3921: /* /\* 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]); *\/ */
3922: /* } */
3923: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3924: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3925: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3926: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3927: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3928: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3929: /* } */
3930: /* /\* 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]); *\/ */
3931: /* } */
3932: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3933: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3934: /* if(Dummy[Tvard[k][1]]==0){ */
3935: /* if(Dummy[Tvard[k][2]]==0){ */
3936: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3937: /* }else{ */
3938: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3939: /* } */
3940: /* }else{ */
3941: /* if(Dummy[Tvard[k][2]]==0){ */
3942: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3943: /* }else{ */
3944: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3945: /* } */
3946: /* } */
3947: /* } */
3948: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3949: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3950: /** End of old code */
3951:
1.218 brouard 3952: /* Careful transposed matrix */
1.266 brouard 3953: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3954: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3955: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3956: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3957: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3958: /* if((int)age == 70){ */
3959: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3960: /* for(i=1; i<=nlstate+ndeath; i++) { */
3961: /* printf("%d pmmij ",i); */
3962: /* for(j=1;j<=nlstate+ndeath;j++) { */
3963: /* printf("%f ",pmmij[i][j]); */
3964: /* } */
3965: /* printf(" oldm "); */
3966: /* for(j=1;j<=nlstate+ndeath;j++) { */
3967: /* printf("%f ",oldm[i][j]); */
3968: /* } */
3969: /* printf("\n"); */
3970: /* } */
3971: /* } */
3972: savm=oldm;
3973: oldm=newm;
3974: }
3975: for(i=1; i<=nlstate+ndeath; i++)
3976: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3977: po[i][j][h]=newm[i][j];
1.268 brouard 3978: /* if(h==nhstepm) */
3979: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3980: }
1.268 brouard 3981: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3982: } /* end h */
1.268 brouard 3983: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3984: return po;
3985: }
3986:
3987:
1.162 brouard 3988: #ifdef NLOPT
3989: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3990: double fret;
3991: double *xt;
3992: int j;
3993: myfunc_data *d2 = (myfunc_data *) pd;
3994: /* xt = (p1-1); */
3995: xt=vector(1,n);
3996: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3997:
3998: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3999: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
4000: printf("Function = %.12lf ",fret);
4001: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
4002: printf("\n");
4003: free_vector(xt,1,n);
4004: return fret;
4005: }
4006: #endif
1.126 brouard 4007:
4008: /*************** log-likelihood *************/
4009: double func( double *x)
4010: {
1.336 brouard 4011: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 4012: int ioffset=0;
1.339 brouard 4013: int ipos=0,iposold=0,ncovv=0;
4014:
1.340 brouard 4015: double cotvarv, cotvarvold;
1.226 brouard 4016: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
4017: double **out;
4018: double lli; /* Individual log likelihood */
4019: int s1, s2;
1.228 brouard 4020: 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 4021:
1.226 brouard 4022: double bbh, survp;
4023: double agexact;
1.336 brouard 4024: double agebegin, ageend;
1.226 brouard 4025: /*extern weight */
4026: /* We are differentiating ll according to initial status */
4027: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4028: /*for(i=1;i<imx;i++)
4029: printf(" %d\n",s[4][i]);
4030: */
1.162 brouard 4031:
1.226 brouard 4032: ++countcallfunc;
1.162 brouard 4033:
1.226 brouard 4034: cov[1]=1.;
1.126 brouard 4035:
1.226 brouard 4036: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4037: ioffset=0;
1.226 brouard 4038: if(mle==1){
4039: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4040: /* Computes the values of the ncovmodel covariates of the model
4041: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4042: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4043: to be observed in j being in i according to the model.
4044: */
1.243 brouard 4045: ioffset=2+nagesqr ;
1.233 brouard 4046: /* Fixed */
1.345 brouard 4047: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4048: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4049: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4050: /* 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 4051: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4052: 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 4053: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4054: }
1.226 brouard 4055: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4056: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4057: has been calculated etc */
4058: /* For an individual i, wav[i] gives the number of effective waves */
4059: /* We compute the contribution to Likelihood of each effective transition
4060: mw[mi][i] is real wave of the mi th effectve wave */
4061: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4062: s2=s[mw[mi+1][i]][i];
1.341 brouard 4063: 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 4064: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4065: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4066: */
1.336 brouard 4067: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4068: /* Wave varying (but not age varying) */
1.339 brouard 4069: /* 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*\/ */
4070: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4071: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4072: /* } */
1.340 brouard 4073: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4074: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4075: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4076: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4077: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4078: }else{ /* fixed covariate */
1.345 brouard 4079: 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 4080: }
1.339 brouard 4081: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4082: cotvarvold=cotvarv;
4083: }else{ /* A second product */
4084: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4085: }
4086: iposold=ipos;
1.340 brouard 4087: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4088: }
1.339 brouard 4089: /* for products of time varying to be done */
1.234 brouard 4090: for (ii=1;ii<=nlstate+ndeath;ii++)
4091: for (j=1;j<=nlstate+ndeath;j++){
4092: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4093: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4094: }
1.336 brouard 4095:
4096: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4097: 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 4098: for(d=0; d<dh[mi][i]; d++){
4099: newm=savm;
4100: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4101: cov[2]=agexact;
4102: if(nagesqr==1)
4103: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 4104: /* for (kk=1; kk<=cptcovage;kk++) { */
4105: /* if(!FixedV[Tvar[Tage[kk]]]) */
4106: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
4107: /* else */
4108: /* 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) *\/ */
4109: /* } */
4110: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4111: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4112: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4113: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4114: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4115: }else{ /* fixed covariate */
4116: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4117: }
4118: if(ipos!=iposold){ /* Not a product or first of a product */
4119: cotvarvold=cotvarv;
4120: }else{ /* A second product */
4121: cotvarv=cotvarv*cotvarvold;
4122: }
4123: iposold=ipos;
4124: cov[ioffset+ipos]=cotvarv*agexact;
4125: /* For products */
1.234 brouard 4126: }
1.349 brouard 4127:
1.234 brouard 4128: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4129: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4130: savm=oldm;
4131: oldm=newm;
4132: } /* end mult */
4133:
4134: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4135: /* But now since version 0.9 we anticipate for bias at large stepm.
4136: * If stepm is larger than one month (smallest stepm) and if the exact delay
4137: * (in months) between two waves is not a multiple of stepm, we rounded to
4138: * the nearest (and in case of equal distance, to the lowest) interval but now
4139: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4140: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4141: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4142: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4143: * -stepm/2 to stepm/2 .
4144: * For stepm=1 the results are the same as for previous versions of Imach.
4145: * For stepm > 1 the results are less biased than in previous versions.
4146: */
1.234 brouard 4147: s1=s[mw[mi][i]][i];
4148: s2=s[mw[mi+1][i]][i];
4149: bbh=(double)bh[mi][i]/(double)stepm;
4150: /* bias bh is positive if real duration
4151: * is higher than the multiple of stepm and negative otherwise.
4152: */
4153: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4154: if( s2 > nlstate){
4155: /* i.e. if s2 is a death state and if the date of death is known
4156: then the contribution to the likelihood is the probability to
4157: die between last step unit time and current step unit time,
4158: which is also equal to probability to die before dh
4159: minus probability to die before dh-stepm .
4160: In version up to 0.92 likelihood was computed
4161: as if date of death was unknown. Death was treated as any other
4162: health state: the date of the interview describes the actual state
4163: and not the date of a change in health state. The former idea was
4164: to consider that at each interview the state was recorded
4165: (healthy, disable or death) and IMaCh was corrected; but when we
4166: introduced the exact date of death then we should have modified
4167: the contribution of an exact death to the likelihood. This new
4168: contribution is smaller and very dependent of the step unit
4169: stepm. It is no more the probability to die between last interview
4170: and month of death but the probability to survive from last
4171: interview up to one month before death multiplied by the
4172: probability to die within a month. Thanks to Chris
4173: Jackson for correcting this bug. Former versions increased
4174: mortality artificially. The bad side is that we add another loop
4175: which slows down the processing. The difference can be up to 10%
4176: lower mortality.
4177: */
4178: /* If, at the beginning of the maximization mostly, the
4179: cumulative probability or probability to be dead is
4180: constant (ie = 1) over time d, the difference is equal to
4181: 0. out[s1][3] = savm[s1][3]: probability, being at state
4182: s1 at precedent wave, to be dead a month before current
4183: wave is equal to probability, being at state s1 at
4184: precedent wave, to be dead at mont of the current
4185: wave. Then the observed probability (that this person died)
4186: is null according to current estimated parameter. In fact,
4187: it should be very low but not zero otherwise the log go to
4188: infinity.
4189: */
1.183 brouard 4190: /* #ifdef INFINITYORIGINAL */
4191: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4192: /* #else */
4193: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4194: /* lli=log(mytinydouble); */
4195: /* else */
4196: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4197: /* #endif */
1.226 brouard 4198: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4199:
1.226 brouard 4200: } else if ( s2==-1 ) { /* alive */
4201: for (j=1,survp=0. ; j<=nlstate; j++)
4202: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4203: /*survp += out[s1][j]; */
4204: lli= log(survp);
4205: }
1.336 brouard 4206: /* else if (s2==-4) { */
4207: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4208: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4209: /* lli= log(survp); */
4210: /* } */
4211: /* else if (s2==-5) { */
4212: /* for (j=1,survp=0. ; j<=2; j++) */
4213: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4214: /* lli= log(survp); */
4215: /* } */
1.226 brouard 4216: else{
4217: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4218: /* 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 */
4219: }
4220: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4221: /*if(lli ==000.0)*/
1.340 brouard 4222: /* 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 4223: ipmx +=1;
4224: sw += weight[i];
4225: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4226: /* if (lli < log(mytinydouble)){ */
4227: /* 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); */
4228: /* 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]); */
4229: /* } */
4230: } /* end of wave */
4231: } /* end of individual */
4232: } else if(mle==2){
4233: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4234: ioffset=2+nagesqr ;
4235: for (k=1; k<=ncovf;k++)
4236: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4237: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4238: for(k=1; k <= ncovv ; k++){
1.341 brouard 4239: 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 4240: }
1.226 brouard 4241: for (ii=1;ii<=nlstate+ndeath;ii++)
4242: for (j=1;j<=nlstate+ndeath;j++){
4243: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4244: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4245: }
4246: for(d=0; d<=dh[mi][i]; d++){
4247: newm=savm;
4248: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4249: cov[2]=agexact;
4250: if(nagesqr==1)
4251: cov[3]= agexact*agexact;
4252: for (kk=1; kk<=cptcovage;kk++) {
4253: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4254: }
4255: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4256: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4257: savm=oldm;
4258: oldm=newm;
4259: } /* end mult */
4260:
4261: s1=s[mw[mi][i]][i];
4262: s2=s[mw[mi+1][i]][i];
4263: bbh=(double)bh[mi][i]/(double)stepm;
4264: 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 */
4265: ipmx +=1;
4266: sw += weight[i];
4267: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4268: } /* end of wave */
4269: } /* end of individual */
4270: } else if(mle==3){ /* exponential inter-extrapolation */
4271: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4272: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4273: for(mi=1; mi<= wav[i]-1; mi++){
4274: for (ii=1;ii<=nlstate+ndeath;ii++)
4275: for (j=1;j<=nlstate+ndeath;j++){
4276: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4277: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4278: }
4279: for(d=0; d<dh[mi][i]; d++){
4280: newm=savm;
4281: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4282: cov[2]=agexact;
4283: if(nagesqr==1)
4284: cov[3]= agexact*agexact;
4285: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4286: if(!FixedV[Tvar[Tage[kk]]])
4287: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4288: else
1.341 brouard 4289: 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 4290: }
4291: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4292: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4293: savm=oldm;
4294: oldm=newm;
4295: } /* end mult */
4296:
4297: s1=s[mw[mi][i]][i];
4298: s2=s[mw[mi+1][i]][i];
4299: bbh=(double)bh[mi][i]/(double)stepm;
4300: 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 */
4301: ipmx +=1;
4302: sw += weight[i];
4303: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4304: } /* end of wave */
4305: } /* end of individual */
4306: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4307: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4308: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4309: for(mi=1; mi<= wav[i]-1; mi++){
4310: for (ii=1;ii<=nlstate+ndeath;ii++)
4311: for (j=1;j<=nlstate+ndeath;j++){
4312: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4313: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4314: }
4315: for(d=0; d<dh[mi][i]; d++){
4316: newm=savm;
4317: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4318: cov[2]=agexact;
4319: if(nagesqr==1)
4320: cov[3]= agexact*agexact;
4321: for (kk=1; kk<=cptcovage;kk++) {
4322: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4323: }
1.126 brouard 4324:
1.226 brouard 4325: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4326: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4327: savm=oldm;
4328: oldm=newm;
4329: } /* end mult */
4330:
4331: s1=s[mw[mi][i]][i];
4332: s2=s[mw[mi+1][i]][i];
4333: if( s2 > nlstate){
4334: lli=log(out[s1][s2] - savm[s1][s2]);
4335: } else if ( s2==-1 ) { /* alive */
4336: for (j=1,survp=0. ; j<=nlstate; j++)
4337: survp += out[s1][j];
4338: lli= log(survp);
4339: }else{
4340: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4341: }
4342: ipmx +=1;
4343: sw += weight[i];
4344: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4345: /* 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 4346: } /* end of wave */
4347: } /* end of individual */
4348: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4349: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4350: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4351: for(mi=1; mi<= wav[i]-1; mi++){
4352: for (ii=1;ii<=nlstate+ndeath;ii++)
4353: for (j=1;j<=nlstate+ndeath;j++){
4354: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4355: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4356: }
4357: for(d=0; d<dh[mi][i]; d++){
4358: newm=savm;
4359: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4360: cov[2]=agexact;
4361: if(nagesqr==1)
4362: cov[3]= agexact*agexact;
4363: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4364: if(!FixedV[Tvar[Tage[kk]]])
4365: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4366: else
1.341 brouard 4367: 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 4368: }
1.126 brouard 4369:
1.226 brouard 4370: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4371: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4372: savm=oldm;
4373: oldm=newm;
4374: } /* end mult */
4375:
4376: s1=s[mw[mi][i]][i];
4377: s2=s[mw[mi+1][i]][i];
4378: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4379: ipmx +=1;
4380: sw += weight[i];
4381: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4382: /*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]);*/
4383: } /* end of wave */
4384: } /* end of individual */
4385: } /* End of if */
4386: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4387: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4388: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4389: return -l;
1.126 brouard 4390: }
4391:
4392: /*************** log-likelihood *************/
4393: double funcone( double *x)
4394: {
1.228 brouard 4395: /* Same as func but slower because of a lot of printf and if */
1.349 brouard 4396: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4397: int ioffset=0;
1.339 brouard 4398: int ipos=0,iposold=0,ncovv=0;
4399:
1.340 brouard 4400: double cotvarv, cotvarvold;
1.131 brouard 4401: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4402: double **out;
4403: double lli; /* Individual log likelihood */
4404: double llt;
4405: int s1, s2;
1.228 brouard 4406: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4407:
1.126 brouard 4408: double bbh, survp;
1.187 brouard 4409: double agexact;
1.214 brouard 4410: double agebegin, ageend;
1.126 brouard 4411: /*extern weight */
4412: /* We are differentiating ll according to initial status */
4413: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4414: /*for(i=1;i<imx;i++)
4415: printf(" %d\n",s[4][i]);
4416: */
4417: cov[1]=1.;
4418:
4419: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4420: ioffset=0;
4421: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4422: /* Computes the values of the ncovmodel covariates of the model
4423: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4424: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4425: to be observed in j being in i according to the model.
4426: */
1.243 brouard 4427: /* ioffset=2+nagesqr+cptcovage; */
4428: ioffset=2+nagesqr;
1.232 brouard 4429: /* Fixed */
1.224 brouard 4430: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4431: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 4432: 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 4433: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4434: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4435: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4436: 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 4437: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4438: /* cov[2+6]=covar[Tvar[6]][i]; */
4439: /* cov[2+6]=covar[2][i]; V2 */
4440: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4441: /* cov[2+7]=covar[Tvar[7]][i]; */
4442: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4443: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4444: /* cov[2+9]=covar[Tvar[9]][i]; */
4445: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4446: }
1.336 brouard 4447: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4448: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4449: has been calculated etc */
4450: /* For an individual i, wav[i] gives the number of effective waves */
4451: /* We compute the contribution to Likelihood of each effective transition
4452: mw[mi][i] is real wave of the mi th effectve wave */
4453: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4454: s2=s[mw[mi+1][i]][i];
1.341 brouard 4455: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4456: */
4457: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4458: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4459: /* 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?)*\/ */
4460: /* } */
1.231 brouard 4461: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4462: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4463: /* } */
1.225 brouard 4464:
1.233 brouard 4465:
4466: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4467: /* 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 */
4468: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4469: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4470: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4471: /* } */
4472:
4473: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4474: /* model V1+V3+age*V1+age*V3+V1*V3 */
4475: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4476: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4477: /* We need the position of the time varying or product in the model */
4478: /* 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 */
4479: /* TvarVV gives the variable name */
1.340 brouard 4480: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4481: * k= 1 2 3 4 5 6 7 8 9
4482: * varying 1 2 3 4 5
4483: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4484: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4485: * TvarVVind 2 3 7 7 8 8 9 9
4486: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4487: */
1.345 brouard 4488: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 4489: * 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 4490: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 4491: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4492: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
4493: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
4494: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4495: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4496: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4497: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4498: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4499: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4500: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4501: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4502: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4503: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4504: * 12 13 14 15 16
4505: * 17 18 19 20 21
4506: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
4507: * 2 3 4 6 7
4508: * 9 11 12 13 14
4509: * cptcovage=5+5 total of covariates with age
4510: * Tage[cptcovage] age*V2=12 13 14 15 16
4511: *1 17 18 19 20 21 gives the position in model of covariates associated with age
4512: *3 Tage[cptcovage] age*V3*V2=6
4513: *3 age*V2=12 13 14 15 16
4514: *3 age*V6*V3=18 19 20 21
4515: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4516: * 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
4517: * 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
4518: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4519: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4520: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
4521: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
4522: * 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
4523: * Tvar= {2, 3, 4, 6, 7,
4524: * 9, 10, 11, 12, 13, 14,
4525: * Tvar[12]=2, 3, 4, 6, 7,
4526: * Tvar[17]=9, 11, 12, 13, 14}
4527: * Typevar[1]@21 = {0, 0, 0, 0, 0,
4528: * 2, 2, 2, 2, 2, 2,
4529: * 3 3, 2, 2, 2, 2, 2,
4530: * 1, 1, 1, 1, 1,
4531: * 3, 3, 3, 3, 3}
4532: * 3 2, 3, 3, 3, 3}
4533: * 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
4534: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4535: * 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}
4536: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4537: * cptcovprod=11 (6+5)
4538: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
4539: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
4540: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
4541: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
4542: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4543: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4544: * cptcovdageprod=5 for gnuplot printing
4545: * cptcovprodvage=6
4546: * ncova=15 1 2 3 4 5
4547: * 6 7 8 9 10 11 12 13 14 15
4548: * TvarA 2 3 4 6 7
4549: * 6 2 6 7 7 3 6 4 7 4
4550: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4551: * ncovf 1 2 3
1.349 brouard 4552: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4553: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4554: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4555: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4556: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4557: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4558: * 3 1 2 3 4 5 6 7 8 9 10 11 12
4559: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
4560: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
4561: * 3 cptcovprodvage=6
4562: * 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
4563: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
4564: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.354 brouard 4565: *?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 4566: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
4567: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4568: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
4569: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
4570: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
4571: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
4572: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
4573: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4574: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 4575: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
4576: * 2, 3, 4, 6, 7,
4577: * 6, 8, 9, 10, 11}
1.345 brouard 4578: * TvarFind[itv] 0 0 0
4579: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
1.354 brouard 4580: *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0
1.345 brouard 4581: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4582: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4583: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 4584: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4585: */
4586:
1.349 brouard 4587: 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 */
4588: 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 4589: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4590: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4591: 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 4592: /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.345 brouard 4593: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.354 brouard 4594: /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4595: }else{ /* fixed covariate */
1.345 brouard 4596: /* 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 4597: /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.349 brouard 4598: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.354 brouard 4599: /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4600: }
1.339 brouard 4601: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4602: cotvarvold=cotvarv;
4603: }else{ /* A second product */
4604: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4605: }
4606: iposold=ipos;
1.340 brouard 4607: cov[ioffset+ipos]=cotvarv;
1.354 brouard 4608: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
1.339 brouard 4609: /* For products */
4610: }
4611: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4612: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4613: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4614: /* /\* 1 2 3 4 5 *\/ */
4615: /* /\*itv 1 *\/ */
4616: /* /\* TvarVInd[1]= 2 *\/ */
4617: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4618: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4619: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4620: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4621: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4622: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4623: /* /\* 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]); *\/ */
4624: /* } */
1.232 brouard 4625: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4626: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4627: /* /\* 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]); *\/ */
4628: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4629: /* } */
1.126 brouard 4630: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4631: for (j=1;j<=nlstate+ndeath;j++){
4632: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4633: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4634: }
1.214 brouard 4635:
4636: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4637: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4638: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4639: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4640: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4641: and mw[mi+1][i]. dh depends on stepm.*/
4642: newm=savm;
1.247 brouard 4643: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4644: cov[2]=agexact;
4645: if(nagesqr==1)
4646: cov[3]= agexact*agexact;
1.349 brouard 4647: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4648: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4649: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4650: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4651: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4652: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4653: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4654: }else{ /* fixed covariate */
4655: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4656: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4657: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4658: }
4659: if(ipos!=iposold){ /* Not a product or first of a product */
4660: cotvarvold=cotvarv;
4661: }else{ /* A second product */
4662: /* printf("DEBUG * \n"); */
4663: cotvarv=cotvarv*cotvarvold;
4664: }
4665: iposold=ipos;
4666: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4667: cov[ioffset+ipos]=cotvarv*agexact;
4668: /* For products */
1.242 brouard 4669: }
1.349 brouard 4670:
1.242 brouard 4671: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4672: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4673: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4674: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4675: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4676: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4677: savm=oldm;
4678: oldm=newm;
1.126 brouard 4679: } /* end mult */
1.336 brouard 4680: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4681: /* But now since version 0.9 we anticipate for bias at large stepm.
4682: * If stepm is larger than one month (smallest stepm) and if the exact delay
4683: * (in months) between two waves is not a multiple of stepm, we rounded to
4684: * the nearest (and in case of equal distance, to the lowest) interval but now
4685: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4686: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4687: * probability in order to take into account the bias as a fraction of the way
4688: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4689: * -stepm/2 to stepm/2 .
4690: * For stepm=1 the results are the same as for previous versions of Imach.
4691: * For stepm > 1 the results are less biased than in previous versions.
4692: */
1.126 brouard 4693: s1=s[mw[mi][i]][i];
4694: s2=s[mw[mi+1][i]][i];
1.217 brouard 4695: /* if(s2==-1){ */
1.268 brouard 4696: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4697: /* /\* exit(1); *\/ */
4698: /* } */
1.126 brouard 4699: bbh=(double)bh[mi][i]/(double)stepm;
4700: /* bias is positive if real duration
4701: * is higher than the multiple of stepm and negative otherwise.
4702: */
4703: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4704: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4705: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4706: for (j=1,survp=0. ; j<=nlstate; j++)
4707: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4708: lli= log(survp);
1.126 brouard 4709: }else if (mle==1){
1.242 brouard 4710: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4711: } else if(mle==2){
1.242 brouard 4712: 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 4713: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4714: 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 4715: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4716: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4717: } else{ /* mle=0 back to 1 */
1.242 brouard 4718: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4719: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4720: } /* End of if */
4721: ipmx +=1;
4722: sw += weight[i];
4723: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4724: /* Printing covariates values for each contribution for checking */
1.343 brouard 4725: /* 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 4726: if(globpr){
1.246 brouard 4727: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4728: %11.6f %11.6f %11.6f ", \
1.242 brouard 4729: 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 4730: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4731: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4732: /* %11.6f %11.6f %11.6f ", \ */
4733: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4734: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4735: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4736: llt +=ll[k]*gipmx/gsw;
4737: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4738: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4739: }
1.343 brouard 4740: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4741: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4742: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4743: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4744: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4745: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4746: }
4747: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4748: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4749: if(ipos!=iposold){ /* Not a product or first of a product */
4750: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4751: /* printf(" %g",cov[ioffset+ipos]); */
4752: }else{
4753: fprintf(ficresilk,"*");
4754: /* printf("*"); */
1.342 brouard 4755: }
1.343 brouard 4756: iposold=ipos;
4757: }
1.349 brouard 4758: /* for (kk=1; kk<=cptcovage;kk++) { */
4759: /* if(!FixedV[Tvar[Tage[kk]]]){ */
4760: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
4761: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
4762: /* }else{ */
4763: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4764: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
4765: /* } */
4766: /* } */
4767: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4768: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4769: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4770: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4771: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4772: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4773: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4774: }else{ /* fixed covariate */
4775: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4776: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4777: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4778: }
4779: if(ipos!=iposold){ /* Not a product or first of a product */
4780: cotvarvold=cotvarv;
4781: }else{ /* A second product */
4782: /* printf("DEBUG * \n"); */
4783: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4784: }
1.349 brouard 4785: cotvarv=cotvarv*agexact;
4786: fprintf(ficresilk," %g*age",cotvarv);
4787: iposold=ipos;
4788: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4789: cov[ioffset+ipos]=cotvarv;
4790: /* For products */
1.343 brouard 4791: }
4792: /* printf("\n"); */
1.342 brouard 4793: /* } /\* End debugILK *\/ */
4794: fprintf(ficresilk,"\n");
4795: } /* End if globpr */
1.335 brouard 4796: } /* end of wave */
4797: } /* end of individual */
4798: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4799: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4800: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4801: if(globpr==0){ /* First time we count the contributions and weights */
4802: gipmx=ipmx;
4803: gsw=sw;
4804: }
1.343 brouard 4805: return -l;
1.126 brouard 4806: }
4807:
4808:
4809: /*************** function likelione ***********/
1.292 brouard 4810: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4811: {
4812: /* This routine should help understanding what is done with
4813: the selection of individuals/waves and
4814: to check the exact contribution to the likelihood.
4815: Plotting could be done.
1.342 brouard 4816: */
4817: void pstamp(FILE *ficres);
1.343 brouard 4818: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4819:
4820: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4821: strcpy(fileresilk,"ILK_");
1.202 brouard 4822: strcat(fileresilk,fileresu);
1.126 brouard 4823: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4824: printf("Problem with resultfile: %s\n", fileresilk);
4825: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4826: }
1.342 brouard 4827: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4828: 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");
4829: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4830: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4831: for(k=1; k<=nlstate; k++)
4832: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4833: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4834:
4835: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4836: for(kf=1;kf <= ncovf; kf++){
4837: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4838: /* printf("V%d",Tvar[TvarFind[kf]]); */
4839: }
4840: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4841: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4842: if(ipos!=iposold){ /* Not a product or first of a product */
4843: /* printf(" %d",ipos); */
4844: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4845: }else{
4846: /* printf("*"); */
4847: fprintf(ficresilk,"*");
1.343 brouard 4848: }
1.342 brouard 4849: iposold=ipos;
4850: }
4851: for (kk=1; kk<=cptcovage;kk++) {
4852: if(!FixedV[Tvar[Tage[kk]]]){
4853: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4854: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4855: }else{
4856: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4857: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4858: }
4859: }
4860: /* } /\* End if debugILK *\/ */
4861: /* printf("\n"); */
4862: fprintf(ficresilk,"\n");
4863: } /* End glogpri */
1.126 brouard 4864:
1.292 brouard 4865: *fretone=(*func)(p);
1.126 brouard 4866: if(*globpri !=0){
4867: fclose(ficresilk);
1.205 brouard 4868: if (mle ==0)
4869: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4870: else if(mle >=1)
4871: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4872: 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 4873: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4874:
1.207 brouard 4875: 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 4876: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4877: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4878: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4879:
4880: for (k=1; k<= nlstate ; k++) {
4881: 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 \
4882: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4883: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 4884: kvar=Tvar[TvarFind[kf]]; /* variable */
4885: 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]]);
4886: 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);
4887: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 4888: }
4889: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4890: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4891: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4892: /* 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]); */
4893: if(ipos!=iposold){ /* Not a product or first of a product */
4894: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4895: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4896: 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) */
4897: 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> \
4898: <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);
4899: } /* End only for dummies time varying (single?) */
4900: }else{ /* Useless product */
4901: /* printf("*"); */
4902: /* fprintf(ficresilk,"*"); */
4903: }
4904: iposold=ipos;
4905: } /* For each time varying covariate */
4906: } /* End loop on states */
4907:
4908: /* if(debugILK){ */
4909: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4910: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4911: /* for (k=1; k<= nlstate ; k++) { */
4912: /* 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> \ */
4913: /* <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]]); */
4914: /* } */
4915: /* } */
4916: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4917: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4918: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4919: /* /\* 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]); *\/ */
4920: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4921: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4922: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4923: /* 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) *\/ */
4924: /* for (k=1; k<= nlstate ; k++) { */
4925: /* 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> \ */
4926: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4927: /* } /\* End state *\/ */
4928: /* } /\* End only for dummies time varying (single?) *\/ */
4929: /* }else{ /\* Useless product *\/ */
4930: /* /\* printf("*"); *\/ */
4931: /* /\* fprintf(ficresilk,"*"); *\/ */
4932: /* } */
4933: /* iposold=ipos; */
4934: /* } /\* For each time varying covariate *\/ */
4935: /* }/\* End debugILK *\/ */
1.207 brouard 4936: fflush(fichtm);
1.343 brouard 4937: }/* End globpri */
1.126 brouard 4938: return;
4939: }
4940:
4941:
4942: /*********** Maximum Likelihood Estimation ***************/
4943:
4944: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4945: {
1.319 brouard 4946: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4947: double **xi;
4948: double fret;
4949: double fretone; /* Only one call to likelihood */
4950: /* char filerespow[FILENAMELENGTH];*/
1.354 brouard 4951:
4952: double * p1; /* Shifted parameters from 0 instead of 1 */
1.162 brouard 4953: #ifdef NLOPT
4954: int creturn;
4955: nlopt_opt opt;
4956: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4957: double *lb;
4958: double minf; /* the minimum objective value, upon return */
1.354 brouard 4959:
1.162 brouard 4960: myfunc_data dinst, *d = &dinst;
4961: #endif
4962:
4963:
1.126 brouard 4964: xi=matrix(1,npar,1,npar);
4965: for (i=1;i<=npar;i++)
4966: for (j=1;j<=npar;j++)
4967: xi[i][j]=(i==j ? 1.0 : 0.0);
4968: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4969: strcpy(filerespow,"POW_");
1.126 brouard 4970: strcat(filerespow,fileres);
4971: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4972: printf("Problem with resultfile: %s\n", filerespow);
4973: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4974: }
4975: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4976: for (i=1;i<=nlstate;i++)
4977: for(j=1;j<=nlstate+ndeath;j++)
4978: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4979: fprintf(ficrespow,"\n");
1.162 brouard 4980: #ifdef POWELL
1.319 brouard 4981: #ifdef LINMINORIGINAL
4982: #else /* LINMINORIGINAL */
4983:
4984: flatdir=ivector(1,npar);
4985: for (j=1;j<=npar;j++) flatdir[j]=0;
4986: #endif /*LINMINORIGINAL */
4987:
4988: #ifdef FLATSUP
4989: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4990: /* reorganizing p by suppressing flat directions */
4991: for(i=1, jk=1; i <=nlstate; i++){
4992: for(k=1; k <=(nlstate+ndeath); k++){
4993: if (k != i) {
4994: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4995: if(flatdir[jk]==1){
4996: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4997: }
4998: for(j=1; j <=ncovmodel; j++){
4999: printf("%12.7f ",p[jk]);
5000: jk++;
5001: }
5002: printf("\n");
5003: }
5004: }
5005: }
5006: /* skipping */
5007: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
5008: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
5009: for(k=1; k <=(nlstate+ndeath); k++){
5010: if (k != i) {
5011: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
5012: if(flatdir[jk]==1){
5013: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
5014: for(j=1; j <=ncovmodel; jk++,j++){
5015: printf(" p[%d]=%12.7f",jk, p[jk]);
5016: /*q[jjk]=p[jk];*/
5017: }
5018: }else{
5019: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
5020: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
5021: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
5022: /*q[jjk]=p[jk];*/
5023: }
5024: }
5025: printf("\n");
5026: }
5027: fflush(stdout);
5028: }
5029: }
5030: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5031: #else /* FLATSUP */
1.126 brouard 5032: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 5033: #endif /* FLATSUP */
5034:
5035: #ifdef LINMINORIGINAL
5036: #else
5037: free_ivector(flatdir,1,npar);
5038: #endif /* LINMINORIGINAL*/
5039: #endif /* POWELL */
1.126 brouard 5040:
1.162 brouard 5041: #ifdef NLOPT
5042: #ifdef NEWUOA
5043: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
5044: #else
5045: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
5046: #endif
5047: lb=vector(0,npar-1);
5048: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
5049: nlopt_set_lower_bounds(opt, lb);
5050: nlopt_set_initial_step1(opt, 0.1);
5051:
5052: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5053: d->function = func;
5054: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5055: nlopt_set_min_objective(opt, myfunc, d);
5056: nlopt_set_xtol_rel(opt, ftol);
5057: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5058: printf("nlopt failed! %d\n",creturn);
5059: }
5060: else {
5061: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5062: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5063: iter=1; /* not equal */
5064: }
5065: nlopt_destroy(opt);
5066: #endif
1.319 brouard 5067: #ifdef FLATSUP
5068: /* npared = npar -flatd/ncovmodel; */
5069: /* xired= matrix(1,npared,1,npared); */
5070: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5071: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5072: /* free_matrix(xire,1,npared,1,npared); */
5073: #else /* FLATSUP */
5074: #endif /* FLATSUP */
1.126 brouard 5075: free_matrix(xi,1,npar,1,npar);
5076: fclose(ficrespow);
1.203 brouard 5077: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5078: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5079: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5080:
5081: }
5082:
5083: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5084: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5085: {
5086: double **a,**y,*x,pd;
1.203 brouard 5087: /* double **hess; */
1.164 brouard 5088: int i, j;
1.126 brouard 5089: int *indx;
5090:
5091: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5092: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5093: void lubksb(double **a, int npar, int *indx, double b[]) ;
5094: void ludcmp(double **a, int npar, int *indx, double *d) ;
5095: double gompertz(double p[]);
1.203 brouard 5096: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5097:
5098: printf("\nCalculation of the hessian matrix. Wait...\n");
5099: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5100: for (i=1;i<=npar;i++){
1.203 brouard 5101: printf("%d-",i);fflush(stdout);
5102: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5103:
5104: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5105:
5106: /* printf(" %f ",p[i]);
5107: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5108: }
5109:
5110: for (i=1;i<=npar;i++) {
5111: for (j=1;j<=npar;j++) {
5112: if (j>i) {
1.203 brouard 5113: printf(".%d-%d",i,j);fflush(stdout);
5114: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5115: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5116:
5117: hess[j][i]=hess[i][j];
5118: /*printf(" %lf ",hess[i][j]);*/
5119: }
5120: }
5121: }
5122: printf("\n");
5123: fprintf(ficlog,"\n");
5124:
5125: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5126: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5127:
5128: a=matrix(1,npar,1,npar);
5129: y=matrix(1,npar,1,npar);
5130: x=vector(1,npar);
5131: indx=ivector(1,npar);
5132: for (i=1;i<=npar;i++)
5133: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5134: ludcmp(a,npar,indx,&pd);
5135:
5136: for (j=1;j<=npar;j++) {
5137: for (i=1;i<=npar;i++) x[i]=0;
5138: x[j]=1;
5139: lubksb(a,npar,indx,x);
5140: for (i=1;i<=npar;i++){
5141: matcov[i][j]=x[i];
5142: }
5143: }
5144:
5145: printf("\n#Hessian matrix#\n");
5146: fprintf(ficlog,"\n#Hessian matrix#\n");
5147: for (i=1;i<=npar;i++) {
5148: for (j=1;j<=npar;j++) {
1.203 brouard 5149: printf("%.6e ",hess[i][j]);
5150: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5151: }
5152: printf("\n");
5153: fprintf(ficlog,"\n");
5154: }
5155:
1.203 brouard 5156: /* printf("\n#Covariance matrix#\n"); */
5157: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5158: /* for (i=1;i<=npar;i++) { */
5159: /* for (j=1;j<=npar;j++) { */
5160: /* printf("%.6e ",matcov[i][j]); */
5161: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5162: /* } */
5163: /* printf("\n"); */
5164: /* fprintf(ficlog,"\n"); */
5165: /* } */
5166:
1.126 brouard 5167: /* Recompute Inverse */
1.203 brouard 5168: /* for (i=1;i<=npar;i++) */
5169: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5170: /* ludcmp(a,npar,indx,&pd); */
5171:
5172: /* printf("\n#Hessian matrix recomputed#\n"); */
5173:
5174: /* for (j=1;j<=npar;j++) { */
5175: /* for (i=1;i<=npar;i++) x[i]=0; */
5176: /* x[j]=1; */
5177: /* lubksb(a,npar,indx,x); */
5178: /* for (i=1;i<=npar;i++){ */
5179: /* y[i][j]=x[i]; */
5180: /* printf("%.3e ",y[i][j]); */
5181: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5182: /* } */
5183: /* printf("\n"); */
5184: /* fprintf(ficlog,"\n"); */
5185: /* } */
5186:
5187: /* Verifying the inverse matrix */
5188: #ifdef DEBUGHESS
5189: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5190:
1.203 brouard 5191: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5192: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5193:
5194: for (j=1;j<=npar;j++) {
5195: for (i=1;i<=npar;i++){
1.203 brouard 5196: printf("%.2f ",y[i][j]);
5197: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5198: }
5199: printf("\n");
5200: fprintf(ficlog,"\n");
5201: }
1.203 brouard 5202: #endif
1.126 brouard 5203:
5204: free_matrix(a,1,npar,1,npar);
5205: free_matrix(y,1,npar,1,npar);
5206: free_vector(x,1,npar);
5207: free_ivector(indx,1,npar);
1.203 brouard 5208: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5209:
5210:
5211: }
5212:
5213: /*************** hessian matrix ****************/
5214: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5215: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5216: int i;
5217: int l=1, lmax=20;
1.203 brouard 5218: double k1,k2, res, fx;
1.132 brouard 5219: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5220: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5221: int k=0,kmax=10;
5222: double l1;
5223:
5224: fx=func(x);
5225: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5226: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5227: l1=pow(10,l);
5228: delts=delt;
5229: for(k=1 ; k <kmax; k=k+1){
5230: delt = delta*(l1*k);
5231: p2[theta]=x[theta] +delt;
1.145 brouard 5232: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5233: p2[theta]=x[theta]-delt;
5234: k2=func(p2)-fx;
5235: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5236: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5237:
1.203 brouard 5238: #ifdef DEBUGHESSII
1.126 brouard 5239: 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);
5240: 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);
5241: #endif
5242: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5243: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5244: k=kmax;
5245: }
5246: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5247: k=kmax; l=lmax*10;
1.126 brouard 5248: }
5249: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5250: delts=delt;
5251: }
1.203 brouard 5252: } /* End loop k */
1.126 brouard 5253: }
5254: delti[theta]=delts;
5255: return res;
5256:
5257: }
5258:
1.203 brouard 5259: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5260: {
5261: int i;
1.164 brouard 5262: int l=1, lmax=20;
1.126 brouard 5263: double k1,k2,k3,k4,res,fx;
1.132 brouard 5264: double p2[MAXPARM+1];
1.203 brouard 5265: int k, kmax=1;
5266: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5267:
5268: int firstime=0;
1.203 brouard 5269:
1.126 brouard 5270: fx=func(x);
1.203 brouard 5271: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5272: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5273: p2[thetai]=x[thetai]+delti[thetai]*k;
5274: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5275: k1=func(p2)-fx;
5276:
1.203 brouard 5277: p2[thetai]=x[thetai]+delti[thetai]*k;
5278: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5279: k2=func(p2)-fx;
5280:
1.203 brouard 5281: p2[thetai]=x[thetai]-delti[thetai]*k;
5282: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5283: k3=func(p2)-fx;
5284:
1.203 brouard 5285: p2[thetai]=x[thetai]-delti[thetai]*k;
5286: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5287: k4=func(p2)-fx;
1.203 brouard 5288: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5289: if(k1*k2*k3*k4 <0.){
1.208 brouard 5290: firstime=1;
1.203 brouard 5291: kmax=kmax+10;
1.208 brouard 5292: }
5293: if(kmax >=10 || firstime ==1){
1.354 brouard 5294: /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */
1.246 brouard 5295: 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);
5296: 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 5297: 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);
5298: 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);
5299: }
5300: #ifdef DEBUGHESSIJ
5301: v1=hess[thetai][thetai];
5302: v2=hess[thetaj][thetaj];
5303: cv12=res;
5304: /* Computing eigen value of Hessian matrix */
5305: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5306: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5307: if ((lc2 <0) || (lc1 <0) ){
5308: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5309: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5310: 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);
5311: 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);
5312: }
1.126 brouard 5313: #endif
5314: }
5315: return res;
5316: }
5317:
1.203 brouard 5318: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5319: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5320: /* { */
5321: /* int i; */
5322: /* int l=1, lmax=20; */
5323: /* double k1,k2,k3,k4,res,fx; */
5324: /* double p2[MAXPARM+1]; */
5325: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5326: /* int k=0,kmax=10; */
5327: /* double l1; */
5328:
5329: /* fx=func(x); */
5330: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5331: /* l1=pow(10,l); */
5332: /* delts=delt; */
5333: /* for(k=1 ; k <kmax; k=k+1){ */
5334: /* delt = delti*(l1*k); */
5335: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5336: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5337: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5338: /* k1=func(p2)-fx; */
5339:
5340: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5341: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5342: /* k2=func(p2)-fx; */
5343:
5344: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5345: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5346: /* k3=func(p2)-fx; */
5347:
5348: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5349: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5350: /* k4=func(p2)-fx; */
5351: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5352: /* #ifdef DEBUGHESSIJ */
5353: /* 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); */
5354: /* 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); */
5355: /* #endif */
5356: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5357: /* k=kmax; */
5358: /* } */
5359: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5360: /* k=kmax; l=lmax*10; */
5361: /* } */
5362: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5363: /* delts=delt; */
5364: /* } */
5365: /* } /\* End loop k *\/ */
5366: /* } */
5367: /* delti[theta]=delts; */
5368: /* return res; */
5369: /* } */
5370:
5371:
1.126 brouard 5372: /************** Inverse of matrix **************/
5373: void ludcmp(double **a, int n, int *indx, double *d)
5374: {
5375: int i,imax,j,k;
5376: double big,dum,sum,temp;
5377: double *vv;
5378:
5379: vv=vector(1,n);
5380: *d=1.0;
5381: for (i=1;i<=n;i++) {
5382: big=0.0;
5383: for (j=1;j<=n;j++)
5384: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5385: if (big == 0.0){
5386: printf(" Singular Hessian matrix at row %d:\n",i);
5387: for (j=1;j<=n;j++) {
5388: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5389: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5390: }
5391: fflush(ficlog);
5392: fclose(ficlog);
5393: nrerror("Singular matrix in routine ludcmp");
5394: }
1.126 brouard 5395: vv[i]=1.0/big;
5396: }
5397: for (j=1;j<=n;j++) {
5398: for (i=1;i<j;i++) {
5399: sum=a[i][j];
5400: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5401: a[i][j]=sum;
5402: }
5403: big=0.0;
5404: for (i=j;i<=n;i++) {
5405: sum=a[i][j];
5406: for (k=1;k<j;k++)
5407: sum -= a[i][k]*a[k][j];
5408: a[i][j]=sum;
5409: if ( (dum=vv[i]*fabs(sum)) >= big) {
5410: big=dum;
5411: imax=i;
5412: }
5413: }
5414: if (j != imax) {
5415: for (k=1;k<=n;k++) {
5416: dum=a[imax][k];
5417: a[imax][k]=a[j][k];
5418: a[j][k]=dum;
5419: }
5420: *d = -(*d);
5421: vv[imax]=vv[j];
5422: }
5423: indx[j]=imax;
5424: if (a[j][j] == 0.0) a[j][j]=TINY;
5425: if (j != n) {
5426: dum=1.0/(a[j][j]);
5427: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5428: }
5429: }
5430: free_vector(vv,1,n); /* Doesn't work */
5431: ;
5432: }
5433:
5434: void lubksb(double **a, int n, int *indx, double b[])
5435: {
5436: int i,ii=0,ip,j;
5437: double sum;
5438:
5439: for (i=1;i<=n;i++) {
5440: ip=indx[i];
5441: sum=b[ip];
5442: b[ip]=b[i];
5443: if (ii)
5444: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5445: else if (sum) ii=i;
5446: b[i]=sum;
5447: }
5448: for (i=n;i>=1;i--) {
5449: sum=b[i];
5450: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5451: b[i]=sum/a[i][i];
5452: }
5453: }
5454:
5455: void pstamp(FILE *fichier)
5456: {
1.196 brouard 5457: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5458: }
5459:
1.297 brouard 5460: void date2dmy(double date,double *day, double *month, double *year){
5461: double yp=0., yp1=0., yp2=0.;
5462:
5463: yp1=modf(date,&yp);/* extracts integral of date in yp and
5464: fractional in yp1 */
5465: *year=yp;
5466: yp2=modf((yp1*12),&yp);
5467: *month=yp;
5468: yp1=modf((yp2*30.5),&yp);
5469: *day=yp;
5470: if(*day==0) *day=1;
5471: if(*month==0) *month=1;
5472: }
5473:
1.253 brouard 5474:
5475:
1.126 brouard 5476: /************ Frequencies ********************/
1.251 brouard 5477: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5478: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5479: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5480: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5481: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5482: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5483: int iind=0, iage=0;
5484: int mi; /* Effective wave */
5485: int first;
5486: double ***freq; /* Frequencies */
1.268 brouard 5487: 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 */
5488: 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 5489: double *meanq, *stdq, *idq;
1.226 brouard 5490: double **meanqt;
5491: double *pp, **prop, *posprop, *pospropt;
5492: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5493: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5494: double agebegin, ageend;
5495:
5496: pp=vector(1,nlstate);
1.251 brouard 5497: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5498: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5499: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5500: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5501: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5502: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5503: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5504: meanqt=matrix(1,lastpass,1,nqtveff);
5505: strcpy(fileresp,"P_");
5506: strcat(fileresp,fileresu);
5507: /*strcat(fileresphtm,fileresu);*/
5508: if((ficresp=fopen(fileresp,"w"))==NULL) {
5509: printf("Problem with prevalence resultfile: %s\n", fileresp);
5510: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5511: exit(0);
5512: }
1.240 brouard 5513:
1.226 brouard 5514: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5515: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5516: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5517: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5518: fflush(ficlog);
5519: exit(70);
5520: }
5521: else{
5522: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5523: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5524: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5525: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5526: }
1.319 brouard 5527: 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 5528:
1.226 brouard 5529: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5530: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5531: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5532: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5533: fflush(ficlog);
5534: exit(70);
1.240 brouard 5535: } else{
1.226 brouard 5536: 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 5537: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5538: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5539: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5540: }
1.319 brouard 5541: 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 5542:
1.253 brouard 5543: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5544: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5545: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5546: j1=0;
1.126 brouard 5547:
1.227 brouard 5548: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5549: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5550: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5551: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5552:
5553:
1.226 brouard 5554: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5555: reference=low_education V1=0,V2=0
5556: med_educ V1=1 V2=0,
5557: high_educ V1=0 V2=1
1.330 brouard 5558: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5559: */
1.249 brouard 5560: dateintsum=0;
5561: k2cpt=0;
5562:
1.253 brouard 5563: if(cptcoveff == 0 )
1.265 brouard 5564: nl=1; /* Constant and age model only */
1.253 brouard 5565: else
5566: nl=2;
1.265 brouard 5567:
5568: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5569: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5570: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5571: * freq[s1][s2][iage] =0.
5572: * Loop on iind
5573: * ++freq[s1][s2][iage] weighted
5574: * end iind
5575: * if covariate and j!0
5576: * headers Variable on one line
5577: * endif cov j!=0
5578: * header of frequency table by age
5579: * Loop on age
5580: * pp[s1]+=freq[s1][s2][iage] weighted
5581: * pos+=freq[s1][s2][iage] weighted
5582: * Loop on s1 initial state
5583: * fprintf(ficresp
5584: * end s1
5585: * end age
5586: * if j!=0 computes starting values
5587: * end compute starting values
5588: * end j1
5589: * end nl
5590: */
1.253 brouard 5591: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5592: if(nj==1)
5593: j=0; /* First pass for the constant */
1.265 brouard 5594: else{
1.335 brouard 5595: 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 5596: }
1.251 brouard 5597: first=1;
1.332 brouard 5598: 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 5599: posproptt=0.;
1.330 brouard 5600: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5601: scanf("%d", i);*/
5602: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5603: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5604: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5605: freq[i][s2][m]=0;
1.251 brouard 5606:
5607: for (i=1; i<=nlstate; i++) {
1.240 brouard 5608: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5609: prop[i][m]=0;
5610: posprop[i]=0;
5611: pospropt[i]=0;
5612: }
1.283 brouard 5613: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5614: idq[z1]=0.;
5615: meanq[z1]=0.;
5616: stdq[z1]=0.;
1.283 brouard 5617: }
5618: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5619: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5620: /* meanqt[m][z1]=0.; */
5621: /* } */
5622: /* } */
1.251 brouard 5623: /* dateintsum=0; */
5624: /* k2cpt=0; */
5625:
1.265 brouard 5626: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5627: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5628: bool=1;
5629: if(j !=0){
5630: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5631: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5632: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5633: /* if(Tvaraff[z1] ==-20){ */
5634: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5635: /* }else if(Tvaraff[z1] ==-10){ */
5636: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5637: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5638: /* 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); */
5639: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5640: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5641: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5642: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5643: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5644: /* 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", */
5645: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5646: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5647: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5648: } /* Onlyf fixed */
5649: } /* end z1 */
1.335 brouard 5650: } /* cptcoveff > 0 */
1.251 brouard 5651: } /* end any */
5652: }/* end j==0 */
1.265 brouard 5653: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5654: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5655: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5656: m=mw[mi][iind];
5657: if(j!=0){
5658: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5659: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5660: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5661: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5662: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5663: 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 5664: value is -1, we don't select. It differs from the
5665: constant and age model which counts them. */
5666: bool=0; /* not selected */
5667: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5668: /* i1=Tvaraff[z1]; */
5669: /* i2=TnsdVar[i1]; */
5670: /* i3=nbcode[i1][i2]; */
5671: /* i4=covar[i1][iind]; */
5672: /* if(i4 != i3){ */
5673: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5674: bool=0;
5675: }
5676: }
5677: }
5678: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5679: } /* end j==0 */
5680: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5681: if(bool==1){ /*Selected */
1.251 brouard 5682: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5683: and mw[mi+1][iind]. dh depends on stepm. */
5684: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5685: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5686: if(m >=firstpass && m <=lastpass){
5687: k2=anint[m][iind]+(mint[m][iind]/12.);
5688: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5689: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5690: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5691: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5692: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5693: if (m<lastpass) {
5694: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5695: /* 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]); */
5696: if(s[m][iind]==-1)
5697: 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.));
5698: 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 5699: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5700: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5701: idq[z1]=idq[z1]+weight[iind];
5702: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5703: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5704: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5705: }
1.284 brouard 5706: }
1.251 brouard 5707: /* if((int)agev[m][iind] == 55) */
5708: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5709: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5710: 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 5711: }
1.251 brouard 5712: } /* end if between passes */
5713: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5714: dateintsum=dateintsum+k2; /* on all covariates ?*/
5715: k2cpt++;
5716: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5717: }
1.251 brouard 5718: }else{
5719: bool=1;
5720: }/* end bool 2 */
5721: } /* end m */
1.284 brouard 5722: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5723: /* idq[z1]=idq[z1]+weight[iind]; */
5724: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5725: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5726: /* } */
1.251 brouard 5727: } /* end bool */
5728: } /* end iind = 1 to imx */
1.319 brouard 5729: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5730: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5731:
5732:
5733: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5734: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5735: pstamp(ficresp);
1.335 brouard 5736: if (cptcoveff>0 && j!=0){
1.265 brouard 5737: pstamp(ficresp);
1.251 brouard 5738: printf( "\n#********** Variable ");
5739: fprintf(ficresp, "\n#********** Variable ");
5740: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5741: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5742: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5743: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5744: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5745: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5746: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5747: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5748: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5749: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5750: }else{
1.330 brouard 5751: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5752: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5753: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5754: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5755: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5756: }
5757: }
5758: printf( "**********\n#");
5759: fprintf(ficresp, "**********\n#");
5760: fprintf(ficresphtm, "**********</h3>\n");
5761: fprintf(ficresphtmfr, "**********</h3>\n");
5762: fprintf(ficlog, "**********\n");
5763: }
1.284 brouard 5764: /*
5765: Printing means of quantitative variables if any
5766: */
5767: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5768: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5769: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5770: if(weightopt==1){
5771: printf(" Weighted mean and standard deviation of");
5772: fprintf(ficlog," Weighted mean and standard deviation of");
5773: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5774: }
1.311 brouard 5775: /* mu = \frac{w x}{\sum w}
5776: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5777: */
5778: 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]));
5779: 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]));
5780: 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 5781: }
5782: /* for (z1=1; z1<= nqtveff; z1++) { */
5783: /* for(m=1;m<=lastpass;m++){ */
5784: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5785: /* } */
5786: /* } */
1.283 brouard 5787:
1.251 brouard 5788: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5789: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5790: fprintf(ficresp, " Age");
1.335 brouard 5791: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5792: 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]]);
5793: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5794: }
1.251 brouard 5795: for(i=1; i<=nlstate;i++) {
1.335 brouard 5796: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5797: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5798: }
1.335 brouard 5799: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5800: fprintf(ficresphtm, "\n");
5801:
5802: /* Header of frequency table by age */
5803: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5804: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5805: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5806: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5807: if(s2!=0 && m!=0)
5808: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5809: }
1.226 brouard 5810: }
1.251 brouard 5811: fprintf(ficresphtmfr, "\n");
5812:
5813: /* For each age */
5814: for(iage=iagemin; iage <= iagemax+3; iage++){
5815: fprintf(ficresphtm,"<tr>");
5816: if(iage==iagemax+1){
5817: fprintf(ficlog,"1");
5818: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5819: }else if(iage==iagemax+2){
5820: fprintf(ficlog,"0");
5821: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5822: }else if(iage==iagemax+3){
5823: fprintf(ficlog,"Total");
5824: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5825: }else{
1.240 brouard 5826: if(first==1){
1.251 brouard 5827: first=0;
5828: printf("See log file for details...\n");
5829: }
5830: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5831: fprintf(ficlog,"Age %d", iage);
5832: }
1.265 brouard 5833: for(s1=1; s1 <=nlstate ; s1++){
5834: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5835: pp[s1] += freq[s1][m][iage];
1.251 brouard 5836: }
1.265 brouard 5837: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5838: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5839: pos += freq[s1][m][iage];
5840: if(pp[s1]>=1.e-10){
1.251 brouard 5841: if(first==1){
1.265 brouard 5842: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5843: }
1.265 brouard 5844: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5845: }else{
5846: if(first==1)
1.265 brouard 5847: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5848: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5849: }
5850: }
5851:
1.265 brouard 5852: for(s1=1; s1 <=nlstate ; s1++){
5853: /* posprop[s1]=0; */
5854: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5855: pp[s1] += freq[s1][m][iage];
5856: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5857:
5858: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5859: pos += pp[s1]; /* pos is the total number of transitions until this age */
5860: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5861: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5862: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5863: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5864: }
5865:
5866: /* Writing ficresp */
1.335 brouard 5867: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5868: if( iage <= iagemax){
5869: fprintf(ficresp," %d",iage);
5870: }
5871: }else if( nj==2){
5872: if( iage <= iagemax){
5873: fprintf(ficresp," %d",iage);
1.335 brouard 5874: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5875: }
1.240 brouard 5876: }
1.265 brouard 5877: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5878: if(pos>=1.e-5){
1.251 brouard 5879: if(first==1)
1.265 brouard 5880: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5881: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5882: }else{
5883: if(first==1)
1.265 brouard 5884: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5885: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5886: }
5887: if( iage <= iagemax){
5888: if(pos>=1.e-5){
1.335 brouard 5889: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5890: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5891: }else if( nj==2){
5892: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5893: }
5894: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5895: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5896: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5897: } else{
1.335 brouard 5898: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5899: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5900: }
1.240 brouard 5901: }
1.265 brouard 5902: pospropt[s1] +=posprop[s1];
5903: } /* end loop s1 */
1.251 brouard 5904: /* pospropt=0.; */
1.265 brouard 5905: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5906: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5907: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5908: if(first==1){
1.265 brouard 5909: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5910: }
1.265 brouard 5911: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5912: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5913: }
1.265 brouard 5914: if(s1!=0 && m!=0)
5915: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5916: }
1.265 brouard 5917: } /* end loop s1 */
1.251 brouard 5918: posproptt=0.;
1.265 brouard 5919: for(s1=1; s1 <=nlstate; s1++){
5920: posproptt += pospropt[s1];
1.251 brouard 5921: }
5922: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5923: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5924: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5925: if(iage <= iagemax)
5926: fprintf(ficresp,"\n");
1.240 brouard 5927: }
1.251 brouard 5928: if(first==1)
5929: printf("Others in log...\n");
5930: fprintf(ficlog,"\n");
5931: } /* end loop age iage */
1.265 brouard 5932:
1.251 brouard 5933: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5934: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5935: if(posproptt < 1.e-5){
1.265 brouard 5936: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5937: }else{
1.265 brouard 5938: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5939: }
1.226 brouard 5940: }
1.251 brouard 5941: fprintf(ficresphtm,"</tr>\n");
5942: fprintf(ficresphtm,"</table>\n");
5943: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5944: if(posproptt < 1.e-5){
1.251 brouard 5945: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5946: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5947: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5948: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5949: invalidvarcomb[j1]=1;
1.226 brouard 5950: }else{
1.338 brouard 5951: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5952: invalidvarcomb[j1]=0;
1.226 brouard 5953: }
1.251 brouard 5954: fprintf(ficresphtmfr,"</table>\n");
5955: fprintf(ficlog,"\n");
5956: if(j!=0){
5957: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5958: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5959: for(k=1; k <=(nlstate+ndeath); k++){
5960: if (k != i) {
1.265 brouard 5961: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5962: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5963: if(j1==1){ /* All dummy covariates to zero */
5964: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5965: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5966: printf("%d%d ",i,k);
5967: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5968: 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]));
5969: 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]));
5970: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5971: }
1.253 brouard 5972: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5973: for(iage=iagemin; iage <= iagemax+3; iage++){
5974: x[iage]= (double)iage;
5975: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5976: /* 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 5977: }
1.268 brouard 5978: /* Some are not finite, but linreg will ignore these ages */
5979: no=0;
1.253 brouard 5980: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5981: pstart[s1]=b;
5982: pstart[s1-1]=a;
1.252 brouard 5983: }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 */
5984: 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]);
5985: 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 5986: 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 5987: printf("%d%d ",i,k);
5988: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5989: 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 5990: }else{ /* Other cases, like quantitative fixed or varying covariates */
5991: ;
5992: }
5993: /* printf("%12.7f )", param[i][jj][k]); */
5994: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5995: s1++;
1.251 brouard 5996: } /* end jj */
5997: } /* end k!= i */
5998: } /* end k */
1.265 brouard 5999: } /* end i, s1 */
1.251 brouard 6000: } /* end j !=0 */
6001: } /* end selected combination of covariate j1 */
6002: if(j==0){ /* We can estimate starting values from the occurences in each case */
6003: printf("#Freqsummary: Starting values for the constants:\n");
6004: fprintf(ficlog,"\n");
1.265 brouard 6005: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 6006: for(k=1; k <=(nlstate+ndeath); k++){
6007: if (k != i) {
6008: printf("%d%d ",i,k);
6009: fprintf(ficlog,"%d%d ",i,k);
6010: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 6011: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 6012: if(jj==1){ /* Age has to be done */
1.265 brouard 6013: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
6014: 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]));
6015: 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 6016: }
6017: /* printf("%12.7f )", param[i][jj][k]); */
6018: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 6019: s1++;
1.250 brouard 6020: }
1.251 brouard 6021: printf("\n");
6022: fprintf(ficlog,"\n");
1.250 brouard 6023: }
6024: }
1.284 brouard 6025: } /* end of state i */
1.251 brouard 6026: printf("#Freqsummary\n");
6027: fprintf(ficlog,"\n");
1.265 brouard 6028: for(s1=-1; s1 <=nlstate+ndeath; s1++){
6029: for(s2=-1; s2 <=nlstate+ndeath; s2++){
6030: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
6031: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6032: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6033: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
6034: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
6035: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 6036: /* } */
6037: }
1.265 brouard 6038: } /* end loop s1 */
1.251 brouard 6039:
6040: printf("\n");
6041: fprintf(ficlog,"\n");
6042: } /* end j=0 */
1.249 brouard 6043: } /* end j */
1.252 brouard 6044:
1.253 brouard 6045: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 6046: for(i=1, jk=1; i <=nlstate; i++){
6047: for(j=1; j <=nlstate+ndeath; j++){
6048: if(j!=i){
6049: /*ca[0]= k+'a'-1;ca[1]='\0';*/
6050: printf("%1d%1d",i,j);
6051: fprintf(ficparo,"%1d%1d",i,j);
6052: for(k=1; k<=ncovmodel;k++){
6053: /* printf(" %lf",param[i][j][k]); */
6054: /* fprintf(ficparo," %lf",param[i][j][k]); */
6055: p[jk]=pstart[jk];
6056: printf(" %f ",pstart[jk]);
6057: fprintf(ficparo," %f ",pstart[jk]);
6058: jk++;
6059: }
6060: printf("\n");
6061: fprintf(ficparo,"\n");
6062: }
6063: }
6064: }
6065: } /* end mle=-2 */
1.226 brouard 6066: dateintmean=dateintsum/k2cpt;
1.296 brouard 6067: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6068:
1.226 brouard 6069: fclose(ficresp);
6070: fclose(ficresphtm);
6071: fclose(ficresphtmfr);
1.283 brouard 6072: free_vector(idq,1,nqfveff);
1.226 brouard 6073: free_vector(meanq,1,nqfveff);
1.284 brouard 6074: free_vector(stdq,1,nqfveff);
1.226 brouard 6075: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6076: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6077: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6078: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6079: free_vector(pospropt,1,nlstate);
6080: free_vector(posprop,1,nlstate);
1.251 brouard 6081: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6082: free_vector(pp,1,nlstate);
6083: /* End of freqsummary */
6084: }
1.126 brouard 6085:
1.268 brouard 6086: /* Simple linear regression */
6087: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6088:
6089: /* y=a+bx regression */
6090: double sumx = 0.0; /* sum of x */
6091: double sumx2 = 0.0; /* sum of x**2 */
6092: double sumxy = 0.0; /* sum of x * y */
6093: double sumy = 0.0; /* sum of y */
6094: double sumy2 = 0.0; /* sum of y**2 */
6095: double sume2 = 0.0; /* sum of square or residuals */
6096: double yhat;
6097:
6098: double denom=0;
6099: int i;
6100: int ne=*no;
6101:
6102: for ( i=ifi, ne=0;i<=ila;i++) {
6103: if(!isfinite(x[i]) || !isfinite(y[i])){
6104: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6105: continue;
6106: }
6107: ne=ne+1;
6108: sumx += x[i];
6109: sumx2 += x[i]*x[i];
6110: sumxy += x[i] * y[i];
6111: sumy += y[i];
6112: sumy2 += y[i]*y[i];
6113: denom = (ne * sumx2 - sumx*sumx);
6114: /* 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); */
6115: }
6116:
6117: denom = (ne * sumx2 - sumx*sumx);
6118: if (denom == 0) {
6119: // vertical, slope m is infinity
6120: *b = INFINITY;
6121: *a = 0;
6122: if (r) *r = 0;
6123: return 1;
6124: }
6125:
6126: *b = (ne * sumxy - sumx * sumy) / denom;
6127: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6128: if (r!=NULL) {
6129: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6130: sqrt((sumx2 - sumx*sumx/ne) *
6131: (sumy2 - sumy*sumy/ne));
6132: }
6133: *no=ne;
6134: for ( i=ifi, ne=0;i<=ila;i++) {
6135: if(!isfinite(x[i]) || !isfinite(y[i])){
6136: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6137: continue;
6138: }
6139: ne=ne+1;
6140: yhat = y[i] - *a -*b* x[i];
6141: sume2 += yhat * yhat ;
6142:
6143: denom = (ne * sumx2 - sumx*sumx);
6144: /* 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); */
6145: }
6146: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6147: *sa= *sb * sqrt(sumx2/ne);
6148:
6149: return 0;
6150: }
6151:
1.126 brouard 6152: /************ Prevalence ********************/
1.227 brouard 6153: 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)
6154: {
6155: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6156: in each health status at the date of interview (if between dateprev1 and dateprev2).
6157: We still use firstpass and lastpass as another selection.
6158: */
1.126 brouard 6159:
1.227 brouard 6160: int i, m, jk, j1, bool, z1,j, iv;
6161: int mi; /* Effective wave */
6162: int iage;
6163: double agebegin, ageend;
6164:
6165: double **prop;
6166: double posprop;
6167: double y2; /* in fractional years */
6168: int iagemin, iagemax;
6169: int first; /** to stop verbosity which is redirected to log file */
6170:
6171: iagemin= (int) agemin;
6172: iagemax= (int) agemax;
6173: /*pp=vector(1,nlstate);*/
1.251 brouard 6174: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6175: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6176: j1=0;
1.222 brouard 6177:
1.227 brouard 6178: /*j=cptcoveff;*/
6179: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6180:
1.288 brouard 6181: first=0;
1.335 brouard 6182: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6183: for (i=1; i<=nlstate; i++)
1.251 brouard 6184: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6185: prop[i][iage]=0.0;
6186: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6187: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6188: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6189:
6190: for (i=1; i<=imx; i++) { /* Each individual */
6191: bool=1;
6192: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6193: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6194: m=mw[mi][i];
6195: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6196: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6197: for (z1=1; z1<=cptcoveff; z1++){
6198: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6199: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6200: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6201: bool=0;
6202: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6203: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6204: bool=0;
6205: }
6206: }
6207: if(bool==1){ /* Otherwise we skip that wave/person */
6208: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6209: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6210: if(m >=firstpass && m <=lastpass){
6211: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6212: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6213: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6214: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6215: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6216: 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);
6217: exit(1);
6218: }
6219: if (s[m][i]>0 && s[m][i]<=nlstate) {
6220: /*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]]);*/
6221: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6222: prop[s[m][i]][iagemax+3] += weight[i];
6223: } /* end valid statuses */
6224: } /* end selection of dates */
6225: } /* end selection of waves */
6226: } /* end bool */
6227: } /* end wave */
6228: } /* end individual */
6229: for(i=iagemin; i <= iagemax+3; i++){
6230: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6231: posprop += prop[jk][i];
6232: }
6233:
6234: for(jk=1; jk <=nlstate ; jk++){
6235: if( i <= iagemax){
6236: if(posprop>=1.e-5){
6237: probs[i][jk][j1]= prop[jk][i]/posprop;
6238: } else{
1.288 brouard 6239: if(!first){
6240: first=1;
1.266 brouard 6241: 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]);
6242: }else{
1.288 brouard 6243: 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 6244: }
6245: }
6246: }
6247: }/* end jk */
6248: }/* end i */
1.222 brouard 6249: /*} *//* end i1 */
1.227 brouard 6250: } /* end j1 */
1.222 brouard 6251:
1.227 brouard 6252: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6253: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6254: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6255: } /* End of prevalence */
1.126 brouard 6256:
6257: /************* Waves Concatenation ***************/
6258:
6259: 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)
6260: {
1.298 brouard 6261: /* 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 6262: Death is a valid wave (if date is known).
6263: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6264: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6265: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6266: */
1.126 brouard 6267:
1.224 brouard 6268: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6269: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6270: double sum=0., jmean=0.;*/
1.224 brouard 6271: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6272: int j, k=0,jk, ju, jl;
6273: double sum=0.;
6274: first=0;
1.214 brouard 6275: firstwo=0;
1.217 brouard 6276: firsthree=0;
1.218 brouard 6277: firstfour=0;
1.164 brouard 6278: jmin=100000;
1.126 brouard 6279: jmax=-1;
6280: jmean=0.;
1.224 brouard 6281:
6282: /* Treating live states */
1.214 brouard 6283: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6284: mi=0; /* First valid wave */
1.227 brouard 6285: mli=0; /* Last valid wave */
1.309 brouard 6286: m=firstpass; /* Loop on waves */
6287: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6288: 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 */
6289: mli=m-1;/* mw[++mi][i]=m-1; */
6290: }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 6291: 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 6292: mli=m;
1.224 brouard 6293: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6294: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6295: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6296: }
1.309 brouard 6297: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6298: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6299: break;
1.224 brouard 6300: #else
1.317 brouard 6301: 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 6302: if(firsthree == 0){
1.302 brouard 6303: 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 6304: firsthree=1;
1.317 brouard 6305: }else if(firsthree >=1 && firsthree < 10){
6306: 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);
6307: firsthree++;
6308: }else if(firsthree == 10){
6309: printf("Information, too many Information flags: no more reported to log either\n");
6310: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6311: firsthree++;
6312: }else{
6313: firsthree++;
1.227 brouard 6314: }
1.309 brouard 6315: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6316: mli=m;
6317: }
6318: if(s[m][i]==-2){ /* Vital status is really unknown */
6319: nbwarn++;
1.309 brouard 6320: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6321: 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);
6322: 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);
6323: }
6324: break;
6325: }
6326: break;
1.224 brouard 6327: #endif
1.227 brouard 6328: }/* End m >= lastpass */
1.126 brouard 6329: }/* end while */
1.224 brouard 6330:
1.227 brouard 6331: /* 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 6332: /* After last pass */
1.224 brouard 6333: /* Treating death states */
1.214 brouard 6334: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6335: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6336: /* } */
1.126 brouard 6337: mi++; /* Death is another wave */
6338: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6339: /* Only death is a correct wave */
1.126 brouard 6340: mw[mi][i]=m;
1.257 brouard 6341: } /* else not in a death state */
1.224 brouard 6342: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6343: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6344: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6345: 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 6346: nbwarn++;
6347: if(firstfiv==0){
1.309 brouard 6348: 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 6349: firstfiv=1;
6350: }else{
1.309 brouard 6351: 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 6352: }
1.309 brouard 6353: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6354: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6355: nberr++;
6356: if(firstwo==0){
1.309 brouard 6357: 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 6358: firstwo=1;
6359: }
1.309 brouard 6360: 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 6361: }
1.257 brouard 6362: }else{ /* if date of interview is unknown */
1.227 brouard 6363: /* death is known but not confirmed by death status at any wave */
6364: if(firstfour==0){
1.309 brouard 6365: 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 6366: firstfour=1;
6367: }
1.309 brouard 6368: 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 6369: }
1.224 brouard 6370: } /* end if date of death is known */
6371: #endif
1.309 brouard 6372: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6373: /* wav[i]=mw[mi][i]; */
1.126 brouard 6374: if(mi==0){
6375: nbwarn++;
6376: if(first==0){
1.227 brouard 6377: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6378: first=1;
1.126 brouard 6379: }
6380: if(first==1){
1.227 brouard 6381: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6382: }
6383: } /* end mi==0 */
6384: } /* End individuals */
1.214 brouard 6385: /* wav and mw are no more changed */
1.223 brouard 6386:
1.317 brouard 6387: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6388: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6389:
6390:
1.126 brouard 6391: for(i=1; i<=imx; i++){
6392: for(mi=1; mi<wav[i];mi++){
6393: if (stepm <=0)
1.227 brouard 6394: dh[mi][i]=1;
1.126 brouard 6395: else{
1.260 brouard 6396: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6397: if (agedc[i] < 2*AGESUP) {
6398: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6399: if(j==0) j=1; /* Survives at least one month after exam */
6400: else if(j<0){
6401: nberr++;
6402: printf("Error! Negative delay (%d to death) between waves %d and %d of individual %ld at 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]);
6403: j=1; /* Temporary Dangerous patch */
6404: 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);
6405: fprintf(ficlog,"Error! Negative delay (%d to death) between waves %d and %d of individual %ld at 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]);
6406: 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);
6407: }
6408: k=k+1;
6409: if (j >= jmax){
6410: jmax=j;
6411: ijmax=i;
6412: }
6413: if (j <= jmin){
6414: jmin=j;
6415: ijmin=i;
6416: }
6417: sum=sum+j;
6418: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6419: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6420: }
6421: }
6422: else{
6423: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6424: /* 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 6425:
1.227 brouard 6426: k=k+1;
6427: if (j >= jmax) {
6428: jmax=j;
6429: ijmax=i;
6430: }
6431: else if (j <= jmin){
6432: jmin=j;
6433: ijmin=i;
6434: }
6435: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6436: /*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]);*/
6437: if(j<0){
6438: nberr++;
6439: printf("Error! Negative delay (%d) between waves %d and %d of individual %ld at 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]);
6440: fprintf(ficlog,"Error! Negative delay (%d) between waves %d and %d of individual %ld at 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]);
6441: }
6442: sum=sum+j;
6443: }
6444: jk= j/stepm;
6445: jl= j -jk*stepm;
6446: ju= j -(jk+1)*stepm;
6447: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6448: if(jl==0){
6449: dh[mi][i]=jk;
6450: bh[mi][i]=0;
6451: }else{ /* We want a negative bias in order to only have interpolation ie
6452: * to avoid the price of an extra matrix product in likelihood */
6453: dh[mi][i]=jk+1;
6454: bh[mi][i]=ju;
6455: }
6456: }else{
6457: if(jl <= -ju){
6458: dh[mi][i]=jk;
6459: bh[mi][i]=jl; /* bias is positive if real duration
6460: * is higher than the multiple of stepm and negative otherwise.
6461: */
6462: }
6463: else{
6464: dh[mi][i]=jk+1;
6465: bh[mi][i]=ju;
6466: }
6467: if(dh[mi][i]==0){
6468: dh[mi][i]=1; /* At least one step */
6469: bh[mi][i]=ju; /* At least one step */
6470: /* 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);*/
6471: }
6472: } /* end if mle */
1.126 brouard 6473: }
6474: } /* end wave */
6475: }
6476: jmean=sum/k;
6477: 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 6478: 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 6479: }
1.126 brouard 6480:
6481: /*********** Tricode ****************************/
1.220 brouard 6482: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6483: {
6484: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6485: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6486: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6487: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6488: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6489: */
1.130 brouard 6490:
1.242 brouard 6491: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6492: int modmaxcovj=0; /* Modality max of covariates j */
6493: int cptcode=0; /* Modality max of covariates j */
6494: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6495:
6496:
1.242 brouard 6497: /* cptcoveff=0; */
6498: /* *cptcov=0; */
1.126 brouard 6499:
1.242 brouard 6500: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6501: for (k=1; k <= maxncov; k++)
6502: for(j=1; j<=2; j++)
6503: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6504:
1.242 brouard 6505: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6506: 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 6507: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6508: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 6509: 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 6510: switch(Fixed[k]) {
6511: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6512: modmaxcovj=0;
6513: modmincovj=0;
1.242 brouard 6514: 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 6515: /* 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 6516: ij=(int)(covar[Tvar[k]][i]);
6517: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6518: * If product of Vn*Vm, still boolean *:
6519: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6520: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6521: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6522: modality of the nth covariate of individual i. */
6523: if (ij > modmaxcovj)
6524: modmaxcovj=ij;
6525: else if (ij < modmincovj)
6526: modmincovj=ij;
1.287 brouard 6527: if (ij <0 || ij >1 ){
1.311 brouard 6528: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6529: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6530: fflush(ficlog);
6531: exit(1);
1.287 brouard 6532: }
6533: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6534: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6535: exit(1);
6536: }else
6537: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6538: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6539: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6540: /* getting the maximum value of the modality of the covariate
6541: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6542: female ies 1, then modmaxcovj=1.
6543: */
6544: } /* end for loop on individuals i */
6545: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6546: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6547: cptcode=modmaxcovj;
6548: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6549: /*for (i=0; i<=cptcode; i++) {*/
6550: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6551: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6552: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6553: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6554: if( j != -1){
6555: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6556: covariate for which somebody answered excluding
6557: undefined. Usually 2: 0 and 1. */
6558: }
6559: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6560: covariate for which somebody answered including
6561: undefined. Usually 3: -1, 0 and 1. */
6562: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6563: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6564: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6565:
1.242 brouard 6566: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6567: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6568: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6569: /* modmincovj=3; modmaxcovj = 7; */
6570: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6571: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6572: /* defining two dummy variables: variables V1_1 and V1_2.*/
6573: /* nbcode[Tvar[j]][ij]=k; */
6574: /* nbcode[Tvar[j]][1]=0; */
6575: /* nbcode[Tvar[j]][2]=1; */
6576: /* nbcode[Tvar[j]][3]=2; */
6577: /* To be continued (not working yet). */
6578: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6579:
6580: /* 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*/
6581: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6582: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6583: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6584: /*, could be restored in the future */
6585: 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 6586: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6587: break;
6588: }
6589: ij++;
1.287 brouard 6590: 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 6591: cptcode = ij; /* New max modality for covar j */
6592: } /* end of loop on modality i=-1 to 1 or more */
6593: break;
6594: case 1: /* Testing on varying covariate, could be simple and
6595: * should look at waves or product of fixed *
6596: * varying. No time to test -1, assuming 0 and 1 only */
6597: ij=0;
6598: for(i=0; i<=1;i++){
6599: nbcode[Tvar[k]][++ij]=i;
6600: }
6601: break;
6602: default:
6603: break;
6604: } /* end switch */
6605: } /* end dummy test */
1.349 brouard 6606: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6607: 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 6608: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6609: printf("Error k=%d \n",k);
6610: exit(1);
6611: }
1.311 brouard 6612: if(isnan(covar[Tvar[k]][i])){
6613: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6614: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6615: fflush(ficlog);
6616: exit(1);
6617: }
6618: }
1.335 brouard 6619: } /* end Quanti */
1.287 brouard 6620: } /* 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 6621:
6622: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6623: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6624: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6625: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6626: 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 */
6627: 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 */
6628: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6629: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6630:
6631: ij=0;
6632: /* 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 6633: 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 */
6634: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6635: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6636: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6637: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6638: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6639: /* 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 6640: /* If product not in single variable we don't print results */
6641: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6642: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6643: /* k= 1 2 3 4 5 6 7 8 9 */
6644: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6645: /* ij 1 2 3 */
6646: /* Tvaraff[ij]= 4 3 1 */
6647: /* Tmodelind[ij]=2 3 9 */
6648: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6649: 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*/
6650: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6651: 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 */
6652: if(Fixed[k]!=0)
6653: anyvaryingduminmodel=1;
6654: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6655: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6656: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6657: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6658: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6659: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6660: }
6661: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6662: /* ij--; */
6663: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6664: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6665: * because they can be excluded from the model and real
6666: * if in the model but excluded because missing values, but how to get k from ij?*/
6667: for(j=ij+1; j<= cptcovt; j++){
6668: Tvaraff[j]=0;
6669: Tmodelind[j]=0;
6670: }
6671: for(j=ntveff+1; j<= cptcovt; j++){
6672: TmodelInvind[j]=0;
6673: }
6674: /* To be sorted */
6675: ;
6676: }
1.126 brouard 6677:
1.145 brouard 6678:
1.126 brouard 6679: /*********** Health Expectancies ****************/
6680:
1.235 brouard 6681: 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 6682:
6683: {
6684: /* Health expectancies, no variances */
1.329 brouard 6685: /* cij is the combination in the list of combination of dummy covariates */
6686: /* strstart is a string of time at start of computing */
1.164 brouard 6687: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6688: int nhstepma, nstepma; /* Decreasing with age */
6689: double age, agelim, hf;
6690: double ***p3mat;
6691: double eip;
6692:
1.238 brouard 6693: /* pstamp(ficreseij); */
1.126 brouard 6694: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6695: fprintf(ficreseij,"# Age");
6696: for(i=1; i<=nlstate;i++){
6697: for(j=1; j<=nlstate;j++){
6698: fprintf(ficreseij," e%1d%1d ",i,j);
6699: }
6700: fprintf(ficreseij," e%1d. ",i);
6701: }
6702: fprintf(ficreseij,"\n");
6703:
6704:
6705: if(estepm < stepm){
6706: printf ("Problem %d lower than %d\n",estepm, stepm);
6707: }
6708: else hstepm=estepm;
6709: /* We compute the life expectancy from trapezoids spaced every estepm months
6710: * This is mainly to measure the difference between two models: for example
6711: * if stepm=24 months pijx are given only every 2 years and by summing them
6712: * we are calculating an estimate of the Life Expectancy assuming a linear
6713: * progression in between and thus overestimating or underestimating according
6714: * to the curvature of the survival function. If, for the same date, we
6715: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6716: * to compare the new estimate of Life expectancy with the same linear
6717: * hypothesis. A more precise result, taking into account a more precise
6718: * curvature will be obtained if estepm is as small as stepm. */
6719:
6720: /* For example we decided to compute the life expectancy with the smallest unit */
6721: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6722: nhstepm is the number of hstepm from age to agelim
6723: nstepm is the number of stepm from age to agelin.
1.270 brouard 6724: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6725: and note for a fixed period like estepm months */
6726: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6727: survival function given by stepm (the optimization length). Unfortunately it
6728: means that if the survival funtion is printed only each two years of age and if
6729: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6730: results. So we changed our mind and took the option of the best precision.
6731: */
6732: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6733:
6734: agelim=AGESUP;
6735: /* If stepm=6 months */
6736: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6737: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6738:
6739: /* nhstepm age range expressed in number of stepm */
6740: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6741: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6742: /* if (stepm >= YEARM) hstepm=1;*/
6743: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6744: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6745:
6746: for (age=bage; age<=fage; age ++){
6747: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6748: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6749: /* if (stepm >= YEARM) hstepm=1;*/
6750: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6751:
6752: /* If stepm=6 months */
6753: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6754: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6755: /* 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 6756: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6757:
6758: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6759:
6760: printf("%d|",(int)age);fflush(stdout);
6761: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6762:
6763: /* Computing expectancies */
6764: for(i=1; i<=nlstate;i++)
6765: for(j=1; j<=nlstate;j++)
6766: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6767: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6768:
6769: /* 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]);*/
6770:
6771: }
6772:
6773: fprintf(ficreseij,"%3.0f",age );
6774: for(i=1; i<=nlstate;i++){
6775: eip=0;
6776: for(j=1; j<=nlstate;j++){
6777: eip +=eij[i][j][(int)age];
6778: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6779: }
6780: fprintf(ficreseij,"%9.4f", eip );
6781: }
6782: fprintf(ficreseij,"\n");
6783:
6784: }
6785: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6786: printf("\n");
6787: fprintf(ficlog,"\n");
6788:
6789: }
6790:
1.235 brouard 6791: 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 6792:
6793: {
6794: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6795: to initial status i, ei. .
1.126 brouard 6796: */
1.336 brouard 6797: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6798: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6799: int nhstepma, nstepma; /* Decreasing with age */
6800: double age, agelim, hf;
6801: double ***p3matp, ***p3matm, ***varhe;
6802: double **dnewm,**doldm;
6803: double *xp, *xm;
6804: double **gp, **gm;
6805: double ***gradg, ***trgradg;
6806: int theta;
6807:
6808: double eip, vip;
6809:
6810: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6811: xp=vector(1,npar);
6812: xm=vector(1,npar);
6813: dnewm=matrix(1,nlstate*nlstate,1,npar);
6814: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6815:
6816: pstamp(ficresstdeij);
6817: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6818: fprintf(ficresstdeij,"# Age");
6819: for(i=1; i<=nlstate;i++){
6820: for(j=1; j<=nlstate;j++)
6821: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6822: fprintf(ficresstdeij," e%1d. ",i);
6823: }
6824: fprintf(ficresstdeij,"\n");
6825:
6826: pstamp(ficrescveij);
6827: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6828: fprintf(ficrescveij,"# Age");
6829: for(i=1; i<=nlstate;i++)
6830: for(j=1; j<=nlstate;j++){
6831: cptj= (j-1)*nlstate+i;
6832: for(i2=1; i2<=nlstate;i2++)
6833: for(j2=1; j2<=nlstate;j2++){
6834: cptj2= (j2-1)*nlstate+i2;
6835: if(cptj2 <= cptj)
6836: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6837: }
6838: }
6839: fprintf(ficrescveij,"\n");
6840:
6841: if(estepm < stepm){
6842: printf ("Problem %d lower than %d\n",estepm, stepm);
6843: }
6844: else hstepm=estepm;
6845: /* We compute the life expectancy from trapezoids spaced every estepm months
6846: * This is mainly to measure the difference between two models: for example
6847: * if stepm=24 months pijx are given only every 2 years and by summing them
6848: * we are calculating an estimate of the Life Expectancy assuming a linear
6849: * progression in between and thus overestimating or underestimating according
6850: * to the curvature of the survival function. If, for the same date, we
6851: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6852: * to compare the new estimate of Life expectancy with the same linear
6853: * hypothesis. A more precise result, taking into account a more precise
6854: * curvature will be obtained if estepm is as small as stepm. */
6855:
6856: /* For example we decided to compute the life expectancy with the smallest unit */
6857: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6858: nhstepm is the number of hstepm from age to agelim
6859: nstepm is the number of stepm from age to agelin.
6860: Look at hpijx to understand the reason of that which relies in memory size
6861: and note for a fixed period like estepm months */
6862: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6863: survival function given by stepm (the optimization length). Unfortunately it
6864: means that if the survival funtion is printed only each two years of age and if
6865: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6866: results. So we changed our mind and took the option of the best precision.
6867: */
6868: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6869:
6870: /* If stepm=6 months */
6871: /* nhstepm age range expressed in number of stepm */
6872: agelim=AGESUP;
6873: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6874: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6875: /* if (stepm >= YEARM) hstepm=1;*/
6876: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6877:
6878: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6879: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6880: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6881: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6882: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6883: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6884:
6885: for (age=bage; age<=fage; age ++){
6886: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6887: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6888: /* if (stepm >= YEARM) hstepm=1;*/
6889: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6890:
1.126 brouard 6891: /* If stepm=6 months */
6892: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6893: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6894:
6895: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6896:
1.126 brouard 6897: /* Computing Variances of health expectancies */
6898: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6899: decrease memory allocation */
6900: for(theta=1; theta <=npar; theta++){
6901: for(i=1; i<=npar; i++){
1.222 brouard 6902: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6903: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6904: }
1.235 brouard 6905: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6906: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6907:
1.126 brouard 6908: for(j=1; j<= nlstate; j++){
1.222 brouard 6909: for(i=1; i<=nlstate; i++){
6910: for(h=0; h<=nhstepm-1; h++){
6911: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6912: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6913: }
6914: }
1.126 brouard 6915: }
1.218 brouard 6916:
1.126 brouard 6917: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6918: for(h=0; h<=nhstepm-1; h++){
6919: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6920: }
1.126 brouard 6921: }/* End theta */
6922:
6923:
6924: for(h=0; h<=nhstepm-1; h++)
6925: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6926: for(theta=1; theta <=npar; theta++)
6927: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6928:
1.218 brouard 6929:
1.222 brouard 6930: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6931: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6932: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6933:
1.222 brouard 6934: printf("%d|",(int)age);fflush(stdout);
6935: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6936: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6937: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6938: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6939: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6940: for(ij=1;ij<=nlstate*nlstate;ij++)
6941: for(ji=1;ji<=nlstate*nlstate;ji++)
6942: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6943: }
6944: }
1.320 brouard 6945: /* if((int)age ==50){ */
6946: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6947: /* } */
1.126 brouard 6948: /* Computing expectancies */
1.235 brouard 6949: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6950: for(i=1; i<=nlstate;i++)
6951: for(j=1; j<=nlstate;j++)
1.222 brouard 6952: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6953: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6954:
1.222 brouard 6955: /* 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 6956:
1.222 brouard 6957: }
1.269 brouard 6958:
6959: /* Standard deviation of expectancies ij */
1.126 brouard 6960: fprintf(ficresstdeij,"%3.0f",age );
6961: for(i=1; i<=nlstate;i++){
6962: eip=0.;
6963: vip=0.;
6964: for(j=1; j<=nlstate;j++){
1.222 brouard 6965: eip += eij[i][j][(int)age];
6966: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6967: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6968: 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 6969: }
6970: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6971: }
6972: fprintf(ficresstdeij,"\n");
1.218 brouard 6973:
1.269 brouard 6974: /* Variance of expectancies ij */
1.126 brouard 6975: fprintf(ficrescveij,"%3.0f",age );
6976: for(i=1; i<=nlstate;i++)
6977: for(j=1; j<=nlstate;j++){
1.222 brouard 6978: cptj= (j-1)*nlstate+i;
6979: for(i2=1; i2<=nlstate;i2++)
6980: for(j2=1; j2<=nlstate;j2++){
6981: cptj2= (j2-1)*nlstate+i2;
6982: if(cptj2 <= cptj)
6983: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6984: }
1.126 brouard 6985: }
6986: fprintf(ficrescveij,"\n");
1.218 brouard 6987:
1.126 brouard 6988: }
6989: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6990: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6991: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6992: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6993: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6994: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6995: printf("\n");
6996: fprintf(ficlog,"\n");
1.218 brouard 6997:
1.126 brouard 6998: free_vector(xm,1,npar);
6999: free_vector(xp,1,npar);
7000: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
7001: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
7002: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
7003: }
1.218 brouard 7004:
1.126 brouard 7005: /************ Variance ******************/
1.235 brouard 7006: 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 7007: {
1.279 brouard 7008: /** Variance of health expectancies
7009: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
7010: * double **newm;
7011: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
7012: */
1.218 brouard 7013:
7014: /* int movingaverage(); */
7015: double **dnewm,**doldm;
7016: double **dnewmp,**doldmp;
7017: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 7018: int first=0;
1.218 brouard 7019: int k;
7020: double *xp;
1.279 brouard 7021: double **gp, **gm; /**< for var eij */
7022: double ***gradg, ***trgradg; /**< for var eij */
7023: double **gradgp, **trgradgp; /**< for var p point j */
7024: double *gpp, *gmp; /**< for var p point j */
7025: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 7026: double ***p3mat;
7027: double age,agelim, hf;
7028: /* double ***mobaverage; */
7029: int theta;
7030: char digit[4];
7031: char digitp[25];
7032:
7033: char fileresprobmorprev[FILENAMELENGTH];
7034:
7035: if(popbased==1){
7036: if(mobilav!=0)
7037: strcpy(digitp,"-POPULBASED-MOBILAV_");
7038: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
7039: }
7040: else
7041: strcpy(digitp,"-STABLBASED_");
1.126 brouard 7042:
1.218 brouard 7043: /* if (mobilav!=0) { */
7044: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7045: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
7046: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
7047: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
7048: /* } */
7049: /* } */
7050:
7051: strcpy(fileresprobmorprev,"PRMORPREV-");
7052: sprintf(digit,"%-d",ij);
7053: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7054: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7055: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7056: strcat(fileresprobmorprev,fileresu);
7057: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7058: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7059: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7060: }
7061: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7062: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7063: pstamp(ficresprobmorprev);
7064: 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 7065: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7066:
7067: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7068: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7069: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7070: /* } */
7071: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7072: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7073: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7074: }
1.337 brouard 7075: /* for(j=1;j<=cptcoveff;j++) */
7076: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7077: fprintf(ficresprobmorprev,"\n");
7078:
1.218 brouard 7079: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7080: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7081: fprintf(ficresprobmorprev," p.%-d SE",j);
7082: for(i=1; i<=nlstate;i++)
7083: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7084: }
7085: fprintf(ficresprobmorprev,"\n");
7086:
7087: fprintf(ficgp,"\n# Routine varevsij");
7088: fprintf(ficgp,"\nunset title \n");
7089: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7090: 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");
7091: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7092:
1.218 brouard 7093: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7094: pstamp(ficresvij);
7095: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7096: if(popbased==1)
7097: 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);
7098: else
7099: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7100: fprintf(ficresvij,"# Age");
7101: for(i=1; i<=nlstate;i++)
7102: for(j=1; j<=nlstate;j++)
7103: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7104: fprintf(ficresvij,"\n");
7105:
7106: xp=vector(1,npar);
7107: dnewm=matrix(1,nlstate,1,npar);
7108: doldm=matrix(1,nlstate,1,nlstate);
7109: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7110: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7111:
7112: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7113: gpp=vector(nlstate+1,nlstate+ndeath);
7114: gmp=vector(nlstate+1,nlstate+ndeath);
7115: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7116:
1.218 brouard 7117: if(estepm < stepm){
7118: printf ("Problem %d lower than %d\n",estepm, stepm);
7119: }
7120: else hstepm=estepm;
7121: /* For example we decided to compute the life expectancy with the smallest unit */
7122: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7123: nhstepm is the number of hstepm from age to agelim
7124: nstepm is the number of stepm from age to agelim.
7125: Look at function hpijx to understand why because of memory size limitations,
7126: we decided (b) to get a life expectancy respecting the most precise curvature of the
7127: survival function given by stepm (the optimization length). Unfortunately it
7128: means that if the survival funtion is printed every two years of age and if
7129: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7130: results. So we changed our mind and took the option of the best precision.
7131: */
7132: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7133: agelim = AGESUP;
7134: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7135: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7136: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7137: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7138: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7139: gp=matrix(0,nhstepm,1,nlstate);
7140: gm=matrix(0,nhstepm,1,nlstate);
7141:
7142:
7143: for(theta=1; theta <=npar; theta++){
7144: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7145: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7146: }
1.279 brouard 7147: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7148: * returns into prlim .
1.288 brouard 7149: */
1.242 brouard 7150: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7151:
7152: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7153: if (popbased==1) {
7154: if(mobilav ==0){
7155: for(i=1; i<=nlstate;i++)
7156: prlim[i][i]=probs[(int)age][i][ij];
7157: }else{ /* mobilav */
7158: for(i=1; i<=nlstate;i++)
7159: prlim[i][i]=mobaverage[(int)age][i][ij];
7160: }
7161: }
1.295 brouard 7162: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7163: */
7164: 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 7165: /**< 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 7166: * at horizon h in state j including mortality.
7167: */
1.218 brouard 7168: for(j=1; j<= nlstate; j++){
7169: for(h=0; h<=nhstepm; h++){
7170: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7171: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7172: }
7173: }
1.279 brouard 7174: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7175: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7176: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7177: */
7178: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7179: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7180: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7181: }
7182:
7183: /* Again with minus shift */
1.218 brouard 7184:
7185: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7186: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7187:
1.242 brouard 7188: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7189:
7190: if (popbased==1) {
7191: if(mobilav ==0){
7192: for(i=1; i<=nlstate;i++)
7193: prlim[i][i]=probs[(int)age][i][ij];
7194: }else{ /* mobilav */
7195: for(i=1; i<=nlstate;i++)
7196: prlim[i][i]=mobaverage[(int)age][i][ij];
7197: }
7198: }
7199:
1.235 brouard 7200: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7201:
7202: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7203: for(h=0; h<=nhstepm; h++){
7204: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7205: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7206: }
7207: }
7208: /* This for computing probability of death (h=1 means
7209: computed over hstepm matrices product = hstepm*stepm months)
7210: as a weighted average of prlim.
7211: */
7212: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7213: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7214: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7215: }
1.279 brouard 7216: /* end shifting computations */
7217:
7218: /**< Computing gradient matrix at horizon h
7219: */
1.218 brouard 7220: for(j=1; j<= nlstate; j++) /* vareij */
7221: for(h=0; h<=nhstepm; h++){
7222: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7223: }
1.279 brouard 7224: /**< Gradient of overall mortality p.3 (or p.j)
7225: */
7226: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7227: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7228: }
7229:
7230: } /* End theta */
1.279 brouard 7231:
7232: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7233: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7234:
7235: for(h=0; h<=nhstepm; h++) /* veij */
7236: for(j=1; j<=nlstate;j++)
7237: for(theta=1; theta <=npar; theta++)
7238: trgradg[h][j][theta]=gradg[h][theta][j];
7239:
7240: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7241: for(theta=1; theta <=npar; theta++)
7242: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7243: /**< as well as its transposed matrix
7244: */
1.218 brouard 7245:
7246: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7247: for(i=1;i<=nlstate;i++)
7248: for(j=1;j<=nlstate;j++)
7249: vareij[i][j][(int)age] =0.;
1.279 brouard 7250:
7251: /* Computing trgradg by matcov by gradg at age and summing over h
7252: * and k (nhstepm) formula 15 of article
7253: * Lievre-Brouard-Heathcote
7254: */
7255:
1.218 brouard 7256: for(h=0;h<=nhstepm;h++){
7257: for(k=0;k<=nhstepm;k++){
7258: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7259: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7260: for(i=1;i<=nlstate;i++)
7261: for(j=1;j<=nlstate;j++)
7262: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7263: }
7264: }
7265:
1.279 brouard 7266: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7267: * p.j overall mortality formula 49 but computed directly because
7268: * we compute the grad (wix pijx) instead of grad (pijx),even if
7269: * wix is independent of theta.
7270: */
1.218 brouard 7271: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7272: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7273: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7274: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7275: varppt[j][i]=doldmp[j][i];
7276: /* end ppptj */
7277: /* x centered again */
7278:
1.242 brouard 7279: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7280:
7281: if (popbased==1) {
7282: if(mobilav ==0){
7283: for(i=1; i<=nlstate;i++)
7284: prlim[i][i]=probs[(int)age][i][ij];
7285: }else{ /* mobilav */
7286: for(i=1; i<=nlstate;i++)
7287: prlim[i][i]=mobaverage[(int)age][i][ij];
7288: }
7289: }
7290:
7291: /* This for computing probability of death (h=1 means
7292: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7293: as a weighted average of prlim.
7294: */
1.235 brouard 7295: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7296: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7297: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7298: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7299: }
7300: /* end probability of death */
7301:
7302: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7303: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7304: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7305: for(i=1; i<=nlstate;i++){
7306: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7307: }
7308: }
7309: fprintf(ficresprobmorprev,"\n");
7310:
7311: fprintf(ficresvij,"%.0f ",age );
7312: for(i=1; i<=nlstate;i++)
7313: for(j=1; j<=nlstate;j++){
7314: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7315: }
7316: fprintf(ficresvij,"\n");
7317: free_matrix(gp,0,nhstepm,1,nlstate);
7318: free_matrix(gm,0,nhstepm,1,nlstate);
7319: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7320: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7321: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7322: } /* End age */
7323: free_vector(gpp,nlstate+1,nlstate+ndeath);
7324: free_vector(gmp,nlstate+1,nlstate+ndeath);
7325: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7326: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7327: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7328: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7329: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7330: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7331: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7332: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7333: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7334: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7335: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7336: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7337: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7338: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7339: 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);
7340: /* 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 7341: */
1.218 brouard 7342: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7343: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7344:
1.218 brouard 7345: free_vector(xp,1,npar);
7346: free_matrix(doldm,1,nlstate,1,nlstate);
7347: free_matrix(dnewm,1,nlstate,1,npar);
7348: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7349: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7350: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7351: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7352: fclose(ficresprobmorprev);
7353: fflush(ficgp);
7354: fflush(fichtm);
7355: } /* end varevsij */
1.126 brouard 7356:
7357: /************ Variance of prevlim ******************/
1.269 brouard 7358: 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 7359: {
1.205 brouard 7360: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7361: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7362:
1.268 brouard 7363: double **dnewmpar,**doldm;
1.126 brouard 7364: int i, j, nhstepm, hstepm;
7365: double *xp;
7366: double *gp, *gm;
7367: double **gradg, **trgradg;
1.208 brouard 7368: double **mgm, **mgp;
1.126 brouard 7369: double age,agelim;
7370: int theta;
7371:
7372: pstamp(ficresvpl);
1.288 brouard 7373: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7374: fprintf(ficresvpl,"# Age ");
7375: if(nresult >=1)
7376: fprintf(ficresvpl," Result# ");
1.126 brouard 7377: for(i=1; i<=nlstate;i++)
7378: fprintf(ficresvpl," %1d-%1d",i,i);
7379: fprintf(ficresvpl,"\n");
7380:
7381: xp=vector(1,npar);
1.268 brouard 7382: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7383: doldm=matrix(1,nlstate,1,nlstate);
7384:
7385: hstepm=1*YEARM; /* Every year of age */
7386: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7387: agelim = AGESUP;
7388: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7389: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7390: if (stepm >= YEARM) hstepm=1;
7391: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7392: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7393: mgp=matrix(1,npar,1,nlstate);
7394: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7395: gp=vector(1,nlstate);
7396: gm=vector(1,nlstate);
7397:
7398: for(theta=1; theta <=npar; theta++){
7399: for(i=1; i<=npar; i++){ /* Computes gradient */
7400: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7401: }
1.288 brouard 7402: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7403: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7404: /* else */
7405: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7406: for(i=1;i<=nlstate;i++){
1.126 brouard 7407: gp[i] = prlim[i][i];
1.208 brouard 7408: mgp[theta][i] = prlim[i][i];
7409: }
1.126 brouard 7410: for(i=1; i<=npar; i++) /* Computes gradient */
7411: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7412: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7413: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7414: /* else */
7415: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7416: for(i=1;i<=nlstate;i++){
1.126 brouard 7417: gm[i] = prlim[i][i];
1.208 brouard 7418: mgm[theta][i] = prlim[i][i];
7419: }
1.126 brouard 7420: for(i=1;i<=nlstate;i++)
7421: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7422: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7423: } /* End theta */
7424:
7425: trgradg =matrix(1,nlstate,1,npar);
7426:
7427: for(j=1; j<=nlstate;j++)
7428: for(theta=1; theta <=npar; theta++)
7429: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7430: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7431: /* printf("\nmgm mgp %d ",(int)age); */
7432: /* for(j=1; j<=nlstate;j++){ */
7433: /* printf(" %d ",j); */
7434: /* for(theta=1; theta <=npar; theta++) */
7435: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7436: /* printf("\n "); */
7437: /* } */
7438: /* } */
7439: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7440: /* printf("\n gradg %d ",(int)age); */
7441: /* for(j=1; j<=nlstate;j++){ */
7442: /* printf("%d ",j); */
7443: /* for(theta=1; theta <=npar; theta++) */
7444: /* printf("%d %lf ",theta,gradg[theta][j]); */
7445: /* printf("\n "); */
7446: /* } */
7447: /* } */
1.126 brouard 7448:
7449: for(i=1;i<=nlstate;i++)
7450: varpl[i][(int)age] =0.;
1.209 brouard 7451: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7452: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7453: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7454: }else{
1.268 brouard 7455: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7456: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7457: }
1.126 brouard 7458: for(i=1;i<=nlstate;i++)
7459: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7460:
7461: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7462: if(nresult >=1)
7463: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7464: for(i=1; i<=nlstate;i++){
1.126 brouard 7465: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7466: /* for(j=1;j<=nlstate;j++) */
7467: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7468: }
1.126 brouard 7469: fprintf(ficresvpl,"\n");
7470: free_vector(gp,1,nlstate);
7471: free_vector(gm,1,nlstate);
1.208 brouard 7472: free_matrix(mgm,1,npar,1,nlstate);
7473: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7474: free_matrix(gradg,1,npar,1,nlstate);
7475: free_matrix(trgradg,1,nlstate,1,npar);
7476: } /* End age */
7477:
7478: free_vector(xp,1,npar);
7479: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7480: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7481:
7482: }
7483:
7484:
7485: /************ Variance of backprevalence limit ******************/
1.269 brouard 7486: 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 7487: {
7488: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7489: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7490:
7491: double **dnewmpar,**doldm;
7492: int i, j, nhstepm, hstepm;
7493: double *xp;
7494: double *gp, *gm;
7495: double **gradg, **trgradg;
7496: double **mgm, **mgp;
7497: double age,agelim;
7498: int theta;
7499:
7500: pstamp(ficresvbl);
7501: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7502: fprintf(ficresvbl,"# Age ");
7503: if(nresult >=1)
7504: fprintf(ficresvbl," Result# ");
7505: for(i=1; i<=nlstate;i++)
7506: fprintf(ficresvbl," %1d-%1d",i,i);
7507: fprintf(ficresvbl,"\n");
7508:
7509: xp=vector(1,npar);
7510: dnewmpar=matrix(1,nlstate,1,npar);
7511: doldm=matrix(1,nlstate,1,nlstate);
7512:
7513: hstepm=1*YEARM; /* Every year of age */
7514: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7515: agelim = AGEINF;
7516: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7517: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7518: if (stepm >= YEARM) hstepm=1;
7519: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7520: gradg=matrix(1,npar,1,nlstate);
7521: mgp=matrix(1,npar,1,nlstate);
7522: mgm=matrix(1,npar,1,nlstate);
7523: gp=vector(1,nlstate);
7524: gm=vector(1,nlstate);
7525:
7526: for(theta=1; theta <=npar; theta++){
7527: for(i=1; i<=npar; i++){ /* Computes gradient */
7528: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7529: }
7530: if(mobilavproj > 0 )
7531: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7532: else
7533: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7534: for(i=1;i<=nlstate;i++){
7535: gp[i] = bprlim[i][i];
7536: mgp[theta][i] = bprlim[i][i];
7537: }
7538: for(i=1; i<=npar; i++) /* Computes gradient */
7539: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7540: if(mobilavproj > 0 )
7541: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7542: else
7543: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7544: for(i=1;i<=nlstate;i++){
7545: gm[i] = bprlim[i][i];
7546: mgm[theta][i] = bprlim[i][i];
7547: }
7548: for(i=1;i<=nlstate;i++)
7549: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7550: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7551: } /* End theta */
7552:
7553: trgradg =matrix(1,nlstate,1,npar);
7554:
7555: for(j=1; j<=nlstate;j++)
7556: for(theta=1; theta <=npar; theta++)
7557: trgradg[j][theta]=gradg[theta][j];
7558: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7559: /* printf("\nmgm mgp %d ",(int)age); */
7560: /* for(j=1; j<=nlstate;j++){ */
7561: /* printf(" %d ",j); */
7562: /* for(theta=1; theta <=npar; theta++) */
7563: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7564: /* printf("\n "); */
7565: /* } */
7566: /* } */
7567: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7568: /* printf("\n gradg %d ",(int)age); */
7569: /* for(j=1; j<=nlstate;j++){ */
7570: /* printf("%d ",j); */
7571: /* for(theta=1; theta <=npar; theta++) */
7572: /* printf("%d %lf ",theta,gradg[theta][j]); */
7573: /* printf("\n "); */
7574: /* } */
7575: /* } */
7576:
7577: for(i=1;i<=nlstate;i++)
7578: varbpl[i][(int)age] =0.;
7579: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7580: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7581: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7582: }else{
7583: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7584: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7585: }
7586: for(i=1;i<=nlstate;i++)
7587: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7588:
7589: fprintf(ficresvbl,"%.0f ",age );
7590: if(nresult >=1)
7591: fprintf(ficresvbl,"%d ",nres );
7592: for(i=1; i<=nlstate;i++)
7593: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7594: fprintf(ficresvbl,"\n");
7595: free_vector(gp,1,nlstate);
7596: free_vector(gm,1,nlstate);
7597: free_matrix(mgm,1,npar,1,nlstate);
7598: free_matrix(mgp,1,npar,1,nlstate);
7599: free_matrix(gradg,1,npar,1,nlstate);
7600: free_matrix(trgradg,1,nlstate,1,npar);
7601: } /* End age */
7602:
7603: free_vector(xp,1,npar);
7604: free_matrix(doldm,1,nlstate,1,npar);
7605: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7606:
7607: }
7608:
7609: /************ Variance of one-step probabilities ******************/
7610: 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 7611: {
7612: int i, j=0, k1, l1, tj;
7613: int k2, l2, j1, z1;
7614: int k=0, l;
7615: int first=1, first1, first2;
1.326 brouard 7616: int nres=0; /* New */
1.222 brouard 7617: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7618: double **dnewm,**doldm;
7619: double *xp;
7620: double *gp, *gm;
7621: double **gradg, **trgradg;
7622: double **mu;
7623: double age, cov[NCOVMAX+1];
7624: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7625: int theta;
7626: char fileresprob[FILENAMELENGTH];
7627: char fileresprobcov[FILENAMELENGTH];
7628: char fileresprobcor[FILENAMELENGTH];
7629: double ***varpij;
7630:
7631: strcpy(fileresprob,"PROB_");
1.356 ! brouard 7632: strcat(fileresprob,fileresu);
1.222 brouard 7633: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7634: printf("Problem with resultfile: %s\n", fileresprob);
7635: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7636: }
7637: strcpy(fileresprobcov,"PROBCOV_");
7638: strcat(fileresprobcov,fileresu);
7639: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7640: printf("Problem with resultfile: %s\n", fileresprobcov);
7641: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7642: }
7643: strcpy(fileresprobcor,"PROBCOR_");
7644: strcat(fileresprobcor,fileresu);
7645: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7646: printf("Problem with resultfile: %s\n", fileresprobcor);
7647: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7648: }
7649: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7650: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7651: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7652: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7653: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7654: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7655: pstamp(ficresprob);
7656: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7657: fprintf(ficresprob,"# Age");
7658: pstamp(ficresprobcov);
7659: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7660: fprintf(ficresprobcov,"# Age");
7661: pstamp(ficresprobcor);
7662: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7663: fprintf(ficresprobcor,"# Age");
1.126 brouard 7664:
7665:
1.222 brouard 7666: for(i=1; i<=nlstate;i++)
7667: for(j=1; j<=(nlstate+ndeath);j++){
7668: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7669: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7670: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7671: }
7672: /* fprintf(ficresprob,"\n");
7673: fprintf(ficresprobcov,"\n");
7674: fprintf(ficresprobcor,"\n");
7675: */
7676: xp=vector(1,npar);
7677: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7678: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7679: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7680: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7681: first=1;
7682: fprintf(ficgp,"\n# Routine varprob");
7683: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7684: fprintf(fichtm,"\n");
7685:
1.288 brouard 7686: 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 7687: 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);
7688: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7689: and drawn. It helps understanding how is the covariance between two incidences.\
7690: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7691: 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 7692: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7693: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7694: standard deviations wide on each axis. <br>\
7695: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7696: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7697: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7698:
1.222 brouard 7699: cov[1]=1;
7700: /* tj=cptcoveff; */
1.225 brouard 7701: tj = (int) pow(2,cptcoveff);
1.222 brouard 7702: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7703: j1=0;
1.332 brouard 7704:
7705: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7706: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7707: /* 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 7708: if(tj != 1 && TKresult[nres]!= j1)
7709: continue;
7710:
7711: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7712: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7713: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7714: if (cptcovn>0) {
1.334 brouard 7715: fprintf(ficresprob, "\n#********** Variable ");
7716: fprintf(ficresprobcov, "\n#********** Variable ");
7717: fprintf(ficgp, "\n#********** Variable ");
7718: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7719: fprintf(ficresprobcor, "\n#********** Variable ");
7720:
7721: /* Including quantitative variables of the resultline to be done */
7722: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7723: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7724: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7725: /* 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 7726: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7727: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7728: 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 */
7729: 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 */
7730: 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 */
7731: 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 */
7732: 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 */
7733: fprintf(ficresprob,"fixed ");
7734: fprintf(ficresprobcov,"fixed ");
7735: fprintf(ficgp,"fixed ");
7736: fprintf(fichtmcov,"fixed ");
7737: fprintf(ficresprobcor,"fixed ");
7738: }else{
7739: fprintf(ficresprob,"varyi ");
7740: fprintf(ficresprobcov,"varyi ");
7741: fprintf(ficgp,"varyi ");
7742: fprintf(fichtmcov,"varyi ");
7743: fprintf(ficresprobcor,"varyi ");
7744: }
7745: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7746: /* For each selected (single) quantitative value */
1.337 brouard 7747: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7748: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7749: fprintf(ficresprob,"fixed ");
7750: fprintf(ficresprobcov,"fixed ");
7751: fprintf(ficgp,"fixed ");
7752: fprintf(fichtmcov,"fixed ");
7753: fprintf(ficresprobcor,"fixed ");
7754: }else{
7755: fprintf(ficresprob,"varyi ");
7756: fprintf(ficresprobcov,"varyi ");
7757: fprintf(ficgp,"varyi ");
7758: fprintf(fichtmcov,"varyi ");
7759: fprintf(ficresprobcor,"varyi ");
7760: }
7761: }else{
7762: 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 */
7763: 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 */
7764: exit(1);
7765: }
7766: } /* End loop on variable of this resultline */
7767: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7768: fprintf(ficresprob, "**********\n#\n");
7769: fprintf(ficresprobcov, "**********\n#\n");
7770: fprintf(ficgp, "**********\n#\n");
7771: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7772: fprintf(ficresprobcor, "**********\n#");
7773: if(invalidvarcomb[j1]){
7774: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7775: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7776: continue;
7777: }
7778: }
7779: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7780: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7781: gp=vector(1,(nlstate)*(nlstate+ndeath));
7782: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7783: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7784: cov[2]=age;
7785: if(nagesqr==1)
7786: cov[3]= age*age;
1.334 brouard 7787: /* New code end of combination but for each resultline */
7788: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 7789: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7790: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7791: }else{
1.334 brouard 7792: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7793: }
1.334 brouard 7794: }/* End of loop on model equation */
7795: /* Old code */
7796: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7797: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7798: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7799: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7800: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7801: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7802: /* * 1 1 1 1 1 */
7803: /* * 2 2 1 1 1 */
7804: /* * 3 1 2 1 1 */
7805: /* *\/ */
7806: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7807: /* } */
7808: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7809: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7810: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7811: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7812: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7813: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7814: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7815: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7816: /* 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]); */
7817: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7818: /* /\* exit(1); *\/ */
7819: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7820: /* } */
7821: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7822: /* } */
7823: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7824: /* if(Dummy[Tvard[k][1]]==0){ */
7825: /* if(Dummy[Tvard[k][2]]==0){ */
7826: /* 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]])]; */
7827: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7828: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7829: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7830: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7831: /* } */
7832: /* }else{ */
7833: /* if(Dummy[Tvard[k][2]]==0){ */
7834: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7835: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7836: /* }else{ */
7837: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7838: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7839: /* } */
7840: /* } */
7841: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7842: /* } */
1.326 brouard 7843: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7844: for(theta=1; theta <=npar; theta++){
7845: for(i=1; i<=npar; i++)
7846: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7847:
1.222 brouard 7848: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7849:
1.222 brouard 7850: k=0;
7851: for(i=1; i<= (nlstate); i++){
7852: for(j=1; j<=(nlstate+ndeath);j++){
7853: k=k+1;
7854: gp[k]=pmmij[i][j];
7855: }
7856: }
1.220 brouard 7857:
1.222 brouard 7858: for(i=1; i<=npar; i++)
7859: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7860:
1.222 brouard 7861: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7862: k=0;
7863: for(i=1; i<=(nlstate); i++){
7864: for(j=1; j<=(nlstate+ndeath);j++){
7865: k=k+1;
7866: gm[k]=pmmij[i][j];
7867: }
7868: }
1.220 brouard 7869:
1.222 brouard 7870: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7871: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7872: }
1.126 brouard 7873:
1.222 brouard 7874: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7875: for(theta=1; theta <=npar; theta++)
7876: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7877:
1.222 brouard 7878: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7879: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7880:
1.222 brouard 7881: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7882:
1.222 brouard 7883: k=0;
7884: for(i=1; i<=(nlstate); i++){
7885: for(j=1; j<=(nlstate+ndeath);j++){
7886: k=k+1;
7887: mu[k][(int) age]=pmmij[i][j];
7888: }
7889: }
7890: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7891: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7892: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7893:
1.222 brouard 7894: /*printf("\n%d ",(int)age);
7895: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7896: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7897: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7898: }*/
1.220 brouard 7899:
1.222 brouard 7900: fprintf(ficresprob,"\n%d ",(int)age);
7901: fprintf(ficresprobcov,"\n%d ",(int)age);
7902: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7903:
1.222 brouard 7904: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7905: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7906: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7907: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7908: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7909: }
7910: i=0;
7911: for (k=1; k<=(nlstate);k++){
7912: for (l=1; l<=(nlstate+ndeath);l++){
7913: i++;
7914: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7915: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7916: for (j=1; j<=i;j++){
7917: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7918: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7919: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7920: }
7921: }
7922: }/* end of loop for state */
7923: } /* end of loop for age */
7924: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7925: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7926: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7927: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7928:
7929: /* Confidence intervalle of pij */
7930: /*
7931: fprintf(ficgp,"\nunset parametric;unset label");
7932: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7933: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7934: 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);
7935: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7936: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7937: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7938: */
7939:
7940: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7941: first1=1;first2=2;
7942: for (k2=1; k2<=(nlstate);k2++){
7943: for (l2=1; l2<=(nlstate+ndeath);l2++){
7944: if(l2==k2) continue;
7945: j=(k2-1)*(nlstate+ndeath)+l2;
7946: for (k1=1; k1<=(nlstate);k1++){
7947: for (l1=1; l1<=(nlstate+ndeath);l1++){
7948: if(l1==k1) continue;
7949: i=(k1-1)*(nlstate+ndeath)+l1;
7950: if(i<=j) continue;
7951: for (age=bage; age<=fage; age ++){
7952: if ((int)age %5==0){
7953: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7954: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7955: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7956: mu1=mu[i][(int) age]/stepm*YEARM ;
7957: mu2=mu[j][(int) age]/stepm*YEARM;
7958: c12=cv12/sqrt(v1*v2);
7959: /* Computing eigen value of matrix of covariance */
7960: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7961: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7962: if ((lc2 <0) || (lc1 <0) ){
7963: if(first2==1){
7964: first1=0;
7965: 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);
7966: }
7967: 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);
7968: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7969: /* lc2=fabs(lc2); */
7970: }
1.220 brouard 7971:
1.222 brouard 7972: /* Eigen vectors */
1.280 brouard 7973: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7974: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7975: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7976: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7977: }else
7978: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7979: /*v21=sqrt(1.-v11*v11); *//* error */
7980: v21=(lc1-v1)/cv12*v11;
7981: v12=-v21;
7982: v22=v11;
7983: tnalp=v21/v11;
7984: if(first1==1){
7985: first1=0;
7986: 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);
7987: }
7988: 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);
7989: /*printf(fignu*/
7990: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7991: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7992: if(first==1){
7993: first=0;
7994: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7995: fprintf(ficgp,"\nset parametric;unset label");
7996: 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);
7997: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7998: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7999: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 8000: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 8001: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
8002: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8003: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8004: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
8005: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8006: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
8007: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
8008: 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 8009: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
8010: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 8011: }else{
8012: first=0;
8013: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
8014: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
8015: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
8016: 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 8017: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
8018: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 8019: }/* if first */
8020: } /* age mod 5 */
8021: } /* end loop age */
8022: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8023: first=1;
8024: } /*l12 */
8025: } /* k12 */
8026: } /*l1 */
8027: }/* k1 */
1.332 brouard 8028: } /* loop on combination of covariates j1 */
1.326 brouard 8029: } /* loop on nres */
1.222 brouard 8030: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
8031: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
8032: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
8033: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
8034: free_vector(xp,1,npar);
8035: fclose(ficresprob);
8036: fclose(ficresprobcov);
8037: fclose(ficresprobcor);
8038: fflush(ficgp);
8039: fflush(fichtmcov);
8040: }
1.126 brouard 8041:
8042:
8043: /******************* Printing html file ***********/
1.201 brouard 8044: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8045: int lastpass, int stepm, int weightopt, char model[],\
8046: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 8047: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
8048: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
8049: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 8050: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 8051: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8052: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8053: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8054: </ul>");
1.319 brouard 8055: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8056: /* </ul>", model); */
1.214 brouard 8057: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8058: 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",
8059: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8060: 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 8061: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8062: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8063: fprintf(fichtm,"\
8064: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8065: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8066: fprintf(fichtm,"\
1.217 brouard 8067: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8068: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8069: fprintf(fichtm,"\
1.288 brouard 8070: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8071: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8072: fprintf(fichtm,"\
1.288 brouard 8073: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8074: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8075: fprintf(fichtm,"\
1.211 brouard 8076: - (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 8077: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8078: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8079: if(prevfcast==1){
8080: fprintf(fichtm,"\
8081: - Prevalence projections by age and states: \
1.201 brouard 8082: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8083: }
1.126 brouard 8084:
8085:
1.225 brouard 8086: m=pow(2,cptcoveff);
1.222 brouard 8087: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8088:
1.317 brouard 8089: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8090:
8091: jj1=0;
8092:
8093: fprintf(fichtm," \n<ul>");
1.337 brouard 8094: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8095: /* k1=nres; */
1.338 brouard 8096: k1=TKresult[nres];
8097: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8098: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8099: /* if(m != 1 && TKresult[nres]!= k1) */
8100: /* continue; */
1.264 brouard 8101: jj1++;
8102: if (cptcovn > 0) {
8103: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8104: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8105: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8106: }
1.337 brouard 8107: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8108: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8109: /* } */
8110: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8111: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8112: /* } */
1.264 brouard 8113: fprintf(fichtm,"\">");
8114:
8115: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8116: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8117: for (cpt=1; cpt<=cptcovs;cpt++){
8118: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8119: }
1.337 brouard 8120: /* fprintf(fichtm,"************ Results for covariates"); */
8121: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8122: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8123: /* } */
8124: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8125: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8126: /* } */
1.264 brouard 8127: if(invalidvarcomb[k1]){
8128: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8129: continue;
8130: }
8131: fprintf(fichtm,"</a></li>");
8132: } /* cptcovn >0 */
8133: }
1.317 brouard 8134: fprintf(fichtm," \n</ul>");
1.264 brouard 8135:
1.222 brouard 8136: jj1=0;
1.237 brouard 8137:
1.337 brouard 8138: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8139: /* k1=nres; */
1.338 brouard 8140: k1=TKresult[nres];
8141: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8142: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8143: /* if(m != 1 && TKresult[nres]!= k1) */
8144: /* continue; */
1.220 brouard 8145:
1.222 brouard 8146: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8147: jj1++;
8148: if (cptcovn > 0) {
1.264 brouard 8149: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8150: for (cpt=1; cpt<=cptcovs;cpt++){
8151: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8152: }
1.337 brouard 8153: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8154: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8155: /* } */
1.264 brouard 8156: fprintf(fichtm,"\"</a>");
8157:
1.222 brouard 8158: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8159: for (cpt=1; cpt<=cptcovs;cpt++){
8160: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8161: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8162: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8163: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8164: }
1.230 brouard 8165: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8166: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8167: if(invalidvarcomb[k1]){
8168: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8169: printf("\nCombination (%d) ignored because no cases \n",k1);
8170: continue;
8171: }
8172: }
8173: /* aij, bij */
1.259 brouard 8174: 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 8175: <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 8176: /* Pij */
1.241 brouard 8177: 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> \
8178: <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 8179: /* Quasi-incidences */
8180: 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 8181: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8182: 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 8183: 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> \
8184: <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 8185: /* Survival functions (period) in state j */
8186: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8187: 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. <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);
8188: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8189: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8190: }
8191: /* State specific survival functions (period) */
8192: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8193: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8194: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8195: <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);
8196: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8197: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8198: }
1.288 brouard 8199: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8200: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8201: 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 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 8202: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8203: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8204: }
1.296 brouard 8205: if(prevbcast==1){
1.288 brouard 8206: /* Backward prevalence in each health state */
1.222 brouard 8207: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8208: 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);
8209: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8210: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8211: }
1.217 brouard 8212: }
1.222 brouard 8213: if(prevfcast==1){
1.288 brouard 8214: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8215: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8216: 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);
8217: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8218: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8219: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8220: }
8221: }
1.296 brouard 8222: if(prevbcast==1){
1.268 brouard 8223: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8224: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8225: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8226: 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 \
8227: 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 8228: 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);
8229: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8230: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8231: }
8232: }
1.220 brouard 8233:
1.222 brouard 8234: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8235: 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);
8236: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8237: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8238: }
8239: /* } /\* end i1 *\/ */
1.337 brouard 8240: }/* End k1=nres */
1.222 brouard 8241: fprintf(fichtm,"</ul>");
1.126 brouard 8242:
1.222 brouard 8243: fprintf(fichtm,"\
1.126 brouard 8244: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8245: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8246: - 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 8247: But because parameters are usually highly correlated (a higher incidence of disability \
8248: and a higher incidence of recovery can give very close observed transition) it might \
8249: be very useful to look not only at linear confidence intervals estimated from the \
8250: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8251: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8252: covariance matrix of the one-step probabilities. \
8253: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8254:
1.222 brouard 8255: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8256: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8257: fprintf(fichtm,"\
1.126 brouard 8258: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8259: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8260:
1.222 brouard 8261: fprintf(fichtm,"\
1.126 brouard 8262: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8263: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8264: fprintf(fichtm,"\
1.126 brouard 8265: - 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): \
8266: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8267: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8268: fprintf(fichtm,"\
1.126 brouard 8269: - (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): \
8270: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8271: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8272: fprintf(fichtm,"\
1.288 brouard 8273: - 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 8274: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8275: fprintf(fichtm,"\
1.128 brouard 8276: - 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 8277: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8278: fprintf(fichtm,"\
1.288 brouard 8279: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8280: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8281:
8282: /* if(popforecast==1) fprintf(fichtm,"\n */
8283: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8284: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8285: /* <br>",fileres,fileres,fileres,fileres); */
8286: /* else */
1.338 brouard 8287: /* 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 8288: fflush(fichtm);
1.126 brouard 8289:
1.225 brouard 8290: m=pow(2,cptcoveff);
1.222 brouard 8291: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8292:
1.317 brouard 8293: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8294:
8295: jj1=0;
8296:
8297: fprintf(fichtm," \n<ul>");
1.337 brouard 8298: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8299: /* k1=nres; */
1.338 brouard 8300: k1=TKresult[nres];
1.337 brouard 8301: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8302: /* if(m != 1 && TKresult[nres]!= k1) */
8303: /* continue; */
1.317 brouard 8304: jj1++;
8305: if (cptcovn > 0) {
8306: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8307: for (cpt=1; cpt<=cptcovs;cpt++){
8308: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8309: }
8310: fprintf(fichtm,"\">");
8311:
8312: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8313: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8314: for (cpt=1; cpt<=cptcovs;cpt++){
8315: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8316: }
8317: if(invalidvarcomb[k1]){
8318: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8319: continue;
8320: }
8321: fprintf(fichtm,"</a></li>");
8322: } /* cptcovn >0 */
1.337 brouard 8323: } /* End nres */
1.317 brouard 8324: fprintf(fichtm," \n</ul>");
8325:
1.222 brouard 8326: jj1=0;
1.237 brouard 8327:
1.241 brouard 8328: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8329: /* k1=nres; */
1.338 brouard 8330: k1=TKresult[nres];
8331: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8332: /* for(k1=1; k1<=m;k1++){ */
8333: /* if(m != 1 && TKresult[nres]!= k1) */
8334: /* continue; */
1.222 brouard 8335: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8336: jj1++;
1.126 brouard 8337: if (cptcovn > 0) {
1.317 brouard 8338: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8339: for (cpt=1; cpt<=cptcovs;cpt++){
8340: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8341: }
8342: fprintf(fichtm,"\"</a>");
8343:
1.126 brouard 8344: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8345: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8346: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8347: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8348: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8349: }
1.237 brouard 8350:
1.338 brouard 8351: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8352:
1.222 brouard 8353: if(invalidvarcomb[k1]){
8354: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8355: continue;
8356: }
1.337 brouard 8357: } /* If cptcovn >0 */
1.126 brouard 8358: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8359: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8360: 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);
8361: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8362: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8363: }
8364: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8365: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8366: true period expectancies (those weighted with period prevalences are also\
8367: drawn in addition to the population based expectancies computed using\
1.314 brouard 8368: 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);
8369: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8370: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8371: /* } /\* end i1 *\/ */
1.241 brouard 8372: }/* End nres */
1.222 brouard 8373: fprintf(fichtm,"</ul>");
8374: fflush(fichtm);
1.126 brouard 8375: }
8376:
8377: /******************* Gnuplot file **************/
1.296 brouard 8378: 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 8379:
1.354 brouard 8380: char dirfileres[256],optfileres[256];
8381: char gplotcondition[256], gplotlabel[256];
1.343 brouard 8382: 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 8383: int lv=0, vlv=0, kl=0;
1.130 brouard 8384: int ng=0;
1.201 brouard 8385: int vpopbased;
1.223 brouard 8386: int ioffset; /* variable offset for columns */
1.270 brouard 8387: int iyearc=1; /* variable column for year of projection */
8388: int iagec=1; /* variable column for age of projection */
1.235 brouard 8389: int nres=0; /* Index of resultline */
1.266 brouard 8390: int istart=1; /* For starting graphs in projections */
1.219 brouard 8391:
1.126 brouard 8392: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8393: /* printf("Problem with file %s",optionfilegnuplot); */
8394: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8395: /* } */
8396:
8397: /*#ifdef windows */
8398: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8399: /*#endif */
1.225 brouard 8400: m=pow(2,cptcoveff);
1.126 brouard 8401:
1.274 brouard 8402: /* diagram of the model */
8403: fprintf(ficgp,"\n#Diagram of the model \n");
8404: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8405: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8406: 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);
8407:
1.343 brouard 8408: 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 8409: fprintf(ficgp,"\n#show arrow\nunset label\n");
8410: 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);
8411: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8412: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8413: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8414: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8415:
1.202 brouard 8416: /* Contribution to likelihood */
8417: /* Plot the probability implied in the likelihood */
1.223 brouard 8418: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8419: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8420: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8421: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8422: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8423: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8424: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8425: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8426: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8427: 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));
8428: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8429: 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));
8430: for (i=1; i<= nlstate ; i ++) {
8431: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8432: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8433: 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);
8434: for (j=2; j<= nlstate+ndeath ; j ++) {
8435: 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);
8436: }
8437: fprintf(ficgp,";\nset out; unset ylabel;\n");
8438: }
8439: /* 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 */
8440: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8441: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8442: fprintf(ficgp,"\nset out;unset log\n");
8443: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8444:
1.343 brouard 8445: /* Plot the probability implied in the likelihood by covariate value */
8446: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8447: /* if(debugILK==1){ */
8448: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8449: kvar=Tvar[TvarFind[kf]]; /* variable name */
8450: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 8451: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
1.356 ! brouard 8452: /* k=19+kf;/\*offset because there are 19 columns in the ILK_ file *\/ */
1.355 brouard 8453: 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 8454: for (i=1; i<= nlstate ; i ++) {
8455: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8456: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8457: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8458: 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);
8459: for (j=2; j<= nlstate+ndeath ; j ++) {
8460: 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);
8461: }
8462: }else{
8463: 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);
8464: for (j=2; j<= nlstate+ndeath ; j ++) {
8465: 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);
8466: }
1.343 brouard 8467: }
8468: fprintf(ficgp,";\nset out; unset ylabel;\n");
8469: }
8470: } /* End of each covariate dummy */
8471: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8472: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8473: * kmodel = 1 2 3 4 5 6 7 8 9
8474: * varying 1 2 3 4 5
8475: * ncovv 1 2 3 4 5 6 7 8
8476: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8477: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8478: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8479: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8480: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8481: */
8482: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8483: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8484: /* 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]); */
8485: if(ipos!=iposold){ /* Not a product or first of a product */
8486: /* printf(" %d",ipos); */
8487: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8488: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8489: kk++; /* Position of the ncovv column in ILK_ */
8490: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8491: 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) */
8492: for (i=1; i<= nlstate ; i ++) {
8493: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8494: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8495:
1.348 brouard 8496: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8497: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8498: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8499: 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);
8500: for (j=2; j<= nlstate+ndeath ; j ++) {
8501: 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);
8502: }
8503: }else{
8504: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8505: 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);
8506: for (j=2; j<= nlstate+ndeath ; j ++) {
8507: 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);
8508: }
8509: }
8510: fprintf(ficgp,";\nset out; unset ylabel;\n");
8511: }
8512: }/* End if dummy varying */
8513: }else{ /*Product */
8514: /* printf("*"); */
8515: /* fprintf(ficresilk,"*"); */
8516: }
8517: iposold=ipos;
8518: } /* For each time varying covariate */
8519: /* } /\* debugILK==1 *\/ */
8520: /* 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 */
8521: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8522: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8523: fprintf(ficgp,"\nset out;unset log\n");
8524: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8525:
8526:
8527:
1.126 brouard 8528: strcpy(dirfileres,optionfilefiname);
8529: strcpy(optfileres,"vpl");
1.223 brouard 8530: /* 1eme*/
1.238 brouard 8531: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8532: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8533: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8534: k1=TKresult[nres];
1.338 brouard 8535: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8536: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8537: /* if(m != 1 && TKresult[nres]!= k1) */
8538: /* continue; */
1.238 brouard 8539: /* We are interested in selected combination by the resultline */
1.246 brouard 8540: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8541: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8542: strcpy(gplotlabel,"(");
1.337 brouard 8543: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8544: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8545: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8546:
8547: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8548: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8549: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8550: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8551: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8552: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8553: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8554: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8555: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8556: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8557: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8558: /* } */
8559: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8560: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8561: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8562: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8563: }
8564: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8565: /* printf("\n#\n"); */
1.238 brouard 8566: fprintf(ficgp,"\n#\n");
8567: if(invalidvarcomb[k1]){
1.260 brouard 8568: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8569: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8570: continue;
8571: }
1.235 brouard 8572:
1.241 brouard 8573: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8574: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8575: /* 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 8576: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8577: 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);
8578: /* 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); */
8579: /* k1-1 error should be nres-1*/
1.238 brouard 8580: for (i=1; i<= nlstate ; i ++) {
8581: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8582: else fprintf(ficgp," %%*lf (%%*lf)");
8583: }
1.288 brouard 8584: 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 8585: for (i=1; i<= nlstate ; i ++) {
8586: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8587: else fprintf(ficgp," %%*lf (%%*lf)");
8588: }
1.260 brouard 8589: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8590: for (i=1; i<= nlstate ; i ++) {
8591: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8592: else fprintf(ficgp," %%*lf (%%*lf)");
8593: }
1.265 brouard 8594: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8595:
8596: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8597: if(cptcoveff ==0){
1.271 brouard 8598: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8599: }else{
8600: kl=0;
8601: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8602: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8603: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8604: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8605: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8606: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8607: vlv= nbcode[Tvaraff[k]][lv];
8608: kl++;
8609: /* 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 *\/ */
8610: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8611: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8612: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8613: if(k==cptcoveff){
8614: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8615: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8616: }else{
8617: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8618: kl++;
8619: }
8620: } /* end covariate */
8621: } /* end if no covariate */
8622:
1.296 brouard 8623: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8624: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8625: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8626: if(cptcoveff ==0){
1.245 brouard 8627: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8628: }else{
8629: kl=0;
8630: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8631: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8632: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8633: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8634: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8635: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8636: /* vlv= nbcode[Tvaraff[k]][lv]; */
8637: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8638: kl++;
1.238 brouard 8639: /* 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 *\/ */
8640: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8641: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8642: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8643: if(k==cptcoveff){
1.245 brouard 8644: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8645: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8646: }else{
1.332 brouard 8647: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8648: kl++;
8649: }
8650: } /* end covariate */
8651: } /* end if no covariate */
1.296 brouard 8652: if(prevbcast == 1){
1.268 brouard 8653: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8654: /* k1-1 error should be nres-1*/
8655: for (i=1; i<= nlstate ; i ++) {
8656: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8657: else fprintf(ficgp," %%*lf (%%*lf)");
8658: }
1.271 brouard 8659: 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 8660: for (i=1; i<= nlstate ; i ++) {
8661: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8662: else fprintf(ficgp," %%*lf (%%*lf)");
8663: }
1.276 brouard 8664: 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 8665: for (i=1; i<= nlstate ; i ++) {
8666: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8667: else fprintf(ficgp," %%*lf (%%*lf)");
8668: }
1.274 brouard 8669: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8670: } /* end if backprojcast */
1.296 brouard 8671: } /* end if prevbcast */
1.276 brouard 8672: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8673: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8674: } /* nres */
1.337 brouard 8675: /* } /\* k1 *\/ */
1.201 brouard 8676: } /* cpt */
1.235 brouard 8677:
8678:
1.126 brouard 8679: /*2 eme*/
1.337 brouard 8680: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8681: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8682: k1=TKresult[nres];
1.338 brouard 8683: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8684: /* if(m != 1 && TKresult[nres]!= k1) */
8685: /* continue; */
1.238 brouard 8686: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8687: strcpy(gplotlabel,"(");
1.337 brouard 8688: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8689: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8690: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8691: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8692: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8693: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8694: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8695: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8696: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8697: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8698: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8699: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8700: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8701: /* } */
8702: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8703: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8704: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8705: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8706: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8707: }
1.264 brouard 8708: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8709: fprintf(ficgp,"\n#\n");
1.223 brouard 8710: if(invalidvarcomb[k1]){
8711: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8712: continue;
8713: }
1.219 brouard 8714:
1.241 brouard 8715: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8716: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8717: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8718: if(vpopbased==0){
1.238 brouard 8719: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8720: }else
1.238 brouard 8721: fprintf(ficgp,"\nreplot ");
8722: for (i=1; i<= nlstate+1 ; i ++) {
8723: k=2*i;
1.261 brouard 8724: 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);
1.238 brouard 8725: for (j=1; j<= nlstate+1 ; j ++) {
8726: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8727: else fprintf(ficgp," %%*lf (%%*lf)");
8728: }
8729: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8730: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8731: 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 8732: for (j=1; j<= nlstate+1 ; j ++) {
8733: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8734: else fprintf(ficgp," %%*lf (%%*lf)");
8735: }
8736: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8737: 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 8738: for (j=1; j<= nlstate+1 ; j ++) {
8739: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8740: else fprintf(ficgp," %%*lf (%%*lf)");
8741: }
8742: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8743: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8744: } /* state */
8745: } /* vpopbased */
1.264 brouard 8746: 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 8747: } /* end nres */
1.337 brouard 8748: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8749:
8750:
8751: /*3eme*/
1.337 brouard 8752: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8753: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8754: k1=TKresult[nres];
1.338 brouard 8755: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8756: /* if(m != 1 && TKresult[nres]!= k1) */
8757: /* continue; */
1.238 brouard 8758:
1.332 brouard 8759: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8760: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8761: strcpy(gplotlabel,"(");
1.337 brouard 8762: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8763: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8764: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8765: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8766: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8767: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8768: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8769: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8770: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8771: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8772: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8773: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8774: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8775: /* } */
8776: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8777: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8778: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8779: }
1.264 brouard 8780: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8781: fprintf(ficgp,"\n#\n");
8782: if(invalidvarcomb[k1]){
8783: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8784: continue;
8785: }
8786:
8787: /* k=2+nlstate*(2*cpt-2); */
8788: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8789: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8790: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8791: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8792: 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 8793: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8794: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8795: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8796: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8797: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8798: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8799:
1.238 brouard 8800: */
8801: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8802: 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 8803: /* 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 8804:
1.238 brouard 8805: }
1.261 brouard 8806: 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 8807: }
1.264 brouard 8808: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8809: } /* end nres */
1.337 brouard 8810: /* } /\* end kl 3eme *\/ */
1.126 brouard 8811:
1.223 brouard 8812: /* 4eme */
1.201 brouard 8813: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8814: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8815: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8816: k1=TKresult[nres];
1.338 brouard 8817: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8818: /* if(m != 1 && TKresult[nres]!= k1) */
8819: /* continue; */
1.238 brouard 8820: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8821: strcpy(gplotlabel,"(");
1.337 brouard 8822: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8823: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8824: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8825: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8826: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8827: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8828: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8829: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8830: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8831: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8832: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8833: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8834: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8835: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8836: /* } */
8837: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8838: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8839: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8840: }
1.264 brouard 8841: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8842: fprintf(ficgp,"\n#\n");
8843: if(invalidvarcomb[k1]){
8844: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8845: continue;
1.223 brouard 8846: }
1.238 brouard 8847:
1.241 brouard 8848: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8849: 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 8850: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8851: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8852: k=3;
8853: for (i=1; i<= nlstate ; i ++){
8854: if(i==1){
8855: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8856: }else{
8857: fprintf(ficgp,", '' ");
8858: }
8859: l=(nlstate+ndeath)*(i-1)+1;
8860: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8861: for (j=2; j<= nlstate+ndeath ; j ++)
8862: fprintf(ficgp,"+$%d",k+l+j-1);
8863: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8864: } /* nlstate */
1.264 brouard 8865: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8866: } /* end cpt state*/
8867: } /* end nres */
1.337 brouard 8868: /* } /\* end covariate k1 *\/ */
1.238 brouard 8869:
1.220 brouard 8870: /* 5eme */
1.201 brouard 8871: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8872: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8873: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8874: k1=TKresult[nres];
1.338 brouard 8875: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8876: /* if(m != 1 && TKresult[nres]!= k1) */
8877: /* continue; */
1.238 brouard 8878: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8879: strcpy(gplotlabel,"(");
1.238 brouard 8880: 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 8881: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8882: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8883: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8884: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8885: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8886: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8887: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8888: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8889: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8890: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8891: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8892: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8893: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8894: /* } */
8895: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8896: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8897: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8898: }
1.264 brouard 8899: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8900: fprintf(ficgp,"\n#\n");
8901: if(invalidvarcomb[k1]){
8902: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8903: continue;
8904: }
1.227 brouard 8905:
1.241 brouard 8906: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8907: 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 8908: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8909: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8910: k=3;
8911: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8912: if(j==1)
8913: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8914: else
8915: fprintf(ficgp,", '' ");
8916: l=(nlstate+ndeath)*(cpt-1) +j;
8917: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8918: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8919: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8920: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8921: } /* nlstate */
8922: fprintf(ficgp,", '' ");
8923: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8924: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8925: l=(nlstate+ndeath)*(cpt-1) +j;
8926: if(j < nlstate)
8927: fprintf(ficgp,"$%d +",k+l);
8928: else
8929: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8930: }
1.264 brouard 8931: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8932: } /* end cpt state*/
1.337 brouard 8933: /* } /\* end covariate *\/ */
1.238 brouard 8934: } /* end nres */
1.227 brouard 8935:
1.220 brouard 8936: /* 6eme */
1.202 brouard 8937: /* CV preval stable (period) for each covariate */
1.337 brouard 8938: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8939: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8940: k1=TKresult[nres];
1.338 brouard 8941: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8942: /* if(m != 1 && TKresult[nres]!= k1) */
8943: /* continue; */
1.255 brouard 8944: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8945: strcpy(gplotlabel,"(");
1.288 brouard 8946: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8947: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8948: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8949: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8950: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8951: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8952: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8953: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8954: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8955: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8956: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8957: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8958: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8959: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8960: /* } */
8961: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8962: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8963: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8964: }
1.264 brouard 8965: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8966: fprintf(ficgp,"\n#\n");
1.223 brouard 8967: if(invalidvarcomb[k1]){
1.227 brouard 8968: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8969: continue;
1.223 brouard 8970: }
1.227 brouard 8971:
1.241 brouard 8972: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8973: 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 8974: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8975: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8976: k=3; /* Offset */
1.255 brouard 8977: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8978: if(i==1)
8979: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8980: else
8981: fprintf(ficgp,", '' ");
1.255 brouard 8982: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8983: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8984: for (j=2; j<= nlstate ; j ++)
8985: fprintf(ficgp,"+$%d",k+l+j-1);
8986: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8987: } /* nlstate */
1.264 brouard 8988: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8989: } /* end cpt state*/
8990: } /* end covariate */
1.227 brouard 8991:
8992:
1.220 brouard 8993: /* 7eme */
1.296 brouard 8994: if(prevbcast == 1){
1.288 brouard 8995: /* CV backward prevalence for each covariate */
1.337 brouard 8996: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8997: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8998: k1=TKresult[nres];
1.338 brouard 8999: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9000: /* if(m != 1 && TKresult[nres]!= k1) */
9001: /* continue; */
1.268 brouard 9002: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 9003: strcpy(gplotlabel,"(");
1.288 brouard 9004: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9005: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9006: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9007: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9008: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
9009: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
9010: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9011: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9012: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9013: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9014: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9015: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9016: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9017: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9018: /* } */
9019: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9020: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9021: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9022: }
1.264 brouard 9023: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9024: fprintf(ficgp,"\n#\n");
9025: if(invalidvarcomb[k1]){
9026: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9027: continue;
9028: }
9029:
1.241 brouard 9030: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 9031: 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 9032: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 9033: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 9034: k=3; /* Offset */
1.268 brouard 9035: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 9036: if(i==1)
9037: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
9038: else
9039: fprintf(ficgp,", '' ");
9040: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 9041: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 9042: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
9043: /* 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 9044: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 9045: /* for (j=2; j<= nlstate ; j ++) */
9046: /* fprintf(ficgp,"+$%d",k+l+j-1); */
9047: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 9048: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 9049: } /* nlstate */
1.264 brouard 9050: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 9051: } /* end cpt state*/
9052: } /* end covariate */
1.296 brouard 9053: } /* End if prevbcast */
1.218 brouard 9054:
1.223 brouard 9055: /* 8eme */
1.218 brouard 9056: if(prevfcast==1){
1.288 brouard 9057: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9058:
1.337 brouard 9059: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9060: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9061: k1=TKresult[nres];
1.338 brouard 9062: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9063: /* if(m != 1 && TKresult[nres]!= k1) */
9064: /* continue; */
1.211 brouard 9065: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9066: strcpy(gplotlabel,"(");
1.288 brouard 9067: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9068: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9069: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9070: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9071: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9072: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9073: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9074: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9075: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9076: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9077: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9078: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9079: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9080: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9081: /* } */
9082: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9083: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9084: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9085: }
1.264 brouard 9086: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9087: fprintf(ficgp,"\n#\n");
9088: if(invalidvarcomb[k1]){
9089: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9090: continue;
9091: }
9092:
9093: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9094: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9095: 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 9096: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9097: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9098:
9099: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9100: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9101: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9102: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9103: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9104: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9105: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9106: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9107: if(i==istart){
1.227 brouard 9108: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9109: }else{
9110: fprintf(ficgp,",\\\n '' ");
9111: }
9112: if(cptcoveff ==0){ /* No covariate */
9113: ioffset=2; /* Age is in 2 */
9114: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9115: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9116: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9117: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9118: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9119: if(i==nlstate+1){
1.270 brouard 9120: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9121: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9122: fprintf(ficgp,",\\\n '' ");
9123: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9124: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9125: offyear, \
1.268 brouard 9126: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9127: }else
1.227 brouard 9128: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9129: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9130: }else{ /* more than 2 covariates */
1.270 brouard 9131: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9132: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9133: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9134: iyearc=ioffset-1;
9135: iagec=ioffset;
1.227 brouard 9136: fprintf(ficgp," u %d:(",ioffset);
9137: kl=0;
9138: strcpy(gplotcondition,"(");
1.351 brouard 9139: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 9140: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 9141: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9142: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9143: lv=Tvresult[nres][k];
9144: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 9145: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9146: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9147: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9148: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 9149: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 9150: kl++;
1.351 brouard 9151: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9152: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 9153: kl++;
1.351 brouard 9154: if(k <cptcovs && cptcovs>1)
1.227 brouard 9155: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9156: }
9157: strcpy(gplotcondition+strlen(gplotcondition),")");
9158: /* 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 *\/ */
9159: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9160: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9161: /* '' 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*/
9162: if(i==nlstate+1){
1.270 brouard 9163: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9164: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9165: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9166: fprintf(ficgp," u %d:(",iagec);
9167: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9168: iyearc, iagec, offyear, \
9169: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9170: /* '' 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 9171: }else{
9172: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9173: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9174: }
9175: } /* end if covariate */
9176: } /* nlstate */
1.264 brouard 9177: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9178: } /* end cpt state*/
9179: } /* end covariate */
9180: } /* End if prevfcast */
1.227 brouard 9181:
1.296 brouard 9182: if(prevbcast==1){
1.268 brouard 9183: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9184:
1.337 brouard 9185: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9186: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9187: k1=TKresult[nres];
1.338 brouard 9188: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9189: /* if(m != 1 && TKresult[nres]!= k1) */
9190: /* continue; */
1.268 brouard 9191: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9192: strcpy(gplotlabel,"(");
9193: 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 9194: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9195: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9196: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9197: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9198: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9199: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9200: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9201: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9202: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9203: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9204: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9205: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9206: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9207: /* } */
9208: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9209: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9210: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9211: }
9212: strcpy(gplotlabel+strlen(gplotlabel),")");
9213: fprintf(ficgp,"\n#\n");
9214: if(invalidvarcomb[k1]){
9215: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9216: continue;
9217: }
9218:
9219: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9220: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9221: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9222: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9223: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9224:
9225: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9226: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9227: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9228: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9229: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9230: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9231: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9232: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9233: if(i==istart){
9234: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9235: }else{
9236: fprintf(ficgp,",\\\n '' ");
9237: }
1.351 brouard 9238: /* if(cptcoveff ==0){ /\* No covariate *\/ */
9239: if(cptcovs ==0){ /* No covariate */
1.268 brouard 9240: ioffset=2; /* Age is in 2 */
9241: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9242: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9243: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9244: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9245: fprintf(ficgp," u %d:(", ioffset);
9246: if(i==nlstate+1){
1.270 brouard 9247: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9248: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9249: fprintf(ficgp,",\\\n '' ");
9250: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9251: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9252: offbyear, \
9253: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9254: }else
9255: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9256: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9257: }else{ /* more than 2 covariates */
1.270 brouard 9258: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9259: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9260: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9261: iyearc=ioffset-1;
9262: iagec=ioffset;
1.268 brouard 9263: fprintf(ficgp," u %d:(",ioffset);
9264: kl=0;
9265: strcpy(gplotcondition,"(");
1.337 brouard 9266: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9267: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9268: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9269: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9270: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9271: lv=Tvresult[nres][k];
9272: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9273: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9274: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9275: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9276: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9277: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9278: kl++;
9279: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9280: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9281: kl++;
1.338 brouard 9282: if(k <cptcovs && cptcovs>1)
1.337 brouard 9283: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9284: }
1.268 brouard 9285: }
9286: strcpy(gplotcondition+strlen(gplotcondition),")");
9287: /* 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 *\/ */
9288: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9289: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9290: /* '' 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*/
9291: if(i==nlstate+1){
1.270 brouard 9292: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9293: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9294: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9295: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9296: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9297: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9298: iyearc,iagec,offbyear, \
9299: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9300: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9301: }else{
9302: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9303: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9304: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9305: }
9306: } /* end if covariate */
9307: } /* nlstate */
9308: fprintf(ficgp,"\nset out; unset label;\n");
9309: } /* end cpt state*/
9310: } /* end covariate */
1.296 brouard 9311: } /* End if prevbcast */
1.268 brouard 9312:
1.227 brouard 9313:
1.238 brouard 9314: /* 9eme writing MLE parameters */
9315: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9316: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9317: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9318: for(k=1; k <=(nlstate+ndeath); k++){
9319: if (k != i) {
1.227 brouard 9320: fprintf(ficgp,"# current state %d\n",k);
9321: for(j=1; j <=ncovmodel; j++){
9322: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9323: jk++;
9324: }
9325: fprintf(ficgp,"\n");
1.126 brouard 9326: }
9327: }
1.223 brouard 9328: }
1.187 brouard 9329: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9330:
1.145 brouard 9331: /*goto avoid;*/
1.238 brouard 9332: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9333: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9334: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9335: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9336: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9337: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9338: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9339: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9340: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9341: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9342: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9343: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9344: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9345: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9346: fprintf(ficgp,"#\n");
1.223 brouard 9347: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9348: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9349: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9350: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 9351: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
9352: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 9353: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9354: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9355: /* k1=nres; */
1.338 brouard 9356: k1=TKresult[nres];
9357: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9358: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9359: strcpy(gplotlabel,"(");
1.276 brouard 9360: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9361: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9362: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9363: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9364: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9365: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9366: }
9367: /* if(m != 1 && TKresult[nres]!= k1) */
9368: /* continue; */
9369: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9370: /* strcpy(gplotlabel,"("); */
9371: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9372: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9373: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9374: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9375: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9376: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9377: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9378: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9379: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9380: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9381: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9382: /* } */
9383: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9384: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9385: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9386: /* } */
1.264 brouard 9387: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9388: fprintf(ficgp,"\n#\n");
1.264 brouard 9389: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9390: fprintf(ficgp,"\nset key outside ");
9391: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9392: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9393: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9394: if (ng==1){
9395: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9396: fprintf(ficgp,"\nunset log y");
9397: }else if (ng==2){
9398: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9399: fprintf(ficgp,"\nset log y");
9400: }else if (ng==3){
9401: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9402: fprintf(ficgp,"\nset log y");
9403: }else
9404: fprintf(ficgp,"\nunset title ");
9405: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9406: i=1;
9407: for(k2=1; k2<=nlstate; k2++) {
9408: k3=i;
9409: for(k=1; k<=(nlstate+ndeath); k++) {
9410: if (k != k2){
9411: switch( ng) {
9412: case 1:
9413: if(nagesqr==0)
9414: fprintf(ficgp," p%d+p%d*x",i,i+1);
9415: else /* nagesqr =1 */
9416: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9417: break;
9418: case 2: /* ng=2 */
9419: if(nagesqr==0)
9420: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9421: else /* nagesqr =1 */
9422: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9423: break;
9424: case 3:
9425: if(nagesqr==0)
9426: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9427: else /* nagesqr =1 */
9428: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9429: break;
9430: }
9431: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9432: ijp=1; /* product no age */
9433: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9434: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9435: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9436: switch(Typevar[j]){
9437: case 1:
9438: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9439: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9440: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9441: if(DummyV[j]==0){/* Bug valgrind */
9442: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9443: }else{ /* quantitative */
9444: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9445: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9446: }
9447: ij++;
1.268 brouard 9448: }
1.237 brouard 9449: }
1.329 brouard 9450: }
9451: break;
9452: case 2:
9453: if(cptcovprod >0){
9454: if(j==Tprod[ijp]) { /* */
9455: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9456: if(ijp <=cptcovprod) { /* Product */
9457: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9458: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9459: /* 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)]); */
9460: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9461: }else{ /* Vn is dummy and Vm is quanti */
9462: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9463: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9464: }
9465: }else{ /* Vn*Vm Vn is quanti */
9466: if(DummyV[Tvard[ijp][2]]==0){
9467: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9468: }else{ /* Both quanti */
9469: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9470: }
1.268 brouard 9471: }
1.329 brouard 9472: ijp++;
1.237 brouard 9473: }
1.329 brouard 9474: } /* end Tprod */
9475: }
9476: break;
1.349 brouard 9477: case 3:
9478: if(cptcovdageprod >0){
9479: /* if(j==Tprod[ijp]) { */ /* not necessary */
9480: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 9481: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
9482: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9483: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9484: /* 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)]); */
9485: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9486: }else{ /* Vn is dummy and Vm is quanti */
9487: /* 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 9488: 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 9489: }
1.350 brouard 9490: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 9491: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 9492: 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 9493: }else{ /* Both quanti */
1.350 brouard 9494: 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 9495: }
9496: }
9497: ijp++;
9498: }
9499: /* } */ /* end Tprod */
9500: }
9501: break;
1.329 brouard 9502: case 0:
9503: /* simple covariate */
1.264 brouard 9504: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9505: if(Dummy[j]==0){
9506: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9507: }else{ /* quantitative */
9508: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9509: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9510: }
1.329 brouard 9511: /* end simple */
9512: break;
9513: default:
9514: break;
9515: } /* end switch */
1.237 brouard 9516: } /* end j */
1.329 brouard 9517: }else{ /* k=k2 */
9518: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9519: fprintf(ficgp," (1.");i=i-ncovmodel;
9520: }else
9521: i=i-ncovmodel;
1.223 brouard 9522: }
1.227 brouard 9523:
1.223 brouard 9524: if(ng != 1){
9525: fprintf(ficgp,")/(1");
1.227 brouard 9526:
1.264 brouard 9527: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9528: if(nagesqr==0)
1.264 brouard 9529: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9530: else /* nagesqr =1 */
1.264 brouard 9531: 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 9532:
1.223 brouard 9533: ij=1;
1.329 brouard 9534: ijp=1;
9535: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9536: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9537: switch(Typevar[j]){
9538: case 1:
9539: if(cptcovage >0){
9540: if(j==Tage[ij]) { /* Bug valgrind */
9541: if(ij <=cptcovage) { /* Bug valgrind */
9542: if(DummyV[j]==0){/* Bug valgrind */
9543: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9544: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9545: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9546: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9547: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9548: }else{ /* quantitative */
9549: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9550: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9551: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9552: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9553: }
9554: ij++;
9555: }
9556: }
9557: }
9558: break;
9559: case 2:
9560: if(cptcovprod >0){
9561: if(j==Tprod[ijp]) { /* */
9562: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9563: if(ijp <=cptcovprod) { /* Product */
9564: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9565: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9566: /* 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)]); */
9567: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9568: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9569: }else{ /* Vn is dummy and Vm is quanti */
9570: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9571: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9572: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9573: }
9574: }else{ /* Vn*Vm Vn is quanti */
9575: if(DummyV[Tvard[ijp][2]]==0){
9576: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9577: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9578: }else{ /* Both quanti */
9579: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9580: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9581: }
9582: }
9583: ijp++;
9584: }
9585: } /* end Tprod */
9586: } /* end if */
9587: break;
1.349 brouard 9588: case 3:
9589: if(cptcovdageprod >0){
9590: /* if(j==Tprod[ijp]) { /\* *\/ */
9591: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9592: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 9593: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9594: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9595: /* 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 9596: 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 9597: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9598: }else{ /* Vn is dummy and Vm is quanti */
9599: /* 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 9600: 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 9601: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9602: }
9603: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 9604: if(DummyV[Tvardk[ijp][2]]==0){
9605: 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 9606: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9607: }else{ /* Both quanti */
1.350 brouard 9608: 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 9609: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9610: }
9611: }
9612: ijp++;
9613: }
9614: /* } /\* end Tprod *\/ */
9615: } /* end if */
9616: break;
1.329 brouard 9617: case 0:
9618: /* simple covariate */
9619: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9620: if(Dummy[j]==0){
9621: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9622: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9623: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9624: }else{ /* quantitative */
9625: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9626: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9627: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9628: }
9629: /* end simple */
9630: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9631: break;
9632: default:
9633: break;
9634: } /* end switch */
1.223 brouard 9635: }
9636: fprintf(ficgp,")");
9637: }
9638: fprintf(ficgp,")");
9639: if(ng ==2)
1.276 brouard 9640: 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 9641: else /* ng= 3 */
1.276 brouard 9642: 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 9643: }else{ /* end ng <> 1 */
1.223 brouard 9644: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9645: 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 9646: }
9647: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9648: fprintf(ficgp,",");
9649: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9650: fprintf(ficgp,",");
9651: i=i+ncovmodel;
9652: } /* end k */
9653: } /* end k2 */
1.276 brouard 9654: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9655: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9656: } /* end resultline */
1.223 brouard 9657: } /* end ng */
9658: /* avoid: */
9659: fflush(ficgp);
1.126 brouard 9660: } /* end gnuplot */
9661:
9662:
9663: /*************** Moving average **************/
1.219 brouard 9664: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9665: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9666:
1.222 brouard 9667: int i, cpt, cptcod;
9668: int modcovmax =1;
9669: int mobilavrange, mob;
9670: int iage=0;
1.288 brouard 9671: int firstA1=0, firstA2=0;
1.222 brouard 9672:
1.266 brouard 9673: double sum=0., sumr=0.;
1.222 brouard 9674: double age;
1.266 brouard 9675: double *sumnewp, *sumnewm, *sumnewmr;
9676: double *agemingood, *agemaxgood;
9677: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9678:
9679:
1.278 brouard 9680: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9681: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9682:
9683: sumnewp = vector(1,ncovcombmax);
9684: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9685: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9686: agemingood = vector(1,ncovcombmax);
1.266 brouard 9687: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9688: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9689: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9690:
9691: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9692: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9693: sumnewp[cptcod]=0.;
1.266 brouard 9694: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9695: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9696: }
9697: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9698:
1.266 brouard 9699: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9700: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9701: else mobilavrange=mobilav;
9702: for (age=bage; age<=fage; age++)
9703: for (i=1; i<=nlstate;i++)
9704: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9705: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9706: /* We keep the original values on the extreme ages bage, fage and for
9707: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9708: we use a 5 terms etc. until the borders are no more concerned.
9709: */
9710: for (mob=3;mob <=mobilavrange;mob=mob+2){
9711: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9712: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9713: sumnewm[cptcod]=0.;
9714: for (i=1; i<=nlstate;i++){
1.222 brouard 9715: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9716: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9717: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9718: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9719: }
9720: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9721: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9722: } /* end i */
9723: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9724: } /* end cptcod */
1.222 brouard 9725: }/* end age */
9726: }/* end mob */
1.266 brouard 9727: }else{
9728: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9729: return -1;
1.266 brouard 9730: }
9731:
9732: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9733: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9734: if(invalidvarcomb[cptcod]){
9735: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9736: continue;
9737: }
1.219 brouard 9738:
1.266 brouard 9739: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9740: sumnewm[cptcod]=0.;
9741: sumnewmr[cptcod]=0.;
9742: for (i=1; i<=nlstate;i++){
9743: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9744: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9745: }
9746: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9747: agemingoodr[cptcod]=age;
9748: }
9749: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9750: agemingood[cptcod]=age;
9751: }
9752: } /* age */
9753: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9754: sumnewm[cptcod]=0.;
1.266 brouard 9755: sumnewmr[cptcod]=0.;
1.222 brouard 9756: for (i=1; i<=nlstate;i++){
9757: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9758: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9759: }
9760: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9761: agemaxgoodr[cptcod]=age;
1.222 brouard 9762: }
9763: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9764: agemaxgood[cptcod]=age;
9765: }
9766: } /* age */
9767: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9768: /* but they will change */
1.288 brouard 9769: firstA1=0;firstA2=0;
1.266 brouard 9770: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9771: sumnewm[cptcod]=0.;
9772: sumnewmr[cptcod]=0.;
9773: for (i=1; i<=nlstate;i++){
9774: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9775: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9776: }
9777: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9778: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9779: agemaxgoodr[cptcod]=age; /* age min */
9780: for (i=1; i<=nlstate;i++)
9781: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9782: }else{ /* bad we change the value with the values of good ages */
9783: for (i=1; i<=nlstate;i++){
9784: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9785: } /* i */
9786: } /* end bad */
9787: }else{
9788: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9789: agemaxgood[cptcod]=age;
9790: }else{ /* bad we change the value with the values of good ages */
9791: for (i=1; i<=nlstate;i++){
9792: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9793: } /* i */
9794: } /* end bad */
9795: }/* end else */
9796: sum=0.;sumr=0.;
9797: for (i=1; i<=nlstate;i++){
9798: sum+=mobaverage[(int)age][i][cptcod];
9799: sumr+=probs[(int)age][i][cptcod];
9800: }
9801: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9802: if(!firstA1){
9803: firstA1=1;
9804: 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);
9805: }
9806: 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 9807: } /* end bad */
9808: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9809: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9810: if(!firstA2){
9811: firstA2=1;
9812: 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);
9813: }
9814: 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 9815: } /* end bad */
9816: }/* age */
1.266 brouard 9817:
9818: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9819: sumnewm[cptcod]=0.;
1.266 brouard 9820: sumnewmr[cptcod]=0.;
1.222 brouard 9821: for (i=1; i<=nlstate;i++){
9822: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9823: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9824: }
9825: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9826: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9827: agemingoodr[cptcod]=age;
9828: for (i=1; i<=nlstate;i++)
9829: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9830: }else{ /* bad we change the value with the values of good ages */
9831: for (i=1; i<=nlstate;i++){
9832: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9833: } /* i */
9834: } /* end bad */
9835: }else{
9836: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9837: agemingood[cptcod]=age;
9838: }else{ /* bad */
9839: for (i=1; i<=nlstate;i++){
9840: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9841: } /* i */
9842: } /* end bad */
9843: }/* end else */
9844: sum=0.;sumr=0.;
9845: for (i=1; i<=nlstate;i++){
9846: sum+=mobaverage[(int)age][i][cptcod];
9847: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9848: }
1.266 brouard 9849: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9850: 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 9851: } /* end bad */
9852: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9853: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9854: 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 9855: } /* end bad */
9856: }/* age */
1.266 brouard 9857:
1.222 brouard 9858:
9859: for (age=bage; age<=fage; age++){
1.235 brouard 9860: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9861: sumnewp[cptcod]=0.;
9862: sumnewm[cptcod]=0.;
9863: for (i=1; i<=nlstate;i++){
9864: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9865: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9866: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9867: }
9868: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9869: }
9870: /* printf("\n"); */
9871: /* } */
1.266 brouard 9872:
1.222 brouard 9873: /* brutal averaging */
1.266 brouard 9874: /* for (i=1; i<=nlstate;i++){ */
9875: /* for (age=1; age<=bage; age++){ */
9876: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9877: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9878: /* } */
9879: /* for (age=fage; age<=AGESUP; age++){ */
9880: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9881: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9882: /* } */
9883: /* } /\* end i status *\/ */
9884: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9885: /* for (age=1; age<=AGESUP; age++){ */
9886: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9887: /* mobaverage[(int)age][i][cptcod]=0.; */
9888: /* } */
9889: /* } */
1.222 brouard 9890: }/* end cptcod */
1.266 brouard 9891: free_vector(agemaxgoodr,1, ncovcombmax);
9892: free_vector(agemaxgood,1, ncovcombmax);
9893: free_vector(agemingood,1, ncovcombmax);
9894: free_vector(agemingoodr,1, ncovcombmax);
9895: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9896: free_vector(sumnewm,1, ncovcombmax);
9897: free_vector(sumnewp,1, ncovcombmax);
9898: return 0;
9899: }/* End movingaverage */
1.218 brouard 9900:
1.126 brouard 9901:
1.296 brouard 9902:
1.126 brouard 9903: /************** Forecasting ******************/
1.296 brouard 9904: /* 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)*/
9905: 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){
9906: /* dateintemean, mean date of interviews
9907: dateprojd, year, month, day of starting projection
9908: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9909: agemin, agemax range of age
9910: dateprev1 dateprev2 range of dates during which prevalence is computed
9911: */
1.296 brouard 9912: /* double anprojd, mprojd, jprojd; */
9913: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9914: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9915: double agec; /* generic age */
1.296 brouard 9916: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9917: double *popeffectif,*popcount;
9918: double ***p3mat;
1.218 brouard 9919: /* double ***mobaverage; */
1.126 brouard 9920: char fileresf[FILENAMELENGTH];
9921:
9922: agelim=AGESUP;
1.211 brouard 9923: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9924: in each health status at the date of interview (if between dateprev1 and dateprev2).
9925: We still use firstpass and lastpass as another selection.
9926: */
1.214 brouard 9927: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9928: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9929:
1.201 brouard 9930: strcpy(fileresf,"F_");
9931: strcat(fileresf,fileresu);
1.126 brouard 9932: if((ficresf=fopen(fileresf,"w"))==NULL) {
9933: printf("Problem with forecast resultfile: %s\n", fileresf);
9934: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9935: }
1.235 brouard 9936: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9937: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9938:
1.225 brouard 9939: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9940:
9941:
9942: stepsize=(int) (stepm+YEARM-1)/YEARM;
9943: if (stepm<=12) stepsize=1;
9944: if(estepm < stepm){
9945: printf ("Problem %d lower than %d\n",estepm, stepm);
9946: }
1.270 brouard 9947: else{
9948: hstepm=estepm;
9949: }
9950: if(estepm > stepm){ /* Yes every two year */
9951: stepsize=2;
9952: }
1.296 brouard 9953: hstepm=hstepm/stepm;
1.126 brouard 9954:
1.296 brouard 9955:
9956: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9957: /* fractional in yp1 *\/ */
9958: /* aintmean=yp; */
9959: /* yp2=modf((yp1*12),&yp); */
9960: /* mintmean=yp; */
9961: /* yp1=modf((yp2*30.5),&yp); */
9962: /* jintmean=yp; */
9963: /* if(jintmean==0) jintmean=1; */
9964: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9965:
1.296 brouard 9966:
9967: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9968: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9969: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 9970: /* i1=pow(2,cptcoveff); */
9971: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 9972:
1.296 brouard 9973: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9974:
9975: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9976:
1.126 brouard 9977: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 9978: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9979: k=TKresult[nres];
9980: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
9981: /* 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) *\/ */
9982: /* if(i1 != 1 && TKresult[nres]!= k) */
9983: /* continue; */
9984: /* if(invalidvarcomb[k]){ */
9985: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
9986: /* continue; */
9987: /* } */
1.227 brouard 9988: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 9989: for(j=1;j<=cptcovs;j++){
9990: /* for(j=1;j<=cptcoveff;j++) { */
9991: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
9992: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9993: /* } */
9994: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9995: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9996: /* } */
9997: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 9998: }
1.351 brouard 9999:
1.227 brouard 10000: fprintf(ficresf," yearproj age");
10001: for(j=1; j<=nlstate+ndeath;j++){
10002: for(i=1; i<=nlstate;i++)
10003: fprintf(ficresf," p%d%d",i,j);
10004: fprintf(ficresf," wp.%d",j);
10005: }
1.296 brouard 10006: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 10007: fprintf(ficresf,"\n");
1.296 brouard 10008: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 10009: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
10010: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 10011: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
10012: nhstepm = nhstepm/hstepm;
10013: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10014: oldm=oldms;savm=savms;
1.268 brouard 10015: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 10016: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 10017: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 10018: for (h=0; h<=nhstepm; h++){
10019: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 10020: break;
10021: }
10022: }
10023: fprintf(ficresf,"\n");
1.351 brouard 10024: /* for(j=1;j<=cptcoveff;j++) */
10025: for(j=1;j<=cptcovs;j++)
10026: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 10027: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 10028: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 10029: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 10030:
10031: for(j=1; j<=nlstate+ndeath;j++) {
10032: ppij=0.;
10033: for(i=1; i<=nlstate;i++) {
1.278 brouard 10034: if (mobilav>=1)
10035: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
10036: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
10037: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
10038: }
1.268 brouard 10039: fprintf(ficresf," %.3f", p3mat[i][j][h]);
10040: } /* end i */
10041: fprintf(ficresf," %.3f", ppij);
10042: }/* end j */
1.227 brouard 10043: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10044: } /* end agec */
1.266 brouard 10045: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
10046: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 10047: } /* end yearp */
10048: } /* end k */
1.219 brouard 10049:
1.126 brouard 10050: fclose(ficresf);
1.215 brouard 10051: printf("End of Computing forecasting \n");
10052: fprintf(ficlog,"End of Computing forecasting\n");
10053:
1.126 brouard 10054: }
10055:
1.269 brouard 10056: /************** Back Forecasting ******************/
1.296 brouard 10057: /* 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){ */
10058: 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){
10059: /* back1, year, month, day of starting backprojection
1.267 brouard 10060: agemin, agemax range of age
10061: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 10062: anback2 year of end of backprojection (same day and month as back1).
10063: prevacurrent and prev are prevalences.
1.267 brouard 10064: */
10065: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
10066: double agec; /* generic age */
1.302 brouard 10067: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10068: double *popeffectif,*popcount;
10069: double ***p3mat;
10070: /* double ***mobaverage; */
10071: char fileresfb[FILENAMELENGTH];
10072:
1.268 brouard 10073: agelim=AGEINF;
1.267 brouard 10074: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10075: in each health status at the date of interview (if between dateprev1 and dateprev2).
10076: We still use firstpass and lastpass as another selection.
10077: */
10078: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10079: /* firstpass, lastpass, stepm, weightopt, model); */
10080:
10081: /*Do we need to compute prevalence again?*/
10082:
10083: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10084:
10085: strcpy(fileresfb,"FB_");
10086: strcat(fileresfb,fileresu);
10087: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10088: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10089: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10090: }
10091: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10092: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10093:
10094: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10095:
10096:
10097: stepsize=(int) (stepm+YEARM-1)/YEARM;
10098: if (stepm<=12) stepsize=1;
10099: if(estepm < stepm){
10100: printf ("Problem %d lower than %d\n",estepm, stepm);
10101: }
1.270 brouard 10102: else{
10103: hstepm=estepm;
10104: }
10105: if(estepm >= stepm){ /* Yes every two year */
10106: stepsize=2;
10107: }
1.267 brouard 10108:
10109: hstepm=hstepm/stepm;
1.296 brouard 10110: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10111: /* fractional in yp1 *\/ */
10112: /* aintmean=yp; */
10113: /* yp2=modf((yp1*12),&yp); */
10114: /* mintmean=yp; */
10115: /* yp1=modf((yp2*30.5),&yp); */
10116: /* jintmean=yp; */
10117: /* if(jintmean==0) jintmean=1; */
10118: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10119:
1.351 brouard 10120: /* i1=pow(2,cptcoveff); */
10121: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 10122:
1.296 brouard 10123: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10124: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10125:
10126: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10127:
1.351 brouard 10128: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10129: k=TKresult[nres];
10130: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
10131: /* for(k=1; k<=i1;k++){ */
10132: /* if(i1 != 1 && TKresult[nres]!= k) */
10133: /* continue; */
10134: /* if(invalidvarcomb[k]){ */
10135: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
10136: /* continue; */
10137: /* } */
1.268 brouard 10138: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 10139: for(j=1;j<=cptcovs;j++){
10140: /* for(j=1;j<=cptcoveff;j++) { */
10141: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10142: /* } */
10143: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 10144: }
1.351 brouard 10145: /* fprintf(ficrespij,"******\n"); */
10146: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10147: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10148: /* } */
1.267 brouard 10149: fprintf(ficresfb," yearbproj age");
10150: for(j=1; j<=nlstate+ndeath;j++){
10151: for(i=1; i<=nlstate;i++)
1.268 brouard 10152: fprintf(ficresfb," b%d%d",i,j);
10153: fprintf(ficresfb," b.%d",j);
1.267 brouard 10154: }
1.296 brouard 10155: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10156: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10157: fprintf(ficresfb,"\n");
1.296 brouard 10158: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10159: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10160: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10161: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10162: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10163: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10164: nhstepm = nhstepm/hstepm;
10165: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10166: oldm=oldms;savm=savms;
1.268 brouard 10167: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10168: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10169: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10170: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10171: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10172: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10173: for (h=0; h<=nhstepm; h++){
1.268 brouard 10174: if (h*hstepm/YEARM*stepm ==-yearp) {
10175: break;
10176: }
10177: }
10178: fprintf(ficresfb,"\n");
1.351 brouard 10179: /* for(j=1;j<=cptcoveff;j++) */
10180: for(j=1;j<=cptcovs;j++)
10181: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10182: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 10183: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10184: for(i=1; i<=nlstate+ndeath;i++) {
10185: ppij=0.;ppi=0.;
10186: for(j=1; j<=nlstate;j++) {
10187: /* if (mobilav==1) */
1.269 brouard 10188: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10189: ppi=ppi+prevacurrent[(int)agec][j][k];
10190: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10191: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10192: /* else { */
10193: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10194: /* } */
1.268 brouard 10195: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10196: } /* end j */
10197: if(ppi <0.99){
10198: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10199: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10200: }
10201: fprintf(ficresfb," %.3f", ppij);
10202: }/* end j */
1.267 brouard 10203: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10204: } /* end agec */
10205: } /* end yearp */
10206: } /* end k */
1.217 brouard 10207:
1.267 brouard 10208: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10209:
1.267 brouard 10210: fclose(ficresfb);
10211: printf("End of Computing Back forecasting \n");
10212: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10213:
1.267 brouard 10214: }
1.217 brouard 10215:
1.269 brouard 10216: /* Variance of prevalence limit: varprlim */
10217: 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 10218: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10219:
10220: char fileresvpl[FILENAMELENGTH];
10221: FILE *ficresvpl;
10222: double **oldm, **savm;
10223: double **varpl; /* Variances of prevalence limits by age */
10224: int i1, k, nres, j ;
10225:
10226: strcpy(fileresvpl,"VPL_");
10227: strcat(fileresvpl,fileresu);
10228: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10229: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10230: exit(0);
10231: }
1.288 brouard 10232: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10233: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10234:
10235: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10236: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10237:
10238: i1=pow(2,cptcoveff);
10239: if (cptcovn < 1){i1=1;}
10240:
1.337 brouard 10241: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10242: k=TKresult[nres];
1.338 brouard 10243: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10244: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10245: if(i1 != 1 && TKresult[nres]!= k)
10246: continue;
10247: fprintf(ficresvpl,"\n#****** ");
10248: printf("\n#****** ");
10249: fprintf(ficlog,"\n#****** ");
1.337 brouard 10250: for(j=1;j<=cptcovs;j++) {
10251: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10252: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10253: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10254: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10255: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10256: }
1.337 brouard 10257: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10258: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10259: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10260: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10261: /* } */
1.269 brouard 10262: fprintf(ficresvpl,"******\n");
10263: printf("******\n");
10264: fprintf(ficlog,"******\n");
10265:
10266: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10267: oldm=oldms;savm=savms;
10268: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10269: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10270: /*}*/
10271: }
10272:
10273: fclose(ficresvpl);
1.288 brouard 10274: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10275: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10276:
10277: }
10278: /* Variance of back prevalence: varbprlim */
10279: 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){
10280: /*------- Variance of back (stable) prevalence------*/
10281:
10282: char fileresvbl[FILENAMELENGTH];
10283: FILE *ficresvbl;
10284:
10285: double **oldm, **savm;
10286: double **varbpl; /* Variances of back prevalence limits by age */
10287: int i1, k, nres, j ;
10288:
10289: strcpy(fileresvbl,"VBL_");
10290: strcat(fileresvbl,fileresu);
10291: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10292: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10293: exit(0);
10294: }
10295: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10296: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10297:
10298:
10299: i1=pow(2,cptcoveff);
10300: if (cptcovn < 1){i1=1;}
10301:
1.337 brouard 10302: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10303: k=TKresult[nres];
1.338 brouard 10304: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10305: /* for(k=1; k<=i1;k++){ */
10306: /* if(i1 != 1 && TKresult[nres]!= k) */
10307: /* continue; */
1.269 brouard 10308: fprintf(ficresvbl,"\n#****** ");
10309: printf("\n#****** ");
10310: fprintf(ficlog,"\n#****** ");
1.337 brouard 10311: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10312: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10313: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10314: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10315: /* for(j=1;j<=cptcoveff;j++) { */
10316: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10317: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10318: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10319: /* } */
10320: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10321: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10322: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10323: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10324: }
10325: fprintf(ficresvbl,"******\n");
10326: printf("******\n");
10327: fprintf(ficlog,"******\n");
10328:
10329: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10330: oldm=oldms;savm=savms;
10331:
10332: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10333: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10334: /*}*/
10335: }
10336:
10337: fclose(ficresvbl);
10338: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10339: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10340:
10341: } /* End of varbprlim */
10342:
1.126 brouard 10343: /************** Forecasting *****not tested NB*************/
1.227 brouard 10344: /* 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 10345:
1.227 brouard 10346: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10347: /* int *popage; */
10348: /* double calagedatem, agelim, kk1, kk2; */
10349: /* double *popeffectif,*popcount; */
10350: /* double ***p3mat,***tabpop,***tabpopprev; */
10351: /* /\* double ***mobaverage; *\/ */
10352: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10353:
1.227 brouard 10354: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10355: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10356: /* agelim=AGESUP; */
10357: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10358:
1.227 brouard 10359: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10360:
10361:
1.227 brouard 10362: /* strcpy(filerespop,"POP_"); */
10363: /* strcat(filerespop,fileresu); */
10364: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10365: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10366: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10367: /* } */
10368: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10369: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10370:
1.227 brouard 10371: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10372:
1.227 brouard 10373: /* /\* if (mobilav!=0) { *\/ */
10374: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10375: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10376: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10377: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10378: /* /\* } *\/ */
10379: /* /\* } *\/ */
1.126 brouard 10380:
1.227 brouard 10381: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10382: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10383:
1.227 brouard 10384: /* agelim=AGESUP; */
1.126 brouard 10385:
1.227 brouard 10386: /* hstepm=1; */
10387: /* hstepm=hstepm/stepm; */
1.218 brouard 10388:
1.227 brouard 10389: /* if (popforecast==1) { */
10390: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10391: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10392: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10393: /* } */
10394: /* popage=ivector(0,AGESUP); */
10395: /* popeffectif=vector(0,AGESUP); */
10396: /* popcount=vector(0,AGESUP); */
1.126 brouard 10397:
1.227 brouard 10398: /* i=1; */
10399: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10400:
1.227 brouard 10401: /* imx=i; */
10402: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10403: /* } */
1.218 brouard 10404:
1.227 brouard 10405: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10406: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10407: /* k=k+1; */
10408: /* fprintf(ficrespop,"\n#******"); */
10409: /* for(j=1;j<=cptcoveff;j++) { */
10410: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10411: /* } */
10412: /* fprintf(ficrespop,"******\n"); */
10413: /* fprintf(ficrespop,"# Age"); */
10414: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10415: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10416:
1.227 brouard 10417: /* for (cpt=0; cpt<=0;cpt++) { */
10418: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10419:
1.227 brouard 10420: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10421: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10422: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10423:
1.227 brouard 10424: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10425: /* oldm=oldms;savm=savms; */
10426: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10427:
1.227 brouard 10428: /* for (h=0; h<=nhstepm; h++){ */
10429: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10430: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10431: /* } */
10432: /* for(j=1; j<=nlstate+ndeath;j++) { */
10433: /* kk1=0.;kk2=0; */
10434: /* for(i=1; i<=nlstate;i++) { */
10435: /* if (mobilav==1) */
10436: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10437: /* else { */
10438: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10439: /* } */
10440: /* } */
10441: /* if (h==(int)(calagedatem+12*cpt)){ */
10442: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10443: /* /\*fprintf(ficrespop," %.3f", kk1); */
10444: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10445: /* } */
10446: /* } */
10447: /* for(i=1; i<=nlstate;i++){ */
10448: /* kk1=0.; */
10449: /* for(j=1; j<=nlstate;j++){ */
10450: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10451: /* } */
10452: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10453: /* } */
1.218 brouard 10454:
1.227 brouard 10455: /* if (h==(int)(calagedatem+12*cpt)) */
10456: /* for(j=1; j<=nlstate;j++) */
10457: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10458: /* } */
10459: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10460: /* } */
10461: /* } */
1.218 brouard 10462:
1.227 brouard 10463: /* /\******\/ */
1.218 brouard 10464:
1.227 brouard 10465: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10466: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10467: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10468: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10469: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10470:
1.227 brouard 10471: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10472: /* oldm=oldms;savm=savms; */
10473: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10474: /* for (h=0; h<=nhstepm; h++){ */
10475: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10476: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10477: /* } */
10478: /* for(j=1; j<=nlstate+ndeath;j++) { */
10479: /* kk1=0.;kk2=0; */
10480: /* for(i=1; i<=nlstate;i++) { */
10481: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10482: /* } */
10483: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10484: /* } */
10485: /* } */
10486: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10487: /* } */
10488: /* } */
10489: /* } */
10490: /* } */
1.218 brouard 10491:
1.227 brouard 10492: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10493:
1.227 brouard 10494: /* if (popforecast==1) { */
10495: /* free_ivector(popage,0,AGESUP); */
10496: /* free_vector(popeffectif,0,AGESUP); */
10497: /* free_vector(popcount,0,AGESUP); */
10498: /* } */
10499: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10500: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10501: /* fclose(ficrespop); */
10502: /* } /\* End of popforecast *\/ */
1.218 brouard 10503:
1.126 brouard 10504: int fileappend(FILE *fichier, char *optionfich)
10505: {
10506: if((fichier=fopen(optionfich,"a"))==NULL) {
10507: printf("Problem with file: %s\n", optionfich);
10508: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10509: return (0);
10510: }
10511: fflush(fichier);
10512: return (1);
10513: }
10514:
10515:
10516: /**************** function prwizard **********************/
10517: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10518: {
10519:
10520: /* Wizard to print covariance matrix template */
10521:
1.164 brouard 10522: char ca[32], cb[32];
10523: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10524: int numlinepar;
10525:
10526: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10527: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10528: for(i=1; i <=nlstate; i++){
10529: jj=0;
10530: for(j=1; j <=nlstate+ndeath; j++){
10531: if(j==i) continue;
10532: jj++;
10533: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10534: printf("%1d%1d",i,j);
10535: fprintf(ficparo,"%1d%1d",i,j);
10536: for(k=1; k<=ncovmodel;k++){
10537: /* printf(" %lf",param[i][j][k]); */
10538: /* fprintf(ficparo," %lf",param[i][j][k]); */
10539: printf(" 0.");
10540: fprintf(ficparo," 0.");
10541: }
10542: printf("\n");
10543: fprintf(ficparo,"\n");
10544: }
10545: }
10546: printf("# Scales (for hessian or gradient estimation)\n");
10547: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10548: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10549: for(i=1; i <=nlstate; i++){
10550: jj=0;
10551: for(j=1; j <=nlstate+ndeath; j++){
10552: if(j==i) continue;
10553: jj++;
10554: fprintf(ficparo,"%1d%1d",i,j);
10555: printf("%1d%1d",i,j);
10556: fflush(stdout);
10557: for(k=1; k<=ncovmodel;k++){
10558: /* printf(" %le",delti3[i][j][k]); */
10559: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10560: printf(" 0.");
10561: fprintf(ficparo," 0.");
10562: }
10563: numlinepar++;
10564: printf("\n");
10565: fprintf(ficparo,"\n");
10566: }
10567: }
10568: printf("# Covariance matrix\n");
10569: /* # 121 Var(a12)\n\ */
10570: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10571: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10572: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10573: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10574: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10575: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10576: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10577: fflush(stdout);
10578: fprintf(ficparo,"# Covariance matrix\n");
10579: /* # 121 Var(a12)\n\ */
10580: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10581: /* # ...\n\ */
10582: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10583:
10584: for(itimes=1;itimes<=2;itimes++){
10585: jj=0;
10586: for(i=1; i <=nlstate; i++){
10587: for(j=1; j <=nlstate+ndeath; j++){
10588: if(j==i) continue;
10589: for(k=1; k<=ncovmodel;k++){
10590: jj++;
10591: ca[0]= k+'a'-1;ca[1]='\0';
10592: if(itimes==1){
10593: printf("#%1d%1d%d",i,j,k);
10594: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10595: }else{
10596: printf("%1d%1d%d",i,j,k);
10597: fprintf(ficparo,"%1d%1d%d",i,j,k);
10598: /* printf(" %.5le",matcov[i][j]); */
10599: }
10600: ll=0;
10601: for(li=1;li <=nlstate; li++){
10602: for(lj=1;lj <=nlstate+ndeath; lj++){
10603: if(lj==li) continue;
10604: for(lk=1;lk<=ncovmodel;lk++){
10605: ll++;
10606: if(ll<=jj){
10607: cb[0]= lk +'a'-1;cb[1]='\0';
10608: if(ll<jj){
10609: if(itimes==1){
10610: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10611: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10612: }else{
10613: printf(" 0.");
10614: fprintf(ficparo," 0.");
10615: }
10616: }else{
10617: if(itimes==1){
10618: printf(" Var(%s%1d%1d)",ca,i,j);
10619: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10620: }else{
10621: printf(" 0.");
10622: fprintf(ficparo," 0.");
10623: }
10624: }
10625: }
10626: } /* end lk */
10627: } /* end lj */
10628: } /* end li */
10629: printf("\n");
10630: fprintf(ficparo,"\n");
10631: numlinepar++;
10632: } /* end k*/
10633: } /*end j */
10634: } /* end i */
10635: } /* end itimes */
10636:
10637: } /* end of prwizard */
10638: /******************* Gompertz Likelihood ******************************/
10639: double gompertz(double x[])
10640: {
1.302 brouard 10641: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10642: int i,n=0; /* n is the size of the sample */
10643:
1.220 brouard 10644: for (i=1;i<=imx ; i++) {
1.126 brouard 10645: sump=sump+weight[i];
10646: /* sump=sump+1;*/
10647: num=num+1;
10648: }
1.302 brouard 10649: L=0.0;
10650: /* agegomp=AGEGOMP; */
1.126 brouard 10651: /* for (i=0; i<=imx; i++)
10652: 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]);*/
10653:
1.302 brouard 10654: for (i=1;i<=imx ; i++) {
10655: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10656: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10657: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10658: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10659: * +
10660: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10661: */
10662: if (wav[i] > 1 || agedc[i] < AGESUP) {
10663: if (cens[i] == 1){
10664: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10665: } else if (cens[i] == 0){
1.126 brouard 10666: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10667: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10668: } else
10669: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10670: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10671: L=L+A*weight[i];
1.126 brouard 10672: /* 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 10673: }
10674: }
1.126 brouard 10675:
1.302 brouard 10676: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10677:
10678: return -2*L*num/sump;
10679: }
10680:
1.136 brouard 10681: #ifdef GSL
10682: /******************* Gompertz_f Likelihood ******************************/
10683: double gompertz_f(const gsl_vector *v, void *params)
10684: {
1.302 brouard 10685: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10686: double *x= (double *) v->data;
10687: int i,n=0; /* n is the size of the sample */
10688:
10689: for (i=0;i<=imx-1 ; i++) {
10690: sump=sump+weight[i];
10691: /* sump=sump+1;*/
10692: num=num+1;
10693: }
10694:
10695:
10696: /* for (i=0; i<=imx; i++)
10697: 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]);*/
10698: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10699: for (i=1;i<=imx ; i++)
10700: {
10701: if (cens[i] == 1 && wav[i]>1)
10702: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10703:
10704: if (cens[i] == 0 && wav[i]>1)
10705: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10706: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10707:
10708: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10709: if (wav[i] > 1 ) { /* ??? */
10710: LL=LL+A*weight[i];
10711: /* 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]);*/
10712: }
10713: }
10714:
10715: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10716: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10717:
10718: return -2*LL*num/sump;
10719: }
10720: #endif
10721:
1.126 brouard 10722: /******************* Printing html file ***********/
1.201 brouard 10723: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10724: int lastpass, int stepm, int weightopt, char model[],\
10725: int imx, double p[],double **matcov,double agemortsup){
10726: int i,k;
10727:
10728: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10729: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10730: for (i=1;i<=2;i++)
10731: 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 10732: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10733: fprintf(fichtm,"</ul>");
10734:
10735: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10736:
10737: 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>");
10738:
10739: for (k=agegomp;k<(agemortsup-2);k++)
10740: 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]);
10741:
10742:
10743: fflush(fichtm);
10744: }
10745:
10746: /******************* Gnuplot file **************/
1.201 brouard 10747: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10748:
10749: char dirfileres[132],optfileres[132];
1.164 brouard 10750:
1.126 brouard 10751: int ng;
10752:
10753:
10754: /*#ifdef windows */
10755: fprintf(ficgp,"cd \"%s\" \n",pathc);
10756: /*#endif */
10757:
10758:
10759: strcpy(dirfileres,optionfilefiname);
10760: strcpy(optfileres,"vpl");
1.199 brouard 10761: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10762: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10763: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10764: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10765: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10766:
10767: }
10768:
1.136 brouard 10769: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10770: {
1.126 brouard 10771:
1.136 brouard 10772: /*-------- data file ----------*/
10773: FILE *fic;
10774: char dummy[]=" ";
1.240 brouard 10775: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10776: int lstra;
1.136 brouard 10777: int linei, month, year,iout;
1.302 brouard 10778: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10779: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10780: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10781: char *stratrunc;
1.223 brouard 10782:
1.349 brouard 10783: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
10784: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10785:
10786: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10787:
1.136 brouard 10788: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10789: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10790: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10791: }
1.126 brouard 10792:
1.302 brouard 10793: /* Is it a BOM UTF-8 Windows file? */
10794: /* First data line */
10795: linei=0;
10796: while(fgets(line, MAXLINE, fic)) {
10797: noffset=0;
10798: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10799: {
10800: noffset=noffset+3;
10801: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10802: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10803: fflush(ficlog); return 1;
10804: }
10805: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10806: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10807: {
10808: noffset=noffset+2;
1.304 brouard 10809: 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);
10810: 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 10811: fflush(ficlog); return 1;
10812: }
10813: else if( line[0] == 0 && line[1] == 0)
10814: {
10815: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10816: noffset=noffset+4;
1.304 brouard 10817: 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);
10818: 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 10819: fflush(ficlog); return 1;
10820: }
10821: } else{
10822: ;/*printf(" Not a BOM file\n");*/
10823: }
10824: /* If line starts with a # it is a comment */
10825: if (line[noffset] == '#') {
10826: linei=linei+1;
10827: break;
10828: }else{
10829: break;
10830: }
10831: }
10832: fclose(fic);
10833: if((fic=fopen(datafile,"r"))==NULL) {
10834: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10835: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10836: }
10837: /* Not a Bom file */
10838:
1.136 brouard 10839: i=1;
10840: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10841: linei=linei+1;
10842: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10843: if(line[j] == '\t')
10844: line[j] = ' ';
10845: }
10846: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10847: ;
10848: };
10849: line[j+1]=0; /* Trims blanks at end of line */
10850: if(line[0]=='#'){
10851: fprintf(ficlog,"Comment line\n%s\n",line);
10852: printf("Comment line\n%s\n",line);
10853: continue;
10854: }
10855: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10856: strcpy(line, linetmp);
1.223 brouard 10857:
10858: /* Loops on waves */
10859: for (j=maxwav;j>=1;j--){
10860: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10861: cutv(stra, strb, line, ' ');
10862: if(strb[0]=='.') { /* Missing value */
10863: lval=-1;
10864: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10865: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10866: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10867: 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);
10868: 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);
10869: return 1;
10870: }
10871: }else{
10872: errno=0;
10873: /* what_kind_of_number(strb); */
10874: dval=strtod(strb,&endptr);
10875: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10876: /* if(strb != endptr && *endptr == '\0') */
10877: /* dval=dlval; */
10878: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10879: if( strb[0]=='\0' || (*endptr != '\0')){
10880: 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);
10881: 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);
10882: return 1;
10883: }
10884: cotqvar[j][iv][i]=dval;
1.341 brouard 10885: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10886: }
10887: strcpy(line,stra);
1.223 brouard 10888: }/* end loop ntqv */
1.225 brouard 10889:
1.223 brouard 10890: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10891: cutv(stra, strb, line, ' ');
10892: if(strb[0]=='.') { /* Missing value */
10893: lval=-1;
10894: }else{
10895: errno=0;
10896: lval=strtol(strb,&endptr,10);
10897: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10898: if( strb[0]=='\0' || (*endptr != '\0')){
10899: 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);
10900: 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);
10901: return 1;
10902: }
10903: }
10904: if(lval <-1 || lval >1){
10905: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10906: 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 10907: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10908: For example, for multinomial values like 1, 2 and 3,\n \
10909: build V1=0 V2=0 for the reference value (1),\n \
10910: V1=1 V2=0 for (2) \n \
1.223 brouard 10911: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10912: output of IMaCh is often meaningless.\n \
1.319 brouard 10913: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10914: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10915: 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 10916: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10917: For example, for multinomial values like 1, 2 and 3,\n \
10918: build V1=0 V2=0 for the reference value (1),\n \
10919: V1=1 V2=0 for (2) \n \
1.223 brouard 10920: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10921: output of IMaCh is often meaningless.\n \
1.319 brouard 10922: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10923: return 1;
10924: }
1.341 brouard 10925: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10926: strcpy(line,stra);
1.223 brouard 10927: }/* end loop ntv */
1.225 brouard 10928:
1.223 brouard 10929: /* Statuses at wave */
1.137 brouard 10930: cutv(stra, strb, line, ' ');
1.223 brouard 10931: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10932: lval=-1;
1.136 brouard 10933: }else{
1.238 brouard 10934: errno=0;
10935: lval=strtol(strb,&endptr,10);
10936: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10937: if( strb[0]=='\0' || (*endptr != '\0' )){
10938: 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);
10939: 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);
10940: return 1;
10941: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10942: 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);
10943: 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 10944: return 1;
10945: }
1.136 brouard 10946: }
1.225 brouard 10947:
1.136 brouard 10948: s[j][i]=lval;
1.225 brouard 10949:
1.223 brouard 10950: /* Date of Interview */
1.136 brouard 10951: strcpy(line,stra);
10952: cutv(stra, strb,line,' ');
1.169 brouard 10953: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10954: }
1.169 brouard 10955: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10956: month=99;
10957: year=9999;
1.136 brouard 10958: }else{
1.225 brouard 10959: 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);
10960: 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);
10961: return 1;
1.136 brouard 10962: }
10963: anint[j][i]= (double) year;
1.302 brouard 10964: mint[j][i]= (double)month;
10965: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10966: /* 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]); */
10967: /* 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]); */
10968: /* } */
1.136 brouard 10969: strcpy(line,stra);
1.223 brouard 10970: } /* End loop on waves */
1.225 brouard 10971:
1.223 brouard 10972: /* Date of death */
1.136 brouard 10973: cutv(stra, strb,line,' ');
1.169 brouard 10974: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10975: }
1.169 brouard 10976: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10977: month=99;
10978: year=9999;
10979: }else{
1.141 brouard 10980: 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 10981: 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);
10982: return 1;
1.136 brouard 10983: }
10984: andc[i]=(double) year;
10985: moisdc[i]=(double) month;
10986: strcpy(line,stra);
10987:
1.223 brouard 10988: /* Date of birth */
1.136 brouard 10989: cutv(stra, strb,line,' ');
1.169 brouard 10990: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10991: }
1.169 brouard 10992: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10993: month=99;
10994: year=9999;
10995: }else{
1.141 brouard 10996: 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);
10997: 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 10998: return 1;
1.136 brouard 10999: }
11000: if (year==9999) {
1.141 brouard 11001: 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);
11002: 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 11003: return 1;
11004:
1.136 brouard 11005: }
11006: annais[i]=(double)(year);
1.302 brouard 11007: moisnais[i]=(double)(month);
11008: for (j=1;j<=maxwav;j++){
11009: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
11010: 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]);
11011: 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]);
11012: }
11013: }
11014:
1.136 brouard 11015: strcpy(line,stra);
1.225 brouard 11016:
1.223 brouard 11017: /* Sample weight */
1.136 brouard 11018: cutv(stra, strb,line,' ');
11019: errno=0;
11020: dval=strtod(strb,&endptr);
11021: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 11022: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
11023: 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 11024: fflush(ficlog);
11025: return 1;
11026: }
11027: weight[i]=dval;
11028: strcpy(line,stra);
1.225 brouard 11029:
1.223 brouard 11030: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
11031: cutv(stra, strb, line, ' ');
11032: if(strb[0]=='.') { /* Missing value */
1.225 brouard 11033: lval=-1;
1.311 brouard 11034: coqvar[iv][i]=NAN;
11035: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 11036: }else{
1.225 brouard 11037: errno=0;
11038: /* what_kind_of_number(strb); */
11039: dval=strtod(strb,&endptr);
11040: /* if(strb != endptr && *endptr == '\0') */
11041: /* dval=dlval; */
11042: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
11043: if( strb[0]=='\0' || (*endptr != '\0')){
11044: 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);
11045: 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);
11046: return 1;
11047: }
11048: coqvar[iv][i]=dval;
1.226 brouard 11049: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 11050: }
11051: strcpy(line,stra);
11052: }/* end loop nqv */
1.136 brouard 11053:
1.223 brouard 11054: /* Covariate values */
1.136 brouard 11055: for (j=ncovcol;j>=1;j--){
11056: cutv(stra, strb,line,' ');
1.223 brouard 11057: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 11058: lval=-1;
1.136 brouard 11059: }else{
1.225 brouard 11060: errno=0;
11061: lval=strtol(strb,&endptr,10);
11062: if( strb[0]=='\0' || (*endptr != '\0')){
11063: 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);
11064: 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);
11065: return 1;
11066: }
1.136 brouard 11067: }
11068: if(lval <-1 || lval >1){
1.225 brouard 11069: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11070: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11071: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11072: For example, for multinomial values like 1, 2 and 3,\n \
11073: build V1=0 V2=0 for the reference value (1),\n \
11074: V1=1 V2=0 for (2) \n \
1.136 brouard 11075: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11076: output of IMaCh is often meaningless.\n \
1.136 brouard 11077: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11078: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11079: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11080: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11081: For example, for multinomial values like 1, 2 and 3,\n \
11082: build V1=0 V2=0 for the reference value (1),\n \
11083: V1=1 V2=0 for (2) \n \
1.136 brouard 11084: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11085: output of IMaCh is often meaningless.\n \
1.136 brouard 11086: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11087: return 1;
1.136 brouard 11088: }
11089: covar[j][i]=(double)(lval);
11090: strcpy(line,stra);
11091: }
11092: lstra=strlen(stra);
1.225 brouard 11093:
1.136 brouard 11094: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11095: stratrunc = &(stra[lstra-9]);
11096: num[i]=atol(stratrunc);
11097: }
11098: else
11099: num[i]=atol(stra);
11100: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11101: 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;}*/
11102:
11103: i=i+1;
11104: } /* End loop reading data */
1.225 brouard 11105:
1.136 brouard 11106: *imax=i-1; /* Number of individuals */
11107: fclose(fic);
1.225 brouard 11108:
1.136 brouard 11109: return (0);
1.164 brouard 11110: /* endread: */
1.225 brouard 11111: printf("Exiting readdata: ");
11112: fclose(fic);
11113: return (1);
1.223 brouard 11114: }
1.126 brouard 11115:
1.234 brouard 11116: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11117: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11118: while (*p2 == ' ')
1.234 brouard 11119: p2++;
11120: /* while ((*p1++ = *p2++) !=0) */
11121: /* ; */
11122: /* do */
11123: /* while (*p2 == ' ') */
11124: /* p2++; */
11125: /* while (*p1++ == *p2++); */
11126: *stri=p2;
1.145 brouard 11127: }
11128:
1.330 brouard 11129: int decoderesult( char resultline[], int nres)
1.230 brouard 11130: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11131: {
1.235 brouard 11132: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11133: char resultsav[MAXLINE];
1.330 brouard 11134: /* int resultmodel[MAXLINE]; */
1.334 brouard 11135: /* int modelresult[MAXLINE]; */
1.230 brouard 11136: char stra[80], strb[80], strc[80], strd[80],stre[80];
11137:
1.234 brouard 11138: removefirstspace(&resultline);
1.332 brouard 11139: printf("decoderesult:%s\n",resultline);
1.230 brouard 11140:
1.332 brouard 11141: strcpy(resultsav,resultline);
1.342 brouard 11142: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11143: if (strlen(resultsav) >1){
1.334 brouard 11144: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11145: }
1.353 brouard 11146: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 11147: TKresult[nres]=0; /* Combination for the nresult and the model */
11148: return (0);
11149: }
1.234 brouard 11150: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 brouard 11151: 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);
11152: 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);
11153: if(j==0)
11154: return 1;
1.234 brouard 11155: }
1.334 brouard 11156: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11157: if(nbocc(resultsav,'=') >1){
1.318 brouard 11158: 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 11159: /* 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 11160: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11161: /* If a blank, then strc="V4=" and strd='\0' */
11162: if(strc[0]=='\0'){
11163: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11164: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11165: return 1;
11166: }
1.234 brouard 11167: }else
11168: cutl(strc,strd,resultsav,'=');
1.318 brouard 11169: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11170:
1.230 brouard 11171: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11172: 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 11173: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11174: /* cptcovsel++; */
11175: if (nbocc(stra,'=') >0)
11176: strcpy(resultsav,stra); /* and analyzes it */
11177: }
1.235 brouard 11178: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11179: /* 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 11180: 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 11181: if(Typevar[k1]==0){ /* Single covariate in model */
11182: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11183: match=0;
1.318 brouard 11184: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11185: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11186: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11187: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11188: break;
11189: }
11190: }
11191: if(match == 0){
1.338 brouard 11192: 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]);
11193: 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 11194: return 1;
1.234 brouard 11195: }
1.332 brouard 11196: }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*/
11197: /* We feed resultmodel[k1]=k2; */
11198: match=0;
11199: 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 */
11200: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11201: 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 11202: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11203: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11204: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11205: break;
11206: }
11207: }
11208: if(match == 0){
1.338 brouard 11209: 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]);
11210: 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 11211: return 1;
11212: }
1.349 brouard 11213: }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 11214: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11215: match=0;
1.342 brouard 11216: /* 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 11217: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11218: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11219: /* modelresult[k2]=k1; */
1.342 brouard 11220: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11221: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11222: }
11223: }
11224: if(match == 0){
1.349 brouard 11225: 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);
11226: 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 11227: return 1;
11228: }
11229: match=0;
11230: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11231: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11232: /* modelresult[k2]=k1;*/
1.342 brouard 11233: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11234: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11235: break;
11236: }
11237: }
11238: if(match == 0){
1.349 brouard 11239: 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);
11240: 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 11241: return 1;
11242: }
11243: }/* End of testing */
1.333 brouard 11244: }/* End loop cptcovt */
1.235 brouard 11245: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11246: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11247: 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)
11248: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11249: match=0;
1.318 brouard 11250: 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 11251: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 11252: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11253: 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 11254: 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 11255: ++match;
11256: }
11257: }
11258: }
11259: if(match == 0){
1.338 brouard 11260: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11261: 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 11262: return 1;
1.234 brouard 11263: }else if(match > 1){
1.338 brouard 11264: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11265: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11266: return 1;
1.234 brouard 11267: }
11268: }
1.334 brouard 11269: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11270: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11271: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11272: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11273: /* 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*/
11274: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11275: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11276: /* 1 0 0 0 */
11277: /* 2 1 0 0 */
11278: /* 3 0 1 0 */
1.330 brouard 11279: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11280: /* 5 0 0 1 */
1.330 brouard 11281: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11282: /* 7 0 1 1 */
11283: /* 8 1 1 1 */
1.237 brouard 11284: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11285: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11286: /* V5*age V5 known which value for nres? */
11287: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11288: 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.
11289: * loop on position k1 in the MODEL LINE */
1.331 brouard 11290: /* k counting number of combination of single dummies in the equation model */
11291: /* k4 counting single dummies in the equation model */
11292: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11293: 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 11294: /* 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 11295: /* 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 11296: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11297: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11298: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11299: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11300: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11301: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11302: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11303: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11304: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11305: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11306: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11307: 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 11308: 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 11309: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11310: /* Tinvresult[nres][4]=1 */
1.334 brouard 11311: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11312: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11313: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11314: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11315: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11316: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11317: /* 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 11318: k4++;;
1.331 brouard 11319: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11320: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11321: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11322: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11323: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11324: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11325: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11326: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11327: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11328: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11329: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11330: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11331: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11332: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11333: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11334: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11335: /* 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 11336: k4q++;;
1.350 brouard 11337: }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"*/
11338: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 11339: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 11340: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11341: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11342: /* 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]]); */
11343: }else{
11344: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11345: 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)*/
11346: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
11347: precov[nres][k1]=Tvalsel[k3];
11348: }
1.342 brouard 11349: /* 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 11350: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 11351: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11352: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11353: /* 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]]); */
11354: }else{
11355: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
11356: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
11357: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
11358: precov[nres][k1]=Tvalsel[k3q];
11359: }
1.342 brouard 11360: /* 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 11361: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11362: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11363: /* 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 11364: }else{
1.332 brouard 11365: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11366: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11367: }
11368: }
1.234 brouard 11369:
1.334 brouard 11370: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11371: return (0);
11372: }
1.235 brouard 11373:
1.230 brouard 11374: int decodemodel( char model[], int lastobs)
11375: /**< This routine decodes the model and returns:
1.224 brouard 11376: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11377: * - nagesqr = 1 if age*age in the model, otherwise 0.
11378: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11379: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11380: * - cptcovage number of covariates with age*products =2
11381: * - cptcovs number of simple covariates
1.339 brouard 11382: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11383: * - 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 11384: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11385: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11386: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11387: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11388: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11389: */
1.319 brouard 11390: /* 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 11391: {
1.238 brouard 11392: int i, j, k, ks, v;
1.349 brouard 11393: int n,m;
11394: int j1, k1, k11, k12, k2, k3, k4;
11395: char modelsav[300];
11396: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11397: char *strpt;
1.349 brouard 11398: int **existcomb;
11399:
11400: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
11401: for(i=1;i<=NCOVMAX;i++)
11402: for(j=1;j<=NCOVMAX;j++)
11403: existcomb[i][j]=0;
11404:
1.145 brouard 11405: /*removespace(model);*/
1.136 brouard 11406: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 11407: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11408: if (strstr(model,"AGE") !=0){
1.192 brouard 11409: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11410: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11411: return 1;
11412: }
1.141 brouard 11413: if (strstr(model,"v") !=0){
1.338 brouard 11414: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11415: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11416: return 1;
11417: }
1.187 brouard 11418: strcpy(modelsav,model);
11419: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11420: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11421: if(strpt != model){
1.338 brouard 11422: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11423: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11424: corresponding column of parameters.\n",model);
1.338 brouard 11425: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11426: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11427: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11428: return 1;
1.225 brouard 11429: }
1.187 brouard 11430: nagesqr=1;
11431: if (strstr(model,"+age*age") !=0)
1.234 brouard 11432: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11433: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11434: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11435: else
1.234 brouard 11436: substrchaine(modelsav, model, "age*age");
1.187 brouard 11437: }else
11438: nagesqr=0;
1.349 brouard 11439: 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 11440: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11441: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 11442: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 11443: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11444: * cst, age and age*age
11445: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11446: /* including age products which are counted in cptcovage.
11447: * but the covariates which are products must be treated
11448: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 11449: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
11450: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11451: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 11452: cptcovprodage=0;
11453: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11454:
1.187 brouard 11455: /* Design
11456: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11457: * < ncovcol=8 >
11458: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11459: * k= 1 2 3 4 5 6 7 8
11460: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11461: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11462: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11463: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11464: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11465: * Tage[++cptcovage]=k
1.345 brouard 11466: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11467: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11468: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11469: * 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
11470: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11471: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11472: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11473: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11474: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11475: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11476: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11477: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11478: * p Tprod[1]@2={ 6, 5}
11479: *p Tvard[1][1]@4= {7, 8, 5, 6}
11480: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11481: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11482: *How to reorganize? Tvars(orted)
1.187 brouard 11483: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11484: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11485: * {2, 1, 4, 8, 5, 6, 3, 7}
11486: * Struct []
11487: */
1.225 brouard 11488:
1.187 brouard 11489: /* This loop fills the array Tvar from the string 'model'.*/
11490: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11491: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11492: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11493: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11494: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11495: /* k=1 Tvar[1]=2 (from V2) */
11496: /* k=5 Tvar[5] */
11497: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11498: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11499: /* } */
1.198 brouard 11500: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11501: /*
11502: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11503: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11504: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11505: }
1.187 brouard 11506: cptcovage=0;
1.351 brouard 11507:
11508: /* First loop in order to calculate */
11509: /* for age*VN*Vm
11510: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
11511: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
11512: */
11513: /* Needs FixedV[Tvardk[k][1]] */
11514: /* For others:
11515: * Sets Typevar[k];
11516: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11517: * Tposprod[k]=k11;
11518: * Tprod[k11]=k;
11519: * Tvardk[k][1] =m;
11520: * Needs FixedV[Tvardk[k][1]] == 0
11521: */
11522:
1.319 brouard 11523: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11524: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11525: 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" */
11526: if (nbocc(modelsav,'+')==0)
11527: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11528: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11529: /*scanf("%d",i);*/
1.349 brouard 11530: 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 */
11531: 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 */
11532: 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 */
11533: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
11534: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
11535: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
11536: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
11537: /* We want strb=Vn*Vm */
11538: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
11539: strcpy(strb,strd);
11540: strcat(strb,"*");
11541: strcat(strb,stre);
11542: }else{ /* strf=Vm If strf=V6 then stre=V2 */
11543: strcpy(strb,strf);
11544: strcat(strb,"*");
11545: strcat(strb,stre);
11546: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
11547: }
1.351 brouard 11548: /* 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]]]); */
11549: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 11550: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
11551: strcpy(stre,strb); /* save full b in stre */
11552: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
11553: strcpy(strf,strc); /* save short c in new short f */
11554: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
11555: /* strcpy(strc,stre);*/ /* save full e in c for future */
11556: }
11557: cptcovdageprod++; /* double product with age Which product is it? */
11558: /* 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 *\/ */
11559: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11560: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 11561: n=atoi(stre);
1.234 brouard 11562: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 11563: m=atoi(strc);
11564: cptcovage++; /* Counts the number of covariates which include age as a product */
11565: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
11566: if(existcomb[n][m] == 0){
11567: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
11568: 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);
11569: 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);
11570: fflush(ficlog);
11571: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
11572: k12++;
11573: existcomb[n][m]=k1;
11574: existcomb[m][n]=k1;
11575: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
11576: 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*/
11577: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
11578: Tvard[k1][1] =m; /* m 1 for V1*/
11579: Tvardk[k][1] =m; /* m 1 for V1*/
11580: Tvard[k1][2] =n; /* n 4 for V4*/
11581: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 11582: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 11583: 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 */
11584: for (i=1; i<=lastobs;i++){/* For fixed product */
11585: /* Computes the new covariate which is a product of
11586: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11587: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11588: }
11589: cptcovprodage++; /* Counting the number of fixed covariate with age */
11590: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11591: k12++;
11592: FixedV[ncovcolt+k12]=0;
11593: }else{ /*End of FixedV */
11594: cptcovprodvage++; /* Counting the number of varying covariate with age */
11595: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11596: k12++;
11597: FixedV[ncovcolt+k12]=1;
11598: }
11599: }else{ /* k1 Vn*Vm already exists */
11600: k11=existcomb[n][m];
11601: Tposprod[k]=k11; /* OK */
11602: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
11603: Tvardk[k][1]=m;
11604: Tvardk[k][2]=n;
11605: 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 */
11606: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11607: cptcovprodage++; /* Counting the number of fixed covariate with age */
11608: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11609: Tvar[Tage[cptcovage]]=k1;
11610: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11611: k12++;
11612: FixedV[ncovcolt+k12]=0;
11613: }else{ /* Already exists but time varying (and age) */
11614: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11615: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11616: /* Tvar[Tage[cptcovage]]=k1; */
11617: cptcovprodvage++;
11618: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11619: k12++;
11620: FixedV[ncovcolt+k12]=1;
11621: }
11622: }
11623: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
11624: /* Tvar[k]=k11; /\* HERY *\/ */
11625: } 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 */
11626: cptcovprod++;
11627: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
11628: /* covar is not filled and then is empty */
11629: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
11630: 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 */
11631: Typevar[k]=1; /* 1 for age product */
11632: cptcovage++; /* Counts the number of covariates which include age as a product */
11633: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
11634: if( FixedV[Tvar[k]] == 0){
11635: cptcovprodage++; /* Counting the number of fixed covariate with age */
11636: }else{
11637: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
11638: }
11639: /*printf("stre=%s ", stre);*/
11640: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
11641: cutl(stre,strb,strc,'V');
11642: Tvar[k]=atoi(stre);
11643: Typevar[k]=1; /* 1 for age product */
11644: cptcovage++;
11645: Tage[cptcovage]=k;
11646: if( FixedV[Tvar[k]] == 0){
11647: cptcovprodage++; /* Counting the number of fixed covariate with age */
11648: }else{
11649: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11650: }
1.349 brouard 11651: }else{ /* for product Vn*Vm */
11652: Typevar[k]=2; /* 2 for product Vn*Vm */
11653: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
11654: n=atoi(stre);
11655: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11656: m=atoi(strc);
11657: k1++;
11658: cptcovprodnoage++;
11659: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
11660: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11661: 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]);
11662: fflush(ficlog);
11663: k11=existcomb[n][m];
11664: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11665: Tposprod[k]=k11;
11666: Tprod[k11]=k;
11667: Tvardk[k][1] =m; /* m 1 for V1*/
11668: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
11669: Tvardk[k][2] =n; /* n 4 for V4*/
11670: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
11671: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
11672: existcomb[n][m]=k1;
11673: existcomb[m][n]=k1;
11674: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
11675: because this model-covariate is a construction we invent a new column
11676: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
11677: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
11678: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
11679: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
11680: /* Please remark that the new variables are model dependent */
11681: /* If we have 4 variable but the model uses only 3, like in
11682: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11683: * k= 1 2 3 4 5 6 7 8
11684: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11685: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11686: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11687: */
11688: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
11689: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
11690: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
11691: Tvard[k1][1] =m; /* m 1 for V1*/
11692: Tvardk[k][1] =m; /* m 1 for V1*/
11693: Tvard[k1][2] =n; /* n 4 for V4*/
11694: Tvardk[k][2] =n; /* n 4 for V4*/
11695: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11696: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11697: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
11698: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
11699: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
11700: 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 */
11701: for (i=1; i<=lastobs;i++){/* For fixed product */
11702: /* Computes the new covariate which is a product of
11703: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11704: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11705: }
11706: /* TvarVV[k2]=n; */
11707: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11708: /* TvarVV[k2+1]=m; */
11709: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11710: }else{ /* not FixedV */
11711: /* TvarVV[k2]=n; */
11712: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11713: /* TvarVV[k2+1]=m; */
11714: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11715: }
11716: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
11717: } /* End of product Vn*Vm */
11718: } /* End of age*double product or simple product */
11719: }else { /* not a product */
1.234 brouard 11720: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11721: /* scanf("%d",i);*/
11722: cutl(strd,strc,strb,'V');
11723: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11724: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11725: Tvar[k]=atoi(strd);
11726: Typevar[k]=0; /* 0 for simple covariates */
11727: }
11728: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11729: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11730: scanf("%d",i);*/
1.187 brouard 11731: } /* end of loop + on total covariates */
1.351 brouard 11732:
11733:
1.187 brouard 11734: } /* end if strlen(modelsave == 0) age*age might exist */
11735: } /* end if strlen(model == 0) */
1.349 brouard 11736: 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 */
11737:
1.136 brouard 11738: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11739: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11740:
1.136 brouard 11741: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11742: printf("cptcovprod=%d ", cptcovprod);
11743: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11744: scanf("%d ",i);*/
11745:
11746:
1.230 brouard 11747: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11748: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11749: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11750: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11751: k = 1 2 3 4 5 6 7 8 9
11752: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11753: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11754: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11755: Dummy[k] 1 0 0 0 3 1 1 2 3
11756: Tmodelind[combination of covar]=k;
1.225 brouard 11757: */
11758: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11759: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11760: /* 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 11761: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11762: printf("Model=1+age+%s\n\
1.349 brouard 11763: 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 11764: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11765: 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 11766: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 11767: 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 11768: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11769: 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 11770: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11771: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 11772:
11773:
11774: /* Second loop for calculating Fixed[k], Dummy[k]*/
11775:
11776:
1.349 brouard 11777: 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 11778: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11779: Fixed[k]= 0;
11780: Dummy[k]= 0;
1.225 brouard 11781: ncoveff++;
1.232 brouard 11782: ncovf++;
1.234 brouard 11783: nsd++;
11784: modell[k].maintype= FTYPE;
11785: TvarsD[nsd]=Tvar[k];
11786: TvarsDind[nsd]=k;
1.330 brouard 11787: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11788: TvarF[ncovf]=Tvar[k];
11789: TvarFind[ncovf]=k;
11790: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11791: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11792: /* }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 11793: }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 11794: Fixed[k]= 0;
11795: Dummy[k]= 1;
1.230 brouard 11796: nqfveff++;
1.234 brouard 11797: modell[k].maintype= FTYPE;
11798: modell[k].subtype= FQ;
11799: nsq++;
1.334 brouard 11800: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11801: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11802: ncovf++;
1.234 brouard 11803: TvarF[ncovf]=Tvar[k];
11804: TvarFind[ncovf]=k;
1.231 brouard 11805: 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 11806: 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 11807: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11808: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11809: /* model V1+V3+age*V1+age*V3+V1*V3 */
11810: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11811: ncovvt++;
11812: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11813: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11814:
1.227 brouard 11815: Fixed[k]= 1;
11816: Dummy[k]= 0;
1.225 brouard 11817: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11818: modell[k].maintype= VTYPE;
11819: modell[k].subtype= VD;
11820: nsd++;
11821: TvarsD[nsd]=Tvar[k];
11822: TvarsDind[nsd]=k;
1.330 brouard 11823: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11824: ncovv++; /* Only simple time varying variables */
11825: TvarV[ncovv]=Tvar[k];
1.242 brouard 11826: 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 11827: 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 */
11828: 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 11829: 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);
11830: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11831: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11832: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11833: /* model V1+V3+age*V1+age*V3+V1*V3 */
11834: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11835: ncovvt++;
11836: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11837: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11838:
1.234 brouard 11839: Fixed[k]= 1;
11840: Dummy[k]= 1;
11841: nqtveff++;
11842: modell[k].maintype= VTYPE;
11843: modell[k].subtype= VQ;
11844: ncovv++; /* Only simple time varying variables */
11845: nsq++;
1.334 brouard 11846: 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) */
11847: 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 11848: TvarV[ncovv]=Tvar[k];
1.242 brouard 11849: 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 11850: 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 */
11851: 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 11852: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11853: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 11854: /* 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 11855: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11856: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11857: ncova++;
11858: TvarA[ncova]=Tvar[k];
11859: TvarAind[ncova]=k;
1.349 brouard 11860: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11861: /** 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 11862: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11863: Fixed[k]= 2;
11864: Dummy[k]= 2;
11865: modell[k].maintype= ATYPE;
11866: modell[k].subtype= APFD;
1.349 brouard 11867: ncovta++;
11868: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
11869: TvarAVVAind[ncovta]=k;
1.240 brouard 11870: /* ncoveff++; */
1.227 brouard 11871: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11872: Fixed[k]= 2;
11873: Dummy[k]= 3;
11874: modell[k].maintype= ATYPE;
11875: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 11876: ncovta++;
11877: TvarAVVA[ncovta]=Tvar[k]; /* */
11878: TvarAVVAind[ncovta]=k;
1.240 brouard 11879: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11880: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11881: Fixed[k]= 3;
11882: Dummy[k]= 2;
11883: modell[k].maintype= ATYPE;
11884: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 11885: ncovva++;
11886: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11887: TvarVVAind[ncovva]=k;
11888: ncovta++;
11889: TvarAVVA[ncovta]=Tvar[k]; /* */
11890: TvarAVVAind[ncovta]=k;
1.240 brouard 11891: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11892: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11893: Fixed[k]= 3;
11894: Dummy[k]= 3;
11895: modell[k].maintype= ATYPE;
11896: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 11897: ncovva++;
11898: TvarVVA[ncovva]=Tvar[k]; /* */
11899: TvarVVAind[ncovva]=k;
11900: ncovta++;
11901: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11902: TvarAVVAind[ncovta]=k;
1.240 brouard 11903: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11904: }
1.349 brouard 11905: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
11906: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
11907: 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 */
11908: 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]]);
11909: Fixed[k]= 0;
11910: Dummy[k]= 0;
11911: ncoveff++;
11912: ncovf++;
11913: /* ncovv++; */
11914: /* TvarVV[ncovv]=Tvardk[k][1]; */
11915: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11916: /* ncovv++; */
11917: /* TvarVV[ncovv]=Tvardk[k][2]; */
11918: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11919: modell[k].maintype= FTYPE;
11920: TvarF[ncovf]=Tvar[k];
11921: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
11922: TvarFind[ncovf]=k;
11923: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11924: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11925: }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 */
11926: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11927: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11928: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11929: 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 */
11930: ncovvt++;
11931: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11932: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11933: ncovvt++;
11934: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11935: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11936:
11937: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11938: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
11939:
11940: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11941: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
11942: Fixed[k]= 1;
11943: Dummy[k]= 0;
11944: modell[k].maintype= FTYPE;
11945: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11946: ncovf++; /* Fixed variables without age */
11947: TvarF[ncovf]=Tvar[k];
11948: TvarFind[ncovf]=k;
11949: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11950: Fixed[k]= 0; /* Fixed product */
11951: Dummy[k]= 1;
11952: modell[k].maintype= FTYPE;
11953: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11954: ncovf++; /* Varying variables without age */
11955: TvarF[ncovf]=Tvar[k];
11956: TvarFind[ncovf]=k;
11957: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
11958: Fixed[k]= 1;
11959: Dummy[k]= 0;
11960: modell[k].maintype= VTYPE;
11961: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11962: ncovv++; /* Varying variables without age */
11963: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11964: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11965: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
11966: Fixed[k]= 1;
11967: Dummy[k]= 1;
11968: modell[k].maintype= VTYPE;
11969: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11970: ncovv++; /* Varying variables without age */
11971: TvarV[ncovv]=Tvar[k];
11972: TvarVind[ncovv]=k;
11973: }
11974: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11975: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11976: Fixed[k]= 0; /* Fixed product */
11977: Dummy[k]= 1;
11978: modell[k].maintype= FTYPE;
11979: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11980: ncovf++; /* Fixed variables without age */
11981: TvarF[ncovf]=Tvar[k];
11982: TvarFind[ncovf]=k;
11983: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
11984: Fixed[k]= 1;
11985: Dummy[k]= 1;
11986: modell[k].maintype= VTYPE;
11987: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11988: ncovv++; /* Varying variables without age */
11989: TvarV[ncovv]=Tvar[k];
11990: TvarVind[ncovv]=k;
11991: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
11992: Fixed[k]= 1;
11993: Dummy[k]= 1;
11994: modell[k].maintype= VTYPE;
11995: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11996: ncovv++; /* Varying variables without age */
11997: TvarV[ncovv]=Tvar[k];
11998: TvarVind[ncovv]=k;
11999: ncovv++; /* Varying variables without age */
12000: TvarV[ncovv]=Tvar[k];
12001: TvarVind[ncovv]=k;
12002: }
12003: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
12004: if(Tvard[k1][2] <=ncovcol){
12005: Fixed[k]= 1;
12006: Dummy[k]= 1;
12007: modell[k].maintype= VTYPE;
12008: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
12009: ncovv++; /* Varying variables without age */
12010: TvarV[ncovv]=Tvar[k];
12011: TvarVind[ncovv]=k;
12012: }else if(Tvard[k1][2] <=ncovcol+nqv){
12013: Fixed[k]= 1;
12014: Dummy[k]= 1;
12015: modell[k].maintype= VTYPE;
12016: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
12017: ncovv++; /* Varying variables without age */
12018: TvarV[ncovv]=Tvar[k];
12019: TvarVind[ncovv]=k;
12020: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12021: Fixed[k]= 1;
12022: Dummy[k]= 0;
12023: modell[k].maintype= VTYPE;
12024: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
12025: ncovv++; /* Varying variables without age */
12026: TvarV[ncovv]=Tvar[k];
12027: TvarVind[ncovv]=k;
12028: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12029: Fixed[k]= 1;
12030: Dummy[k]= 1;
12031: modell[k].maintype= VTYPE;
12032: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
12033: ncovv++; /* Varying variables without age */
12034: TvarV[ncovv]=Tvar[k];
12035: TvarVind[ncovv]=k;
12036: }
12037: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
12038: if(Tvard[k1][2] <=ncovcol){
12039: Fixed[k]= 1;
12040: Dummy[k]= 1;
12041: modell[k].maintype= VTYPE;
12042: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
12043: ncovv++; /* Varying variables without age */
12044: TvarV[ncovv]=Tvar[k];
12045: TvarVind[ncovv]=k;
12046: }else if(Tvard[k1][2] <=ncovcol+nqv){
12047: Fixed[k]= 1;
12048: Dummy[k]= 1;
12049: modell[k].maintype= VTYPE;
12050: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
12051: ncovv++; /* Varying variables without age */
12052: TvarV[ncovv]=Tvar[k];
12053: TvarVind[ncovv]=k;
12054: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12055: Fixed[k]= 1;
12056: Dummy[k]= 1;
12057: modell[k].maintype= VTYPE;
12058: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
12059: ncovv++; /* Varying variables without age */
12060: TvarV[ncovv]=Tvar[k];
12061: TvarVind[ncovv]=k;
12062: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12063: Fixed[k]= 1;
12064: Dummy[k]= 1;
12065: modell[k].maintype= VTYPE;
12066: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
12067: ncovv++; /* Varying variables without age */
12068: TvarV[ncovv]=Tvar[k];
12069: TvarVind[ncovv]=k;
12070: }
12071: }else{
12072: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12073: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12074: } /*end k1*/
12075: }
12076: }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 12077: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 12078: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
12079: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
12080: 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 */
12081: ncova++;
12082: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
12083: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
12084: ncova++;
12085: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
12086: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 12087:
1.349 brouard 12088: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
12089: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
12090: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
12091: ncovta++;
12092: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12093: TvarAVVAind[ncovta]=k;
12094: ncovta++;
12095: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12096: TvarAVVAind[ncovta]=k;
12097: }else{
12098: ncovva++; /* HERY reached */
12099: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12100: TvarVVAind[ncovva]=k;
12101: ncovva++;
12102: TvarVVA[ncovva]=Tvard[k1][2]; /* */
12103: TvarVVAind[ncovva]=k;
12104: ncovta++;
12105: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12106: TvarAVVAind[ncovta]=k;
12107: ncovta++;
12108: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12109: TvarAVVAind[ncovta]=k;
12110: }
1.339 brouard 12111: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12112: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 12113: Fixed[k]= 2;
12114: Dummy[k]= 2;
1.240 brouard 12115: modell[k].maintype= FTYPE;
12116: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 12117: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
12118: /* TvarFind[ncova]=k; */
1.339 brouard 12119: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 12120: Fixed[k]= 2; /* Fixed product */
12121: Dummy[k]= 3;
1.240 brouard 12122: modell[k].maintype= FTYPE;
12123: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 12124: /* TvarF[ncova]=Tvar[k]; */
12125: /* TvarFind[ncova]=k; */
1.339 brouard 12126: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 12127: Fixed[k]= 3;
12128: Dummy[k]= 2;
1.240 brouard 12129: modell[k].maintype= VTYPE;
12130: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 12131: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
12132: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12133: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 12134: Fixed[k]= 3;
12135: Dummy[k]= 3;
1.240 brouard 12136: modell[k].maintype= VTYPE;
12137: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 12138: /* ncovv++; /\* Varying variables without age *\/ */
12139: /* TvarV[ncovv]=Tvar[k]; */
12140: /* TvarVind[ncovv]=k; */
1.240 brouard 12141: }
1.339 brouard 12142: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12143: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 12144: Fixed[k]= 2; /* Fixed product */
12145: Dummy[k]= 2;
1.240 brouard 12146: modell[k].maintype= FTYPE;
12147: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 12148: /* ncova++; /\* Fixed variables with age *\/ */
12149: /* TvarF[ncovf]=Tvar[k]; */
12150: /* TvarFind[ncovf]=k; */
1.339 brouard 12151: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 12152: Fixed[k]= 2;
12153: Dummy[k]= 3;
1.240 brouard 12154: modell[k].maintype= VTYPE;
12155: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 12156: /* ncova++; /\* Varying variables with age *\/ */
12157: /* TvarV[ncova]=Tvar[k]; */
12158: /* TvarVind[ncova]=k; */
1.339 brouard 12159: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 12160: Fixed[k]= 3;
12161: Dummy[k]= 2;
1.240 brouard 12162: modell[k].maintype= VTYPE;
12163: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 12164: ncova++; /* Varying variables without age */
12165: TvarV[ncova]=Tvar[k];
12166: TvarVind[ncova]=k;
12167: /* ncova++; /\* Varying variables without age *\/ */
12168: /* TvarV[ncova]=Tvar[k]; */
12169: /* TvarVind[ncova]=k; */
1.240 brouard 12170: }
1.339 brouard 12171: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12172: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12173: Fixed[k]= 2;
12174: Dummy[k]= 2;
1.240 brouard 12175: modell[k].maintype= VTYPE;
12176: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 12177: /* ncova++; /\* Varying variables with age *\/ */
12178: /* TvarV[ncova]=Tvar[k]; */
12179: /* TvarVind[ncova]=k; */
1.240 brouard 12180: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12181: Fixed[k]= 2;
12182: Dummy[k]= 3;
1.240 brouard 12183: modell[k].maintype= VTYPE;
12184: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 12185: /* ncova++; /\* Varying variables with age *\/ */
12186: /* TvarV[ncova]=Tvar[k]; */
12187: /* TvarVind[ncova]=k; */
1.240 brouard 12188: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12189: Fixed[k]= 3;
12190: Dummy[k]= 2;
1.240 brouard 12191: modell[k].maintype= VTYPE;
12192: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 12193: /* ncova++; /\* Varying variables with age *\/ */
12194: /* TvarV[ncova]=Tvar[k]; */
12195: /* TvarVind[ncova]=k; */
1.240 brouard 12196: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12197: Fixed[k]= 3;
12198: Dummy[k]= 3;
1.240 brouard 12199: modell[k].maintype= VTYPE;
12200: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 12201: /* ncova++; /\* Varying variables with age *\/ */
12202: /* TvarV[ncova]=Tvar[k]; */
12203: /* TvarVind[ncova]=k; */
1.240 brouard 12204: }
1.339 brouard 12205: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12206: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12207: Fixed[k]= 2;
12208: Dummy[k]= 2;
1.240 brouard 12209: modell[k].maintype= VTYPE;
12210: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 12211: /* ncova++; /\* Varying variables with age *\/ */
12212: /* TvarV[ncova]=Tvar[k]; */
12213: /* TvarVind[ncova]=k; */
1.240 brouard 12214: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12215: Fixed[k]= 2;
12216: Dummy[k]= 3;
1.240 brouard 12217: modell[k].maintype= VTYPE;
12218: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 12219: /* ncova++; /\* Varying variables with age *\/ */
12220: /* TvarV[ncova]=Tvar[k]; */
12221: /* TvarVind[ncova]=k; */
1.240 brouard 12222: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12223: Fixed[k]= 3;
12224: Dummy[k]= 2;
1.240 brouard 12225: modell[k].maintype= VTYPE;
12226: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 12227: /* ncova++; /\* Varying variables with age *\/ */
12228: /* TvarV[ncova]=Tvar[k]; */
12229: /* TvarVind[ncova]=k; */
1.240 brouard 12230: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12231: Fixed[k]= 3;
12232: Dummy[k]= 3;
1.240 brouard 12233: modell[k].maintype= VTYPE;
12234: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 12235: /* ncova++; /\* Varying variables with age *\/ */
12236: /* TvarV[ncova]=Tvar[k]; */
12237: /* TvarVind[ncova]=k; */
1.240 brouard 12238: }
1.227 brouard 12239: }else{
1.240 brouard 12240: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12241: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12242: } /*end k1*/
1.349 brouard 12243: } else{
1.226 brouard 12244: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12245: 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 12246: }
1.342 brouard 12247: /* 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]); */
12248: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12249: 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]);
12250: }
1.349 brouard 12251: ncovvta=ncovva;
1.227 brouard 12252: /* Searching for doublons in the model */
12253: for(k1=1; k1<= cptcovt;k1++){
12254: for(k2=1; k2 <k1;k2++){
1.285 brouard 12255: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12256: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12257: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12258: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12259: 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]);
12260: 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 12261: return(1);
12262: }
12263: }else if (Typevar[k1] ==2){
12264: k3=Tposprod[k1];
12265: k4=Tposprod[k2];
12266: 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 12267: 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]]);
12268: 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 12269: return(1);
12270: }
12271: }
1.227 brouard 12272: }
12273: }
1.225 brouard 12274: }
12275: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12276: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12277: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12278: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 12279:
12280: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12281: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12282: /*endread:*/
1.225 brouard 12283: printf("Exiting decodemodel: ");
12284: return (1);
1.136 brouard 12285: }
12286:
1.169 brouard 12287: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12288: {/* Check ages at death */
1.136 brouard 12289: int i, m;
1.218 brouard 12290: int firstone=0;
12291:
1.136 brouard 12292: for (i=1; i<=imx; i++) {
12293: for(m=2; (m<= maxwav); m++) {
12294: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12295: anint[m][i]=9999;
1.216 brouard 12296: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12297: s[m][i]=-1;
1.136 brouard 12298: }
12299: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12300: *nberr = *nberr + 1;
1.218 brouard 12301: if(firstone == 0){
12302: firstone=1;
1.260 brouard 12303: 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 12304: }
1.262 brouard 12305: 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 12306: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12307: }
12308: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12309: (*nberr)++;
1.259 brouard 12310: 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 12311: 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 12312: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12313: }
12314: }
12315: }
12316:
12317: for (i=1; i<=imx; i++) {
12318: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12319: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12320: 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 12321: if (s[m][i] >= nlstate+1) {
1.169 brouard 12322: if(agedc[i]>0){
12323: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12324: agev[m][i]=agedc[i];
1.214 brouard 12325: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12326: }else {
1.136 brouard 12327: if ((int)andc[i]!=9999){
12328: nbwarn++;
12329: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12330: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12331: agev[m][i]=-1;
12332: }
12333: }
1.169 brouard 12334: } /* agedc > 0 */
1.214 brouard 12335: } /* end if */
1.136 brouard 12336: else if(s[m][i] !=9){ /* Standard case, age in fractional
12337: years but with the precision of a month */
12338: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12339: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12340: agev[m][i]=1;
12341: else if(agev[m][i] < *agemin){
12342: *agemin=agev[m][i];
12343: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12344: }
12345: else if(agev[m][i] >*agemax){
12346: *agemax=agev[m][i];
1.156 brouard 12347: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12348: }
12349: /*agev[m][i]=anint[m][i]-annais[i];*/
12350: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12351: } /* en if 9*/
1.136 brouard 12352: else { /* =9 */
1.214 brouard 12353: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12354: agev[m][i]=1;
12355: s[m][i]=-1;
12356: }
12357: }
1.214 brouard 12358: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12359: agev[m][i]=1;
1.214 brouard 12360: else{
12361: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12362: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12363: agev[m][i]=0;
12364: }
12365: } /* End for lastpass */
12366: }
1.136 brouard 12367:
12368: for (i=1; i<=imx; i++) {
12369: for(m=firstpass; (m<=lastpass); m++){
12370: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12371: (*nberr)++;
1.136 brouard 12372: 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);
12373: 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);
12374: return 1;
12375: }
12376: }
12377: }
12378:
12379: /*for (i=1; i<=imx; i++){
12380: for (m=firstpass; (m<lastpass); m++){
12381: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12382: }
12383:
12384: }*/
12385:
12386:
1.139 brouard 12387: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12388: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12389:
12390: return (0);
1.164 brouard 12391: /* endread:*/
1.136 brouard 12392: printf("Exiting calandcheckages: ");
12393: return (1);
12394: }
12395:
1.172 brouard 12396: #if defined(_MSC_VER)
12397: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12398: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12399: //#include "stdafx.h"
12400: //#include <stdio.h>
12401: //#include <tchar.h>
12402: //#include <windows.h>
12403: //#include <iostream>
12404: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12405:
12406: LPFN_ISWOW64PROCESS fnIsWow64Process;
12407:
12408: BOOL IsWow64()
12409: {
12410: BOOL bIsWow64 = FALSE;
12411:
12412: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12413: // (HANDLE, PBOOL);
12414:
12415: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12416:
12417: HMODULE module = GetModuleHandle(_T("kernel32"));
12418: const char funcName[] = "IsWow64Process";
12419: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12420: GetProcAddress(module, funcName);
12421:
12422: if (NULL != fnIsWow64Process)
12423: {
12424: if (!fnIsWow64Process(GetCurrentProcess(),
12425: &bIsWow64))
12426: //throw std::exception("Unknown error");
12427: printf("Unknown error\n");
12428: }
12429: return bIsWow64 != FALSE;
12430: }
12431: #endif
1.177 brouard 12432:
1.191 brouard 12433: void syscompilerinfo(int logged)
1.292 brouard 12434: {
12435: #include <stdint.h>
12436:
12437: /* #include "syscompilerinfo.h"*/
1.185 brouard 12438: /* command line Intel compiler 32bit windows, XP compatible:*/
12439: /* /GS /W3 /Gy
12440: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12441: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12442: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12443: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12444: */
12445: /* 64 bits */
1.185 brouard 12446: /*
12447: /GS /W3 /Gy
12448: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12449: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12450: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12451: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12452: /* Optimization are useless and O3 is slower than O2 */
12453: /*
12454: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12455: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12456: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12457: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12458: */
1.186 brouard 12459: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12460: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12461: /PDB:"visual studio
12462: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12463: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12464: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12465: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12466: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12467: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12468: uiAccess='false'"
12469: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12470: /NOLOGO /TLBID:1
12471: */
1.292 brouard 12472:
12473:
1.177 brouard 12474: #if defined __INTEL_COMPILER
1.178 brouard 12475: #if defined(__GNUC__)
12476: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12477: #endif
1.177 brouard 12478: #elif defined(__GNUC__)
1.179 brouard 12479: #ifndef __APPLE__
1.174 brouard 12480: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12481: #endif
1.177 brouard 12482: struct utsname sysInfo;
1.178 brouard 12483: int cross = CROSS;
12484: if (cross){
12485: printf("Cross-");
1.191 brouard 12486: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12487: }
1.174 brouard 12488: #endif
12489:
1.191 brouard 12490: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12491: #if defined(__clang__)
1.191 brouard 12492: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12493: #endif
12494: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12495: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12496: #endif
12497: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12498: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12499: #endif
12500: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12501: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12502: #endif
12503: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12504: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12505: #endif
12506: #if defined(_MSC_VER)
1.191 brouard 12507: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12508: #endif
12509: #if defined(__PGI)
1.191 brouard 12510: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12511: #endif
12512: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12513: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12514: #endif
1.191 brouard 12515: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12516:
1.167 brouard 12517: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12518: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12519: // Windows (x64 and x86)
1.191 brouard 12520: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12521: #elif __unix__ // all unices, not all compilers
12522: // Unix
1.191 brouard 12523: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12524: #elif __linux__
12525: // linux
1.191 brouard 12526: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12527: #elif __APPLE__
1.174 brouard 12528: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12529: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12530: #endif
12531:
12532: /* __MINGW32__ */
12533: /* __CYGWIN__ */
12534: /* __MINGW64__ */
12535: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12536: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12537: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12538: /* _WIN64 // Defined for applications for Win64. */
12539: /* _M_X64 // Defined for compilations that target x64 processors. */
12540: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12541:
1.167 brouard 12542: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12543: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12544: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12545: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12546: #else
1.191 brouard 12547: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12548: #endif
12549:
1.169 brouard 12550: #if defined(__GNUC__)
12551: # if defined(__GNUC_PATCHLEVEL__)
12552: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12553: + __GNUC_MINOR__ * 100 \
12554: + __GNUC_PATCHLEVEL__)
12555: # else
12556: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12557: + __GNUC_MINOR__ * 100)
12558: # endif
1.174 brouard 12559: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12560: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12561:
12562: if (uname(&sysInfo) != -1) {
12563: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12564: 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 12565: }
12566: else
12567: perror("uname() error");
1.179 brouard 12568: //#ifndef __INTEL_COMPILER
12569: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12570: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12571: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12572: #endif
1.169 brouard 12573: #endif
1.172 brouard 12574:
1.286 brouard 12575: // void main ()
1.172 brouard 12576: // {
1.169 brouard 12577: #if defined(_MSC_VER)
1.174 brouard 12578: if (IsWow64()){
1.191 brouard 12579: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12580: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12581: }
12582: else{
1.191 brouard 12583: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12584: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12585: }
1.172 brouard 12586: // printf("\nPress Enter to continue...");
12587: // getchar();
12588: // }
12589:
1.169 brouard 12590: #endif
12591:
1.167 brouard 12592:
1.219 brouard 12593: }
1.136 brouard 12594:
1.219 brouard 12595: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12596: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12597: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12598: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12599: /* double ftolpl = 1.e-10; */
1.180 brouard 12600: double age, agebase, agelim;
1.203 brouard 12601: double tot;
1.180 brouard 12602:
1.202 brouard 12603: strcpy(filerespl,"PL_");
12604: strcat(filerespl,fileresu);
12605: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12606: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12607: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12608: }
1.288 brouard 12609: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12610: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12611: pstamp(ficrespl);
1.288 brouard 12612: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12613: fprintf(ficrespl,"#Age ");
12614: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12615: fprintf(ficrespl,"\n");
1.180 brouard 12616:
1.219 brouard 12617: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12618:
1.219 brouard 12619: agebase=ageminpar;
12620: agelim=agemaxpar;
1.180 brouard 12621:
1.227 brouard 12622: /* i1=pow(2,ncoveff); */
1.234 brouard 12623: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12624: if (cptcovn < 1){i1=1;}
1.180 brouard 12625:
1.337 brouard 12626: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12627: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12628: k=TKresult[nres];
1.338 brouard 12629: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12630: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12631: /* continue; */
1.235 brouard 12632:
1.238 brouard 12633: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12634: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12635: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12636: /* k=k+1; */
12637: /* to clean */
1.332 brouard 12638: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12639: fprintf(ficrespl,"#******");
12640: printf("#******");
12641: fprintf(ficlog,"#******");
1.337 brouard 12642: 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 12643: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12644: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12645: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12646: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12647: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12648: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12649: }
12650: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12651: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12652: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12653: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12654: /* } */
1.238 brouard 12655: fprintf(ficrespl,"******\n");
12656: printf("******\n");
12657: fprintf(ficlog,"******\n");
12658: if(invalidvarcomb[k]){
12659: printf("\nCombination (%d) ignored because no case \n",k);
12660: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12661: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12662: continue;
12663: }
1.219 brouard 12664:
1.238 brouard 12665: fprintf(ficrespl,"#Age ");
1.337 brouard 12666: /* for(j=1;j<=cptcoveff;j++) { */
12667: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12668: /* } */
12669: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12670: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12671: }
12672: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12673: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12674:
1.238 brouard 12675: for (age=agebase; age<=agelim; age++){
12676: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12677: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12678: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12679: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12680: /* for(j=1;j<=cptcoveff;j++) */
12681: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12682: for(j=1;j<=cptcovs;j++)
12683: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12684: tot=0.;
12685: for(i=1; i<=nlstate;i++){
12686: tot += prlim[i][i];
12687: fprintf(ficrespl," %.5f", prlim[i][i]);
12688: }
12689: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12690: } /* Age */
12691: /* was end of cptcod */
1.337 brouard 12692: } /* nres */
12693: /* } /\* for each combination *\/ */
1.219 brouard 12694: return 0;
1.180 brouard 12695: }
12696:
1.218 brouard 12697: 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 12698: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12699:
12700: /* Computes the back prevalence limit for any combination of covariate values
12701: * at any age between ageminpar and agemaxpar
12702: */
1.235 brouard 12703: int i, j, k, i1, nres=0 ;
1.217 brouard 12704: /* double ftolpl = 1.e-10; */
12705: double age, agebase, agelim;
12706: double tot;
1.218 brouard 12707: /* double ***mobaverage; */
12708: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12709:
12710: strcpy(fileresplb,"PLB_");
12711: strcat(fileresplb,fileresu);
12712: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12713: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12714: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12715: }
1.288 brouard 12716: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12717: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12718: pstamp(ficresplb);
1.288 brouard 12719: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12720: fprintf(ficresplb,"#Age ");
12721: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12722: fprintf(ficresplb,"\n");
12723:
1.218 brouard 12724:
12725: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12726:
12727: agebase=ageminpar;
12728: agelim=agemaxpar;
12729:
12730:
1.227 brouard 12731: i1=pow(2,cptcoveff);
1.218 brouard 12732: if (cptcovn < 1){i1=1;}
1.227 brouard 12733:
1.238 brouard 12734: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12735: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12736: k=TKresult[nres];
12737: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12738: /* if(i1 != 1 && TKresult[nres]!= k) */
12739: /* continue; */
12740: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12741: fprintf(ficresplb,"#******");
12742: printf("#******");
12743: fprintf(ficlog,"#******");
1.338 brouard 12744: 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) */
12745: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12746: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12747: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12748: }
1.338 brouard 12749: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12750: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12751: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12752: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12753: /* } */
12754: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12755: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12756: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12757: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12758: /* } */
1.238 brouard 12759: fprintf(ficresplb,"******\n");
12760: printf("******\n");
12761: fprintf(ficlog,"******\n");
12762: if(invalidvarcomb[k]){
12763: printf("\nCombination (%d) ignored because no cases \n",k);
12764: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12765: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12766: continue;
12767: }
1.218 brouard 12768:
1.238 brouard 12769: fprintf(ficresplb,"#Age ");
1.338 brouard 12770: for(j=1;j<=cptcovs;j++) {
12771: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12772: }
12773: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12774: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12775:
12776:
1.238 brouard 12777: for (age=agebase; age<=agelim; age++){
12778: /* for (age=agebase; age<=agebase; age++){ */
12779: if(mobilavproj > 0){
12780: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12781: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12782: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12783: }else if (mobilavproj == 0){
12784: 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);
12785: 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);
12786: exit(1);
12787: }else{
12788: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12789: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12790: /* printf("TOTOT\n"); */
12791: /* exit(1); */
1.238 brouard 12792: }
12793: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12794: for(j=1;j<=cptcovs;j++)
12795: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12796: tot=0.;
12797: for(i=1; i<=nlstate;i++){
12798: tot += bprlim[i][i];
12799: fprintf(ficresplb," %.5f", bprlim[i][i]);
12800: }
12801: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12802: } /* Age */
12803: /* was end of cptcod */
1.255 brouard 12804: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12805: /* } /\* end of any combination *\/ */
1.238 brouard 12806: } /* end of nres */
1.218 brouard 12807: /* hBijx(p, bage, fage); */
12808: /* fclose(ficrespijb); */
12809:
12810: return 0;
1.217 brouard 12811: }
1.218 brouard 12812:
1.180 brouard 12813: int hPijx(double *p, int bage, int fage){
12814: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12815: /* to be optimized with precov */
1.180 brouard 12816: int stepsize;
12817: int agelim;
12818: int hstepm;
12819: int nhstepm;
1.235 brouard 12820: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12821:
12822: double agedeb;
12823: double ***p3mat;
12824:
1.337 brouard 12825: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12826: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12827: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12828: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12829: }
12830: printf("Computing pij: result on file '%s' \n", filerespij);
12831: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12832:
12833: stepsize=(int) (stepm+YEARM-1)/YEARM;
12834: /*if (stepm<=24) stepsize=2;*/
12835:
12836: agelim=AGESUP;
12837: hstepm=stepsize*YEARM; /* Every year of age */
12838: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12839:
12840: /* hstepm=1; aff par mois*/
12841: pstamp(ficrespij);
12842: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12843: i1= pow(2,cptcoveff);
12844: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12845: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12846: /* k=k+1; */
12847: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12848: k=TKresult[nres];
1.338 brouard 12849: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12850: /* for(k=1; k<=i1;k++){ */
12851: /* if(i1 != 1 && TKresult[nres]!= k) */
12852: /* continue; */
12853: fprintf(ficrespij,"\n#****** ");
12854: for(j=1;j<=cptcovs;j++){
12855: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12856: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12857: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12858: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12859: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12860: }
12861: fprintf(ficrespij,"******\n");
12862:
12863: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12864: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12865: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12866:
12867: /* nhstepm=nhstepm*YEARM; aff par mois*/
12868:
12869: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12870: oldm=oldms;savm=savms;
12871: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12872: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12873: for(i=1; i<=nlstate;i++)
12874: for(j=1; j<=nlstate+ndeath;j++)
12875: fprintf(ficrespij," %1d-%1d",i,j);
12876: fprintf(ficrespij,"\n");
12877: for (h=0; h<=nhstepm; h++){
12878: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12879: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12880: for(i=1; i<=nlstate;i++)
12881: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12882: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12883: fprintf(ficrespij,"\n");
12884: }
1.337 brouard 12885: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12886: fprintf(ficrespij,"\n");
1.180 brouard 12887: }
1.337 brouard 12888: }
12889: /*}*/
12890: return 0;
1.180 brouard 12891: }
1.218 brouard 12892:
12893: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12894: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12895: /* To be optimized with precov */
1.217 brouard 12896: int stepsize;
1.218 brouard 12897: /* int agelim; */
12898: int ageminl;
1.217 brouard 12899: int hstepm;
12900: int nhstepm;
1.238 brouard 12901: int h, i, i1, j, k, nres;
1.218 brouard 12902:
1.217 brouard 12903: double agedeb;
12904: double ***p3mat;
1.218 brouard 12905:
12906: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12907: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12908: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12909: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12910: }
12911: printf("Computing pij back: result on file '%s' \n", filerespijb);
12912: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12913:
12914: stepsize=(int) (stepm+YEARM-1)/YEARM;
12915: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12916:
1.218 brouard 12917: /* agelim=AGESUP; */
1.289 brouard 12918: ageminl=AGEINF; /* was 30 */
1.218 brouard 12919: hstepm=stepsize*YEARM; /* Every year of age */
12920: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12921:
12922: /* hstepm=1; aff par mois*/
12923: pstamp(ficrespijb);
1.255 brouard 12924: 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 12925: i1= pow(2,cptcoveff);
1.218 brouard 12926: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12927: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12928: /* k=k+1; */
1.238 brouard 12929: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12930: k=TKresult[nres];
1.338 brouard 12931: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12932: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12933: /* if(i1 != 1 && TKresult[nres]!= k) */
12934: /* continue; */
12935: fprintf(ficrespijb,"\n#****** ");
12936: for(j=1;j<=cptcovs;j++){
1.338 brouard 12937: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12938: /* for(j=1;j<=cptcoveff;j++) */
12939: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12940: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12941: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12942: }
12943: fprintf(ficrespijb,"******\n");
12944: if(invalidvarcomb[k]){ /* Is it necessary here? */
12945: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12946: continue;
12947: }
12948:
12949: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12950: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12951: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12952: 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 */
12953: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12954:
12955: /* nhstepm=nhstepm*YEARM; aff par mois*/
12956:
12957: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12958: /* and memory limitations if stepm is small */
12959:
12960: /* oldm=oldms;savm=savms; */
12961: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12962: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12963: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12964: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12965: for(i=1; i<=nlstate;i++)
12966: for(j=1; j<=nlstate+ndeath;j++)
12967: fprintf(ficrespijb," %1d-%1d",i,j);
12968: fprintf(ficrespijb,"\n");
12969: for (h=0; h<=nhstepm; h++){
12970: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12971: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12972: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12973: for(i=1; i<=nlstate;i++)
12974: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12975: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12976: fprintf(ficrespijb,"\n");
1.337 brouard 12977: }
12978: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12979: fprintf(ficrespijb,"\n");
12980: } /* end age deb */
12981: /* } /\* end combination *\/ */
1.238 brouard 12982: } /* end nres */
1.218 brouard 12983: return 0;
12984: } /* hBijx */
1.217 brouard 12985:
1.180 brouard 12986:
1.136 brouard 12987: /***********************************************/
12988: /**************** Main Program *****************/
12989: /***********************************************/
12990:
12991: int main(int argc, char *argv[])
12992: {
12993: #ifdef GSL
12994: const gsl_multimin_fminimizer_type *T;
12995: size_t iteri = 0, it;
12996: int rval = GSL_CONTINUE;
12997: int status = GSL_SUCCESS;
12998: double ssval;
12999: #endif
13000: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 13001: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
13002: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 13003: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 13004: int jj, ll, li, lj, lk;
1.136 brouard 13005: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 13006: int num_filled;
1.136 brouard 13007: int itimes;
13008: int NDIM=2;
13009: int vpopbased=0;
1.235 brouard 13010: int nres=0;
1.258 brouard 13011: int endishere=0;
1.277 brouard 13012: int noffset=0;
1.274 brouard 13013: int ncurrv=0; /* Temporary variable */
13014:
1.164 brouard 13015: char ca[32], cb[32];
1.136 brouard 13016: /* FILE *fichtm; *//* Html File */
13017: /* FILE *ficgp;*/ /*Gnuplot File */
13018: struct stat info;
1.191 brouard 13019: double agedeb=0.;
1.194 brouard 13020:
13021: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 13022: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 13023:
1.165 brouard 13024: double fret;
1.191 brouard 13025: double dum=0.; /* Dummy variable */
1.136 brouard 13026: double ***p3mat;
1.218 brouard 13027: /* double ***mobaverage; */
1.319 brouard 13028: double wald;
1.164 brouard 13029:
1.351 brouard 13030: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 13031: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
13032:
1.234 brouard 13033: char modeltemp[MAXLINE];
1.332 brouard 13034: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 13035:
1.136 brouard 13036: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 13037: char *tok, *val; /* pathtot */
1.334 brouard 13038: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 13039: int c, h , cpt, c2;
1.191 brouard 13040: int jl=0;
13041: int i1, j1, jk, stepsize=0;
1.194 brouard 13042: int count=0;
13043:
1.164 brouard 13044: int *tab;
1.136 brouard 13045: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 13046: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
13047: /* double anprojf, mprojf, jprojf; */
13048: /* double jintmean,mintmean,aintmean; */
13049: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13050: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13051: double yrfproj= 10.0; /* Number of years of forward projections */
13052: double yrbproj= 10.0; /* Number of years of backward projections */
13053: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 13054: int mobilav=0,popforecast=0;
1.191 brouard 13055: int hstepm=0, nhstepm=0;
1.136 brouard 13056: int agemortsup;
13057: float sumlpop=0.;
13058: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
13059: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
13060:
1.191 brouard 13061: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 13062: double ftolpl=FTOL;
13063: double **prlim;
1.217 brouard 13064: double **bprlim;
1.317 brouard 13065: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
13066: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 13067: double ***paramstart; /* Matrix of starting parameter values */
13068: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 13069: double **matcov; /* Matrix of covariance */
1.203 brouard 13070: double **hess; /* Hessian matrix */
1.136 brouard 13071: double ***delti3; /* Scale */
13072: double *delti; /* Scale */
13073: double ***eij, ***vareij;
13074: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 13075:
1.136 brouard 13076: double *epj, vepp;
1.164 brouard 13077:
1.273 brouard 13078: double dateprev1, dateprev2;
1.296 brouard 13079: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
13080: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
13081:
1.217 brouard 13082:
1.136 brouard 13083: double **ximort;
1.145 brouard 13084: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 13085: int *dcwave;
13086:
1.164 brouard 13087: char z[1]="c";
1.136 brouard 13088:
13089: /*char *strt;*/
13090: char strtend[80];
1.126 brouard 13091:
1.164 brouard 13092:
1.126 brouard 13093: /* setlocale (LC_ALL, ""); */
13094: /* bindtextdomain (PACKAGE, LOCALEDIR); */
13095: /* textdomain (PACKAGE); */
13096: /* setlocale (LC_CTYPE, ""); */
13097: /* setlocale (LC_MESSAGES, ""); */
13098:
13099: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 13100: rstart_time = time(NULL);
13101: /* (void) gettimeofday(&start_time,&tzp);*/
13102: start_time = *localtime(&rstart_time);
1.126 brouard 13103: curr_time=start_time;
1.157 brouard 13104: /*tml = *localtime(&start_time.tm_sec);*/
13105: /* strcpy(strstart,asctime(&tml)); */
13106: strcpy(strstart,asctime(&start_time));
1.126 brouard 13107:
13108: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13109: /* tp.tm_sec = tp.tm_sec +86400; */
13110: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13111: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13112: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13113: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13114: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13115: /* strt=asctime(&tmg); */
13116: /* printf("Time(after) =%s",strstart); */
13117: /* (void) time (&time_value);
13118: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13119: * tm = *localtime(&time_value);
13120: * strstart=asctime(&tm);
13121: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13122: */
13123:
13124: nberr=0; /* Number of errors and warnings */
13125: nbwarn=0;
1.184 brouard 13126: #ifdef WIN32
13127: _getcwd(pathcd, size);
13128: #else
1.126 brouard 13129: getcwd(pathcd, size);
1.184 brouard 13130: #endif
1.191 brouard 13131: syscompilerinfo(0);
1.196 brouard 13132: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13133: if(argc <=1){
13134: printf("\nEnter the parameter file name: ");
1.205 brouard 13135: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13136: printf("ERROR Empty parameter file name\n");
13137: goto end;
13138: }
1.126 brouard 13139: i=strlen(pathr);
13140: if(pathr[i-1]=='\n')
13141: pathr[i-1]='\0';
1.156 brouard 13142: i=strlen(pathr);
1.205 brouard 13143: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13144: pathr[i-1]='\0';
1.205 brouard 13145: }
13146: i=strlen(pathr);
13147: if( i==0 ){
13148: printf("ERROR Empty parameter file name\n");
13149: goto end;
13150: }
13151: for (tok = pathr; tok != NULL; ){
1.126 brouard 13152: printf("Pathr |%s|\n",pathr);
13153: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13154: printf("val= |%s| pathr=%s\n",val,pathr);
13155: strcpy (pathtot, val);
13156: if(pathr[0] == '\0') break; /* Dirty */
13157: }
13158: }
1.281 brouard 13159: else if (argc<=2){
13160: strcpy(pathtot,argv[1]);
13161: }
1.126 brouard 13162: else{
13163: strcpy(pathtot,argv[1]);
1.281 brouard 13164: strcpy(z,argv[2]);
13165: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13166: }
13167: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13168: /*cygwin_split_path(pathtot,path,optionfile);
13169: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13170: /* cutv(path,optionfile,pathtot,'\\');*/
13171:
13172: /* Split argv[0], imach program to get pathimach */
13173: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13174: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13175: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13176: /* strcpy(pathimach,argv[0]); */
13177: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13178: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13179: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13180: #ifdef WIN32
13181: _chdir(path); /* Can be a relative path */
13182: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13183: #else
1.126 brouard 13184: chdir(path); /* Can be a relative path */
1.184 brouard 13185: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13186: #endif
13187: printf("Current directory %s!\n",pathcd);
1.126 brouard 13188: strcpy(command,"mkdir ");
13189: strcat(command,optionfilefiname);
13190: if((outcmd=system(command)) != 0){
1.169 brouard 13191: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13192: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13193: /* fclose(ficlog); */
13194: /* exit(1); */
13195: }
13196: /* if((imk=mkdir(optionfilefiname))<0){ */
13197: /* perror("mkdir"); */
13198: /* } */
13199:
13200: /*-------- arguments in the command line --------*/
13201:
1.186 brouard 13202: /* Main Log file */
1.126 brouard 13203: strcat(filelog, optionfilefiname);
13204: strcat(filelog,".log"); /* */
13205: if((ficlog=fopen(filelog,"w"))==NULL) {
13206: printf("Problem with logfile %s\n",filelog);
13207: goto end;
13208: }
13209: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13210: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13211: fprintf(ficlog,"\nEnter the parameter file name: \n");
13212: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13213: path=%s \n\
13214: optionfile=%s\n\
13215: optionfilext=%s\n\
1.156 brouard 13216: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13217:
1.197 brouard 13218: syscompilerinfo(1);
1.167 brouard 13219:
1.126 brouard 13220: printf("Local time (at start):%s",strstart);
13221: fprintf(ficlog,"Local time (at start): %s",strstart);
13222: fflush(ficlog);
13223: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13224: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13225:
13226: /* */
13227: strcpy(fileres,"r");
13228: strcat(fileres, optionfilefiname);
1.201 brouard 13229: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13230: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13231: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13232:
1.186 brouard 13233: /* Main ---------arguments file --------*/
1.126 brouard 13234:
13235: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13236: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13237: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13238: fflush(ficlog);
1.149 brouard 13239: /* goto end; */
13240: exit(70);
1.126 brouard 13241: }
13242:
13243: strcpy(filereso,"o");
1.201 brouard 13244: strcat(filereso,fileresu);
1.126 brouard 13245: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13246: printf("Problem with Output resultfile: %s\n", filereso);
13247: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13248: fflush(ficlog);
13249: goto end;
13250: }
1.278 brouard 13251: /*-------- Rewriting parameter file ----------*/
13252: strcpy(rfileres,"r"); /* "Rparameterfile */
13253: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13254: strcat(rfileres,"."); /* */
13255: strcat(rfileres,optionfilext); /* Other files have txt extension */
13256: if((ficres =fopen(rfileres,"w"))==NULL) {
13257: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13258: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13259: fflush(ficlog);
13260: goto end;
13261: }
13262: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13263:
1.278 brouard 13264:
1.126 brouard 13265: /* Reads comments: lines beginning with '#' */
13266: numlinepar=0;
1.277 brouard 13267: /* Is it a BOM UTF-8 Windows file? */
13268: /* First parameter line */
1.197 brouard 13269: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13270: noffset=0;
13271: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13272: {
13273: noffset=noffset+3;
13274: printf("# File is an UTF8 Bom.\n"); // 0xBF
13275: }
1.302 brouard 13276: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13277: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13278: {
13279: noffset=noffset+2;
13280: printf("# File is an UTF16BE BOM file\n");
13281: }
13282: else if( line[0] == 0 && line[1] == 0)
13283: {
13284: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13285: noffset=noffset+4;
13286: printf("# File is an UTF16BE BOM file\n");
13287: }
13288: } else{
13289: ;/*printf(" Not a BOM file\n");*/
13290: }
13291:
1.197 brouard 13292: /* If line starts with a # it is a comment */
1.277 brouard 13293: if (line[noffset] == '#') {
1.197 brouard 13294: numlinepar++;
13295: fputs(line,stdout);
13296: fputs(line,ficparo);
1.278 brouard 13297: fputs(line,ficres);
1.197 brouard 13298: fputs(line,ficlog);
13299: continue;
13300: }else
13301: break;
13302: }
13303: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13304: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13305: if (num_filled != 5) {
13306: printf("Should be 5 parameters\n");
1.283 brouard 13307: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13308: }
1.126 brouard 13309: numlinepar++;
1.197 brouard 13310: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13311: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13312: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13313: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13314: }
13315: /* Second parameter line */
13316: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13317: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13318: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13319: if (line[0] == '#') {
13320: numlinepar++;
1.283 brouard 13321: printf("%s",line);
13322: fprintf(ficres,"%s",line);
13323: fprintf(ficparo,"%s",line);
13324: fprintf(ficlog,"%s",line);
1.197 brouard 13325: continue;
13326: }else
13327: break;
13328: }
1.223 brouard 13329: 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", \
13330: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13331: if (num_filled != 11) {
13332: 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 13333: printf("but line=%s\n",line);
1.283 brouard 13334: 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");
13335: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13336: }
1.286 brouard 13337: if( lastpass > maxwav){
13338: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13339: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13340: fflush(ficlog);
13341: goto end;
13342: }
13343: 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 13344: 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 13345: 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 13346: 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 13347: }
1.203 brouard 13348: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13349: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13350: /* Third parameter line */
13351: while(fgets(line, MAXLINE, ficpar)) {
13352: /* If line starts with a # it is a comment */
13353: if (line[0] == '#') {
13354: numlinepar++;
1.283 brouard 13355: printf("%s",line);
13356: fprintf(ficres,"%s",line);
13357: fprintf(ficparo,"%s",line);
13358: fprintf(ficlog,"%s",line);
1.197 brouard 13359: continue;
13360: }else
13361: break;
13362: }
1.351 brouard 13363: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
13364: if (num_filled != 1){
13365: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13366: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13367: model[0]='\0';
13368: goto end;
13369: }else{
13370: trimbtab(linetmp,line); /* Trims multiple blanks in line */
13371: strcpy(line, linetmp);
13372: }
13373: }
13374: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 13375: if (num_filled != 1){
1.302 brouard 13376: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13377: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13378: model[0]='\0';
13379: goto end;
13380: }
13381: else{
13382: if (model[0]=='+'){
13383: for(i=1; i<=strlen(model);i++)
13384: modeltemp[i-1]=model[i];
1.201 brouard 13385: strcpy(model,modeltemp);
1.197 brouard 13386: }
13387: }
1.338 brouard 13388: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13389: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13390: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13391: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13392: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13393: }
13394: /* 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); */
13395: /* numlinepar=numlinepar+3; /\* In general *\/ */
13396: /* 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 13397: /* 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); */
13398: /* 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 13399: fflush(ficlog);
1.190 brouard 13400: /* if(model[0]=='#'|| model[0]== '\0'){ */
13401: if(model[0]=='#'){
1.279 brouard 13402: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13403: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13404: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13405: if(mle != -1){
1.279 brouard 13406: 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 13407: exit(1);
13408: }
13409: }
1.126 brouard 13410: while((c=getc(ficpar))=='#' && c!= EOF){
13411: ungetc(c,ficpar);
13412: fgets(line, MAXLINE, ficpar);
13413: numlinepar++;
1.195 brouard 13414: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13415: z[0]=line[1];
1.342 brouard 13416: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13417: debugILK=1;printf("DebugILK\n");
1.195 brouard 13418: }
13419: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13420: fputs(line, stdout);
13421: //puts(line);
1.126 brouard 13422: fputs(line,ficparo);
13423: fputs(line,ficlog);
13424: }
13425: ungetc(c,ficpar);
13426:
13427:
1.290 brouard 13428: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13429: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13430: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13431: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13432: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13433: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13434: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13435: v1+v2*age+v2*v3 makes cptcovn = 3
13436: */
13437: if (strlen(model)>1)
1.187 brouard 13438: 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 13439: else
1.187 brouard 13440: ncovmodel=2; /* Constant and age */
1.133 brouard 13441: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13442: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13443: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13444: 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);
13445: 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);
13446: fflush(stdout);
13447: fclose (ficlog);
13448: goto end;
13449: }
1.126 brouard 13450: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13451: delti=delti3[1][1];
13452: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13453: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13454: /* We could also provide initial parameters values giving by simple logistic regression
13455: * only one way, that is without matrix product. We will have nlstate maximizations */
13456: /* for(i=1;i<nlstate;i++){ */
13457: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13458: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13459: /* } */
1.126 brouard 13460: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13461: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13462: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13463: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13464: fclose (ficparo);
13465: fclose (ficlog);
13466: goto end;
13467: exit(0);
1.220 brouard 13468: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13469: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13470: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13471: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13472: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13473: matcov=matrix(1,npar,1,npar);
1.203 brouard 13474: hess=matrix(1,npar,1,npar);
1.220 brouard 13475: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13476: /* Read guessed parameters */
1.126 brouard 13477: /* Reads comments: lines beginning with '#' */
13478: while((c=getc(ficpar))=='#' && c!= EOF){
13479: ungetc(c,ficpar);
13480: fgets(line, MAXLINE, ficpar);
13481: numlinepar++;
1.141 brouard 13482: fputs(line,stdout);
1.126 brouard 13483: fputs(line,ficparo);
13484: fputs(line,ficlog);
13485: }
13486: ungetc(c,ficpar);
13487:
13488: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13489: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13490: for(i=1; i <=nlstate; i++){
1.234 brouard 13491: j=0;
1.126 brouard 13492: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13493: if(jj==i) continue;
13494: j++;
1.292 brouard 13495: while((c=getc(ficpar))=='#' && c!= EOF){
13496: ungetc(c,ficpar);
13497: fgets(line, MAXLINE, ficpar);
13498: numlinepar++;
13499: fputs(line,stdout);
13500: fputs(line,ficparo);
13501: fputs(line,ficlog);
13502: }
13503: ungetc(c,ficpar);
1.234 brouard 13504: fscanf(ficpar,"%1d%1d",&i1,&j1);
13505: if ((i1 != i) || (j1 != jj)){
13506: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13507: It might be a problem of design; if ncovcol and the model are correct\n \
13508: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13509: exit(1);
13510: }
13511: fprintf(ficparo,"%1d%1d",i1,j1);
13512: if(mle==1)
13513: printf("%1d%1d",i,jj);
13514: fprintf(ficlog,"%1d%1d",i,jj);
13515: for(k=1; k<=ncovmodel;k++){
13516: fscanf(ficpar," %lf",¶m[i][j][k]);
13517: if(mle==1){
13518: printf(" %lf",param[i][j][k]);
13519: fprintf(ficlog," %lf",param[i][j][k]);
13520: }
13521: else
13522: fprintf(ficlog," %lf",param[i][j][k]);
13523: fprintf(ficparo," %lf",param[i][j][k]);
13524: }
13525: fscanf(ficpar,"\n");
13526: numlinepar++;
13527: if(mle==1)
13528: printf("\n");
13529: fprintf(ficlog,"\n");
13530: fprintf(ficparo,"\n");
1.126 brouard 13531: }
13532: }
13533: fflush(ficlog);
1.234 brouard 13534:
1.251 brouard 13535: /* Reads parameters values */
1.126 brouard 13536: p=param[1][1];
1.251 brouard 13537: pstart=paramstart[1][1];
1.126 brouard 13538:
13539: /* Reads comments: lines beginning with '#' */
13540: while((c=getc(ficpar))=='#' && c!= EOF){
13541: ungetc(c,ficpar);
13542: fgets(line, MAXLINE, ficpar);
13543: numlinepar++;
1.141 brouard 13544: fputs(line,stdout);
1.126 brouard 13545: fputs(line,ficparo);
13546: fputs(line,ficlog);
13547: }
13548: ungetc(c,ficpar);
13549:
13550: for(i=1; i <=nlstate; i++){
13551: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13552: fscanf(ficpar,"%1d%1d",&i1,&j1);
13553: if ( (i1-i) * (j1-j) != 0){
13554: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13555: exit(1);
13556: }
13557: printf("%1d%1d",i,j);
13558: fprintf(ficparo,"%1d%1d",i1,j1);
13559: fprintf(ficlog,"%1d%1d",i1,j1);
13560: for(k=1; k<=ncovmodel;k++){
13561: fscanf(ficpar,"%le",&delti3[i][j][k]);
13562: printf(" %le",delti3[i][j][k]);
13563: fprintf(ficparo," %le",delti3[i][j][k]);
13564: fprintf(ficlog," %le",delti3[i][j][k]);
13565: }
13566: fscanf(ficpar,"\n");
13567: numlinepar++;
13568: printf("\n");
13569: fprintf(ficparo,"\n");
13570: fprintf(ficlog,"\n");
1.126 brouard 13571: }
13572: }
13573: fflush(ficlog);
1.234 brouard 13574:
1.145 brouard 13575: /* Reads covariance matrix */
1.126 brouard 13576: delti=delti3[1][1];
1.220 brouard 13577:
13578:
1.126 brouard 13579: /* 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 13580:
1.126 brouard 13581: /* Reads comments: lines beginning with '#' */
13582: while((c=getc(ficpar))=='#' && c!= EOF){
13583: ungetc(c,ficpar);
13584: fgets(line, MAXLINE, ficpar);
13585: numlinepar++;
1.141 brouard 13586: fputs(line,stdout);
1.126 brouard 13587: fputs(line,ficparo);
13588: fputs(line,ficlog);
13589: }
13590: ungetc(c,ficpar);
1.220 brouard 13591:
1.126 brouard 13592: matcov=matrix(1,npar,1,npar);
1.203 brouard 13593: hess=matrix(1,npar,1,npar);
1.131 brouard 13594: for(i=1; i <=npar; i++)
13595: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13596:
1.194 brouard 13597: /* Scans npar lines */
1.126 brouard 13598: for(i=1; i <=npar; i++){
1.226 brouard 13599: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13600: if(count != 3){
1.226 brouard 13601: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13602: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13603: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13604: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13605: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13606: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13607: exit(1);
1.220 brouard 13608: }else{
1.226 brouard 13609: if(mle==1)
13610: printf("%1d%1d%d",i1,j1,jk);
13611: }
13612: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13613: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13614: for(j=1; j <=i; j++){
1.226 brouard 13615: fscanf(ficpar," %le",&matcov[i][j]);
13616: if(mle==1){
13617: printf(" %.5le",matcov[i][j]);
13618: }
13619: fprintf(ficlog," %.5le",matcov[i][j]);
13620: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13621: }
13622: fscanf(ficpar,"\n");
13623: numlinepar++;
13624: if(mle==1)
1.220 brouard 13625: printf("\n");
1.126 brouard 13626: fprintf(ficlog,"\n");
13627: fprintf(ficparo,"\n");
13628: }
1.194 brouard 13629: /* End of read covariance matrix npar lines */
1.126 brouard 13630: for(i=1; i <=npar; i++)
13631: for(j=i+1;j<=npar;j++)
1.226 brouard 13632: matcov[i][j]=matcov[j][i];
1.126 brouard 13633:
13634: if(mle==1)
13635: printf("\n");
13636: fprintf(ficlog,"\n");
13637:
13638: fflush(ficlog);
13639:
13640: } /* End of mle != -3 */
1.218 brouard 13641:
1.186 brouard 13642: /* Main data
13643: */
1.290 brouard 13644: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13645: /* num=lvector(1,n); */
13646: /* moisnais=vector(1,n); */
13647: /* annais=vector(1,n); */
13648: /* moisdc=vector(1,n); */
13649: /* andc=vector(1,n); */
13650: /* weight=vector(1,n); */
13651: /* agedc=vector(1,n); */
13652: /* cod=ivector(1,n); */
13653: /* for(i=1;i<=n;i++){ */
13654: num=lvector(firstobs,lastobs);
13655: moisnais=vector(firstobs,lastobs);
13656: annais=vector(firstobs,lastobs);
13657: moisdc=vector(firstobs,lastobs);
13658: andc=vector(firstobs,lastobs);
13659: weight=vector(firstobs,lastobs);
13660: agedc=vector(firstobs,lastobs);
13661: cod=ivector(firstobs,lastobs);
13662: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13663: num[i]=0;
13664: moisnais[i]=0;
13665: annais[i]=0;
13666: moisdc[i]=0;
13667: andc[i]=0;
13668: agedc[i]=0;
13669: cod[i]=0;
13670: weight[i]=1.0; /* Equal weights, 1 by default */
13671: }
1.290 brouard 13672: mint=matrix(1,maxwav,firstobs,lastobs);
13673: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13674: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13675: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13676: tab=ivector(1,NCOVMAX);
1.144 brouard 13677: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13678: 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 13679:
1.136 brouard 13680: /* Reads data from file datafile */
13681: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13682: goto end;
13683:
13684: /* Calculation of the number of parameters from char model */
1.234 brouard 13685: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13686: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13687: k=3 V4 Tvar[k=3]= 4 (from V4)
13688: k=2 V1 Tvar[k=2]= 1 (from V1)
13689: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13690: */
13691:
13692: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13693: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13694: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13695: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13696: TvarsD=ivector(1,NCOVMAX); /* */
13697: TvarsQind=ivector(1,NCOVMAX); /* */
13698: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13699: TvarF=ivector(1,NCOVMAX); /* */
13700: TvarFind=ivector(1,NCOVMAX); /* */
13701: TvarV=ivector(1,NCOVMAX); /* */
13702: TvarVind=ivector(1,NCOVMAX); /* */
13703: TvarA=ivector(1,NCOVMAX); /* */
13704: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13705: TvarFD=ivector(1,NCOVMAX); /* */
13706: TvarFDind=ivector(1,NCOVMAX); /* */
13707: TvarFQ=ivector(1,NCOVMAX); /* */
13708: TvarFQind=ivector(1,NCOVMAX); /* */
13709: TvarVD=ivector(1,NCOVMAX); /* */
13710: TvarVDind=ivector(1,NCOVMAX); /* */
13711: TvarVQ=ivector(1,NCOVMAX); /* */
13712: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13713: TvarVV=ivector(1,NCOVMAX); /* */
13714: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 13715: TvarVVA=ivector(1,NCOVMAX); /* */
13716: TvarVVAind=ivector(1,NCOVMAX); /* */
13717: TvarAVVA=ivector(1,NCOVMAX); /* */
13718: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13719:
1.230 brouard 13720: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13721: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13722: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13723: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13724: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 13725: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
13726: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
13727:
1.137 brouard 13728: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13729: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13730: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13731: */
13732: /* For model-covariate k tells which data-covariate to use but
13733: because this model-covariate is a construction we invent a new column
13734: ncovcol + k1
13735: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13736: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13737: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13738: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13739: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13740: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13741: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13742: */
1.145 brouard 13743: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13744: 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 13745: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13746: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 13747: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 13748: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13749: 4 covariates (3 plus signs)
13750: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13751: */
13752: for(i=1;i<NCOVMAX;i++)
13753: Tage[i]=0;
1.230 brouard 13754: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13755: * individual dummy, fixed or varying:
13756: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13757: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13758: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13759: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13760: * Tmodelind[1]@9={9,0,3,2,}*/
13761: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13762: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13763: * individual quantitative, fixed or varying:
13764: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13765: * 3, 1, 0, 0, 0, 0, 0, 0},
13766: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 13767:
13768: /* Probably useless zeroes */
13769: for(i=1;i<NCOVMAX;i++){
13770: DummyV[i]=0;
13771: FixedV[i]=0;
13772: }
13773:
13774: for(i=1; i <=ncovcol;i++){
13775: DummyV[i]=0;
13776: FixedV[i]=0;
13777: }
13778: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
13779: DummyV[i]=1;
13780: FixedV[i]=0;
13781: }
13782: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
13783: DummyV[i]=0;
13784: FixedV[i]=1;
13785: }
13786: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
13787: DummyV[i]=1;
13788: FixedV[i]=1;
13789: }
13790: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
13791: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13792: 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]);
13793: }
13794:
13795:
13796:
1.186 brouard 13797: /* Main decodemodel */
13798:
1.187 brouard 13799:
1.223 brouard 13800: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13801: goto end;
13802:
1.137 brouard 13803: if((double)(lastobs-imx)/(double)imx > 1.10){
13804: nbwarn++;
13805: 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);
13806: 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);
13807: }
1.136 brouard 13808: /* if(mle==1){*/
1.137 brouard 13809: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13810: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13811: }
13812:
13813: /*-calculation of age at interview from date of interview and age at death -*/
13814: agev=matrix(1,maxwav,1,imx);
13815:
13816: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13817: goto end;
13818:
1.126 brouard 13819:
1.136 brouard 13820: agegomp=(int)agemin;
1.290 brouard 13821: free_vector(moisnais,firstobs,lastobs);
13822: free_vector(annais,firstobs,lastobs);
1.126 brouard 13823: /* free_matrix(mint,1,maxwav,1,n);
13824: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13825: /* free_vector(moisdc,1,n); */
13826: /* free_vector(andc,1,n); */
1.145 brouard 13827: /* */
13828:
1.126 brouard 13829: wav=ivector(1,imx);
1.214 brouard 13830: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13831: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13832: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13833: 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.*/
13834: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13835: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13836:
13837: /* Concatenates waves */
1.214 brouard 13838: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13839: Death is a valid wave (if date is known).
13840: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13841: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13842: and mw[mi+1][i]. dh depends on stepm.
13843: */
13844:
1.126 brouard 13845: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13846: /* Concatenates waves */
1.145 brouard 13847:
1.290 brouard 13848: free_vector(moisdc,firstobs,lastobs);
13849: free_vector(andc,firstobs,lastobs);
1.215 brouard 13850:
1.126 brouard 13851: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13852: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13853: ncodemax[1]=1;
1.145 brouard 13854: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13855: cptcoveff=0;
1.220 brouard 13856: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13857: 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 13858: }
13859:
13860: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13861: invalidvarcomb=ivector(0, ncovcombmax);
13862: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13863: invalidvarcomb[i]=0;
13864:
1.211 brouard 13865: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13866: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13867: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13868:
1.200 brouard 13869: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13870: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13871: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13872: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13873: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13874: * (currently 0 or 1) in the data.
13875: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13876: * corresponding modality (h,j).
13877: */
13878:
1.145 brouard 13879: h=0;
13880: /*if (cptcovn > 0) */
1.126 brouard 13881: m=pow(2,cptcoveff);
13882:
1.144 brouard 13883: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13884: * For k=4 covariates, h goes from 1 to m=2**k
13885: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13886: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13887: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13888: *______________________________ *______________________
13889: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13890: * 2 2 1 1 1 * 1 0 0 0 1
13891: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13892: * 4 2 2 1 1 * 3 0 0 1 1
13893: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13894: * 6 2 1 2 1 * 5 0 1 0 1
13895: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13896: * 8 2 2 2 1 * 7 0 1 1 1
13897: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13898: * 10 2 1 1 2 * 9 1 0 0 1
13899: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13900: * 12 2 2 1 2 * 11 1 0 1 1
13901: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13902: * 14 2 1 2 2 * 13 1 1 0 1
13903: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13904: * 16 2 2 2 2 * 15 1 1 1 1
13905: */
1.212 brouard 13906: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13907: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13908: * and the value of each covariate?
13909: * V1=1, V2=1, V3=2, V4=1 ?
13910: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13911: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13912: * In order to get the real value in the data, we use nbcode
13913: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13914: * We are keeping this crazy system in order to be able (in the future?)
13915: * to have more than 2 values (0 or 1) for a covariate.
13916: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13917: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13918: * bbbbbbbb
13919: * 76543210
13920: * h-1 00000101 (6-1=5)
1.219 brouard 13921: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13922: * &
13923: * 1 00000001 (1)
1.219 brouard 13924: * 00000000 = 1 & ((h-1) >> (k-1))
13925: * +1= 00000001 =1
1.211 brouard 13926: *
13927: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13928: * h' 1101 =2^3+2^2+0x2^1+2^0
13929: * >>k' 11
13930: * & 00000001
13931: * = 00000001
13932: * +1 = 00000010=2 = codtabm(14,3)
13933: * Reverse h=6 and m=16?
13934: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13935: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13936: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13937: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13938: * V3=decodtabm(14,3,2**4)=2
13939: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13940: *(h-1) >> (j-1) 0011 =13 >> 2
13941: * &1 000000001
13942: * = 000000001
13943: * +1= 000000010 =2
13944: * 2211
13945: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13946: * V3=2
1.220 brouard 13947: * codtabm and decodtabm are identical
1.211 brouard 13948: */
13949:
1.145 brouard 13950:
13951: free_ivector(Ndum,-1,NCOVMAX);
13952:
13953:
1.126 brouard 13954:
1.186 brouard 13955: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13956: strcpy(optionfilegnuplot,optionfilefiname);
13957: if(mle==-3)
1.201 brouard 13958: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13959: strcat(optionfilegnuplot,".gp");
13960:
13961: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13962: printf("Problem with file %s",optionfilegnuplot);
13963: }
13964: else{
1.204 brouard 13965: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13966: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13967: //fprintf(ficgp,"set missing 'NaNq'\n");
13968: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13969: }
13970: /* fclose(ficgp);*/
1.186 brouard 13971:
13972:
13973: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13974:
13975: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13976: if(mle==-3)
1.201 brouard 13977: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13978: strcat(optionfilehtm,".htm");
13979: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13980: printf("Problem with %s \n",optionfilehtm);
13981: exit(0);
1.126 brouard 13982: }
13983:
13984: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13985: strcat(optionfilehtmcov,"-cov.htm");
13986: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13987: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13988: }
13989: else{
13990: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13991: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13992: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13993: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13994: }
13995:
1.335 brouard 13996: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13997: <title>IMaCh %s</title></head>\n\
13998: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13999: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
14000: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
14001: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
14002: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
14003:
14004: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 14005: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 14006: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 14007: 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 14008: \n\
14009: <hr size=\"2\" color=\"#EC5E5E\">\
14010: <ul><li><h4>Parameter files</h4>\n\
14011: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
14012: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
14013: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
14014: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
14015: - Date and time at start: %s</ul>\n",\
1.335 brouard 14016: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 14017: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
14018: fileres,fileres,\
14019: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
14020: fflush(fichtm);
14021:
14022: strcpy(pathr,path);
14023: strcat(pathr,optionfilefiname);
1.184 brouard 14024: #ifdef WIN32
14025: _chdir(optionfilefiname); /* Move to directory named optionfile */
14026: #else
1.126 brouard 14027: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 14028: #endif
14029:
1.126 brouard 14030:
1.220 brouard 14031: /* Calculates basic frequencies. Computes observed prevalence at single age
14032: and for any valid combination of covariates
1.126 brouard 14033: and prints on file fileres'p'. */
1.251 brouard 14034: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 14035: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 14036:
14037: fprintf(fichtm,"\n");
1.286 brouard 14038: 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 14039: ftol, stepm);
14040: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
14041: ncurrv=1;
14042: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
14043: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
14044: ncurrv=i;
14045: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14046: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 14047: ncurrv=i;
14048: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14049: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 14050: ncurrv=i;
14051: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
14052: 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", \
14053: nlstate, ndeath, maxwav, mle, weightopt);
14054:
14055: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
14056: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
14057:
14058:
1.317 brouard 14059: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 14060: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
14061: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 14062: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 14063: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 14064: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14065: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14066: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14067: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 14068:
1.126 brouard 14069: /* For Powell, parameters are in a vector p[] starting at p[1]
14070: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
14071: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
14072:
14073: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 14074: /* For mortality only */
1.126 brouard 14075: if (mle==-3){
1.136 brouard 14076: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 14077: for(i=1;i<=NDIM;i++)
14078: for(j=1;j<=NDIM;j++)
14079: ximort[i][j]=0.;
1.186 brouard 14080: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 14081: cens=ivector(firstobs,lastobs);
14082: ageexmed=vector(firstobs,lastobs);
14083: agecens=vector(firstobs,lastobs);
14084: dcwave=ivector(firstobs,lastobs);
1.223 brouard 14085:
1.126 brouard 14086: for (i=1; i<=imx; i++){
14087: dcwave[i]=-1;
14088: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 14089: if (s[m][i]>nlstate) {
14090: dcwave[i]=m;
14091: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
14092: break;
14093: }
1.126 brouard 14094: }
1.226 brouard 14095:
1.126 brouard 14096: for (i=1; i<=imx; i++) {
14097: if (wav[i]>0){
1.226 brouard 14098: ageexmed[i]=agev[mw[1][i]][i];
14099: j=wav[i];
14100: agecens[i]=1.;
14101:
14102: if (ageexmed[i]> 1 && wav[i] > 0){
14103: agecens[i]=agev[mw[j][i]][i];
14104: cens[i]= 1;
14105: }else if (ageexmed[i]< 1)
14106: cens[i]= -1;
14107: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
14108: cens[i]=0 ;
1.126 brouard 14109: }
14110: else cens[i]=-1;
14111: }
14112:
14113: for (i=1;i<=NDIM;i++) {
14114: for (j=1;j<=NDIM;j++)
1.226 brouard 14115: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 14116: }
14117:
1.302 brouard 14118: p[1]=0.0268; p[NDIM]=0.083;
14119: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14120:
14121:
1.136 brouard 14122: #ifdef GSL
14123: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14124: #else
1.126 brouard 14125: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14126: #endif
1.201 brouard 14127: strcpy(filerespow,"POW-MORT_");
14128: strcat(filerespow,fileresu);
1.126 brouard 14129: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14130: printf("Problem with resultfile: %s\n", filerespow);
14131: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14132: }
1.136 brouard 14133: #ifdef GSL
14134: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14135: #else
1.126 brouard 14136: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14137: #endif
1.126 brouard 14138: /* for (i=1;i<=nlstate;i++)
14139: for(j=1;j<=nlstate+ndeath;j++)
14140: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14141: */
14142: fprintf(ficrespow,"\n");
1.136 brouard 14143: #ifdef GSL
14144: /* gsl starts here */
14145: T = gsl_multimin_fminimizer_nmsimplex;
14146: gsl_multimin_fminimizer *sfm = NULL;
14147: gsl_vector *ss, *x;
14148: gsl_multimin_function minex_func;
14149:
14150: /* Initial vertex size vector */
14151: ss = gsl_vector_alloc (NDIM);
14152:
14153: if (ss == NULL){
14154: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14155: }
14156: /* Set all step sizes to 1 */
14157: gsl_vector_set_all (ss, 0.001);
14158:
14159: /* Starting point */
1.126 brouard 14160:
1.136 brouard 14161: x = gsl_vector_alloc (NDIM);
14162:
14163: if (x == NULL){
14164: gsl_vector_free(ss);
14165: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14166: }
14167:
14168: /* Initialize method and iterate */
14169: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14170: /* gsl_vector_set(x, 0, 0.0268); */
14171: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14172: gsl_vector_set(x, 0, p[1]);
14173: gsl_vector_set(x, 1, p[2]);
14174:
14175: minex_func.f = &gompertz_f;
14176: minex_func.n = NDIM;
14177: minex_func.params = (void *)&p; /* ??? */
14178:
14179: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14180: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14181:
14182: printf("Iterations beginning .....\n\n");
14183: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14184:
14185: iteri=0;
14186: while (rval == GSL_CONTINUE){
14187: iteri++;
14188: status = gsl_multimin_fminimizer_iterate(sfm);
14189:
14190: if (status) printf("error: %s\n", gsl_strerror (status));
14191: fflush(0);
14192:
14193: if (status)
14194: break;
14195:
14196: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14197: ssval = gsl_multimin_fminimizer_size (sfm);
14198:
14199: if (rval == GSL_SUCCESS)
14200: printf ("converged to a local maximum at\n");
14201:
14202: printf("%5d ", iteri);
14203: for (it = 0; it < NDIM; it++){
14204: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14205: }
14206: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14207: }
14208:
14209: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14210:
14211: gsl_vector_free(x); /* initial values */
14212: gsl_vector_free(ss); /* inital step size */
14213: for (it=0; it<NDIM; it++){
14214: p[it+1]=gsl_vector_get(sfm->x,it);
14215: fprintf(ficrespow," %.12lf", p[it]);
14216: }
14217: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14218: #endif
14219: #ifdef POWELL
14220: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14221: #endif
1.126 brouard 14222: fclose(ficrespow);
14223:
1.203 brouard 14224: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14225:
14226: for(i=1; i <=NDIM; i++)
14227: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14228: matcov[i][j]=matcov[j][i];
1.126 brouard 14229:
14230: printf("\nCovariance matrix\n ");
1.203 brouard 14231: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14232: for(i=1; i <=NDIM; i++) {
14233: for(j=1;j<=NDIM;j++){
1.220 brouard 14234: printf("%f ",matcov[i][j]);
14235: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14236: }
1.203 brouard 14237: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14238: }
14239:
14240: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14241: for (i=1;i<=NDIM;i++) {
1.126 brouard 14242: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14243: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14244: }
1.302 brouard 14245: lsurv=vector(agegomp,AGESUP);
14246: lpop=vector(agegomp,AGESUP);
14247: tpop=vector(agegomp,AGESUP);
1.126 brouard 14248: lsurv[agegomp]=100000;
14249:
14250: for (k=agegomp;k<=AGESUP;k++) {
14251: agemortsup=k;
14252: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14253: }
14254:
14255: for (k=agegomp;k<agemortsup;k++)
14256: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14257:
14258: for (k=agegomp;k<agemortsup;k++){
14259: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14260: sumlpop=sumlpop+lpop[k];
14261: }
14262:
14263: tpop[agegomp]=sumlpop;
14264: for (k=agegomp;k<(agemortsup-3);k++){
14265: /* tpop[k+1]=2;*/
14266: tpop[k+1]=tpop[k]-lpop[k];
14267: }
14268:
14269:
14270: printf("\nAge lx qx dx Lx Tx e(x)\n");
14271: for (k=agegomp;k<(agemortsup-2);k++)
14272: 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]);
14273:
14274:
14275: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14276: ageminpar=50;
14277: agemaxpar=100;
1.194 brouard 14278: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14279: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14280: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14281: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
14282: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14283: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14284: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14285: }else{
14286: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14287: 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 14288: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14289: }
1.201 brouard 14290: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14291: stepm, weightopt,\
14292: model,imx,p,matcov,agemortsup);
14293:
1.302 brouard 14294: free_vector(lsurv,agegomp,AGESUP);
14295: free_vector(lpop,agegomp,AGESUP);
14296: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14297: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14298: free_ivector(dcwave,firstobs,lastobs);
14299: free_vector(agecens,firstobs,lastobs);
14300: free_vector(ageexmed,firstobs,lastobs);
14301: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14302: #ifdef GSL
1.136 brouard 14303: #endif
1.186 brouard 14304: } /* Endof if mle==-3 mortality only */
1.205 brouard 14305: /* Standard */
14306: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14307: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14308: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14309: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14310: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14311: for (k=1; k<=npar;k++)
14312: printf(" %d %8.5f",k,p[k]);
14313: printf("\n");
1.205 brouard 14314: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14315: /* mlikeli uses func not funcone */
1.247 brouard 14316: /* for(i=1;i<nlstate;i++){ */
14317: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14318: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14319: /* } */
1.205 brouard 14320: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14321: }
14322: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14323: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14324: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14325: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14326: }
14327: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14328: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14329: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14330: /* exit(0); */
1.126 brouard 14331: for (k=1; k<=npar;k++)
14332: printf(" %d %8.5f",k,p[k]);
14333: printf("\n");
14334:
14335: /*--------- results files --------------*/
1.283 brouard 14336: /* 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 14337:
14338:
14339: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14340: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14341: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14342:
14343: printf("#model= 1 + age ");
14344: fprintf(ficres,"#model= 1 + age ");
14345: fprintf(ficlog,"#model= 1 + age ");
14346: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14347: </ul>", model);
14348:
14349: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14350: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14351: if(nagesqr==1){
14352: printf(" + age*age ");
14353: fprintf(ficres," + age*age ");
14354: fprintf(ficlog," + age*age ");
14355: fprintf(fichtm, "<th>+ age*age</th>");
14356: }
14357: for(j=1;j <=ncovmodel-2;j++){
14358: if(Typevar[j]==0) {
14359: printf(" + V%d ",Tvar[j]);
14360: fprintf(ficres," + V%d ",Tvar[j]);
14361: fprintf(ficlog," + V%d ",Tvar[j]);
14362: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14363: }else if(Typevar[j]==1) {
14364: printf(" + V%d*age ",Tvar[j]);
14365: fprintf(ficres," + V%d*age ",Tvar[j]);
14366: fprintf(ficlog," + V%d*age ",Tvar[j]);
14367: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14368: }else if(Typevar[j]==2) {
14369: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14370: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14371: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14372: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14373: }else if(Typevar[j]==3) { /* TO VERIFY */
14374: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14375: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14376: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14377: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14378: }
14379: }
14380: printf("\n");
14381: fprintf(ficres,"\n");
14382: fprintf(ficlog,"\n");
14383: fprintf(fichtm, "</tr>");
14384: fprintf(fichtm, "\n");
14385:
14386:
1.126 brouard 14387: for(i=1,jk=1; i <=nlstate; i++){
14388: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14389: if (k != i) {
1.319 brouard 14390: fprintf(fichtm, "<tr>");
1.225 brouard 14391: printf("%d%d ",i,k);
14392: fprintf(ficlog,"%d%d ",i,k);
14393: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14394: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14395: for(j=1; j <=ncovmodel; j++){
14396: printf("%12.7f ",p[jk]);
14397: fprintf(ficlog,"%12.7f ",p[jk]);
14398: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14399: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14400: jk++;
14401: }
14402: printf("\n");
14403: fprintf(ficlog,"\n");
14404: fprintf(ficres,"\n");
1.319 brouard 14405: fprintf(fichtm, "</tr>\n");
1.225 brouard 14406: }
1.126 brouard 14407: }
14408: }
1.319 brouard 14409: /* fprintf(fichtm,"</tr>\n"); */
14410: fprintf(fichtm,"</table>\n");
14411: fprintf(fichtm, "\n");
14412:
1.203 brouard 14413: if(mle != 0){
14414: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14415: ftolhess=ftol; /* Usually correct */
1.203 brouard 14416: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14417: 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");
14418: 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 14419: 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 14420: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14421: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14422: if(nagesqr==1){
14423: printf(" + age*age ");
14424: fprintf(ficres," + age*age ");
14425: fprintf(ficlog," + age*age ");
14426: fprintf(fichtm, "<th>+ age*age</th>");
14427: }
14428: for(j=1;j <=ncovmodel-2;j++){
14429: if(Typevar[j]==0) {
14430: printf(" + V%d ",Tvar[j]);
14431: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14432: }else if(Typevar[j]==1) {
14433: printf(" + V%d*age ",Tvar[j]);
14434: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14435: }else if(Typevar[j]==2) {
14436: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14437: }else if(Typevar[j]==3) { /* TO VERIFY */
14438: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14439: }
14440: }
14441: fprintf(fichtm, "</tr>\n");
14442:
1.203 brouard 14443: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14444: for(k=1; k <=(nlstate+ndeath); k++){
14445: if (k != i) {
1.319 brouard 14446: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14447: printf("%d%d ",i,k);
14448: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14449: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14450: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14451: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14452: 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]));
14453: 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 14454: if(fabs(wald) > 1.96){
1.321 brouard 14455: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14456: }else{
14457: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14458: }
1.324 brouard 14459: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14460: 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 14461: jk++;
14462: }
14463: printf("\n");
14464: fprintf(ficlog,"\n");
1.319 brouard 14465: fprintf(fichtm, "</tr>\n");
1.225 brouard 14466: }
14467: }
1.193 brouard 14468: }
1.203 brouard 14469: } /* end of hesscov and Wald tests */
1.319 brouard 14470: fprintf(fichtm,"</table>\n");
1.225 brouard 14471:
1.203 brouard 14472: /* */
1.126 brouard 14473: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14474: printf("# Scales (for hessian or gradient estimation)\n");
14475: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14476: for(i=1,jk=1; i <=nlstate; i++){
14477: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14478: if (j!=i) {
14479: fprintf(ficres,"%1d%1d",i,j);
14480: printf("%1d%1d",i,j);
14481: fprintf(ficlog,"%1d%1d",i,j);
14482: for(k=1; k<=ncovmodel;k++){
14483: printf(" %.5e",delti[jk]);
14484: fprintf(ficlog," %.5e",delti[jk]);
14485: fprintf(ficres," %.5e",delti[jk]);
14486: jk++;
14487: }
14488: printf("\n");
14489: fprintf(ficlog,"\n");
14490: fprintf(ficres,"\n");
14491: }
1.126 brouard 14492: }
14493: }
14494:
14495: 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 14496: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14497: 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");
14498: 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");
14499: /* # 121 Var(a12)\n\ */
14500: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14501: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14502: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14503: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14504: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14505: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14506: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14507:
14508:
14509: /* Just to have a covariance matrix which will be more understandable
14510: even is we still don't want to manage dictionary of variables
14511: */
14512: for(itimes=1;itimes<=2;itimes++){
14513: jj=0;
14514: for(i=1; i <=nlstate; i++){
1.225 brouard 14515: for(j=1; j <=nlstate+ndeath; j++){
14516: if(j==i) continue;
14517: for(k=1; k<=ncovmodel;k++){
14518: jj++;
14519: ca[0]= k+'a'-1;ca[1]='\0';
14520: if(itimes==1){
14521: if(mle>=1)
14522: printf("#%1d%1d%d",i,j,k);
14523: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14524: fprintf(ficres,"#%1d%1d%d",i,j,k);
14525: }else{
14526: if(mle>=1)
14527: printf("%1d%1d%d",i,j,k);
14528: fprintf(ficlog,"%1d%1d%d",i,j,k);
14529: fprintf(ficres,"%1d%1d%d",i,j,k);
14530: }
14531: ll=0;
14532: for(li=1;li <=nlstate; li++){
14533: for(lj=1;lj <=nlstate+ndeath; lj++){
14534: if(lj==li) continue;
14535: for(lk=1;lk<=ncovmodel;lk++){
14536: ll++;
14537: if(ll<=jj){
14538: cb[0]= lk +'a'-1;cb[1]='\0';
14539: if(ll<jj){
14540: if(itimes==1){
14541: if(mle>=1)
14542: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14543: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14544: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14545: }else{
14546: if(mle>=1)
14547: printf(" %.5e",matcov[jj][ll]);
14548: fprintf(ficlog," %.5e",matcov[jj][ll]);
14549: fprintf(ficres," %.5e",matcov[jj][ll]);
14550: }
14551: }else{
14552: if(itimes==1){
14553: if(mle>=1)
14554: printf(" Var(%s%1d%1d)",ca,i,j);
14555: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14556: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14557: }else{
14558: if(mle>=1)
14559: printf(" %.7e",matcov[jj][ll]);
14560: fprintf(ficlog," %.7e",matcov[jj][ll]);
14561: fprintf(ficres," %.7e",matcov[jj][ll]);
14562: }
14563: }
14564: }
14565: } /* end lk */
14566: } /* end lj */
14567: } /* end li */
14568: if(mle>=1)
14569: printf("\n");
14570: fprintf(ficlog,"\n");
14571: fprintf(ficres,"\n");
14572: numlinepar++;
14573: } /* end k*/
14574: } /*end j */
1.126 brouard 14575: } /* end i */
14576: } /* end itimes */
14577:
14578: fflush(ficlog);
14579: fflush(ficres);
1.225 brouard 14580: while(fgets(line, MAXLINE, ficpar)) {
14581: /* If line starts with a # it is a comment */
14582: if (line[0] == '#') {
14583: numlinepar++;
14584: fputs(line,stdout);
14585: fputs(line,ficparo);
14586: fputs(line,ficlog);
1.299 brouard 14587: fputs(line,ficres);
1.225 brouard 14588: continue;
14589: }else
14590: break;
14591: }
14592:
1.209 brouard 14593: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14594: /* ungetc(c,ficpar); */
14595: /* fgets(line, MAXLINE, ficpar); */
14596: /* fputs(line,stdout); */
14597: /* fputs(line,ficparo); */
14598: /* } */
14599: /* ungetc(c,ficpar); */
1.126 brouard 14600:
14601: estepm=0;
1.209 brouard 14602: 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 14603:
14604: if (num_filled != 6) {
14605: 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);
14606: 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);
14607: goto end;
14608: }
14609: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14610: }
14611: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14612: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14613:
1.209 brouard 14614: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14615: if (estepm==0 || estepm < stepm) estepm=stepm;
14616: if (fage <= 2) {
14617: bage = ageminpar;
14618: fage = agemaxpar;
14619: }
14620:
14621: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14622: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14623: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14624:
1.186 brouard 14625: /* Other stuffs, more or less useful */
1.254 brouard 14626: while(fgets(line, MAXLINE, ficpar)) {
14627: /* If line starts with a # it is a comment */
14628: if (line[0] == '#') {
14629: numlinepar++;
14630: fputs(line,stdout);
14631: fputs(line,ficparo);
14632: fputs(line,ficlog);
1.299 brouard 14633: fputs(line,ficres);
1.254 brouard 14634: continue;
14635: }else
14636: break;
14637: }
14638:
14639: 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){
14640:
14641: if (num_filled != 7) {
14642: 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);
14643: 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);
14644: goto end;
14645: }
14646: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14647: 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);
14648: 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);
14649: 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 14650: }
1.254 brouard 14651:
14652: while(fgets(line, MAXLINE, ficpar)) {
14653: /* If line starts with a # it is a comment */
14654: if (line[0] == '#') {
14655: numlinepar++;
14656: fputs(line,stdout);
14657: fputs(line,ficparo);
14658: fputs(line,ficlog);
1.299 brouard 14659: fputs(line,ficres);
1.254 brouard 14660: continue;
14661: }else
14662: break;
1.126 brouard 14663: }
14664:
14665:
14666: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14667: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14668:
1.254 brouard 14669: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14670: if (num_filled != 1) {
14671: 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);
14672: 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);
14673: goto end;
14674: }
14675: printf("pop_based=%d\n",popbased);
14676: fprintf(ficlog,"pop_based=%d\n",popbased);
14677: fprintf(ficparo,"pop_based=%d\n",popbased);
14678: fprintf(ficres,"pop_based=%d\n",popbased);
14679: }
14680:
1.258 brouard 14681: /* Results */
1.332 brouard 14682: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14683: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14684: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14685: endishere=0;
1.258 brouard 14686: nresult=0;
1.308 brouard 14687: parameterline=0;
1.258 brouard 14688: do{
14689: if(!fgets(line, MAXLINE, ficpar)){
14690: endishere=1;
1.308 brouard 14691: parameterline=15;
1.258 brouard 14692: }else if (line[0] == '#') {
14693: /* If line starts with a # it is a comment */
1.254 brouard 14694: numlinepar++;
14695: fputs(line,stdout);
14696: fputs(line,ficparo);
14697: fputs(line,ficlog);
1.299 brouard 14698: fputs(line,ficres);
1.254 brouard 14699: continue;
1.258 brouard 14700: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14701: parameterline=11;
1.296 brouard 14702: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14703: parameterline=12;
1.307 brouard 14704: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14705: parameterline=13;
1.307 brouard 14706: }
1.258 brouard 14707: else{
14708: parameterline=14;
1.254 brouard 14709: }
1.308 brouard 14710: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14711: case 11:
1.296 brouard 14712: 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)){
14713: 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 14714: 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);
14715: 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);
14716: 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);
14717: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14718: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14719: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14720: prvforecast = 1;
14721: }
14722: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14723: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14724: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14725: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14726: prvforecast = 2;
14727: }
14728: else {
14729: 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);
14730: 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);
14731: goto end;
1.258 brouard 14732: }
1.254 brouard 14733: break;
1.258 brouard 14734: case 12:
1.296 brouard 14735: 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)){
14736: 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);
14737: 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);
14738: 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);
14739: 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);
14740: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14741: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14742: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14743: prvbackcast = 1;
14744: }
14745: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14746: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14747: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14748: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14749: prvbackcast = 2;
14750: }
14751: else {
14752: 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);
14753: 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);
14754: goto end;
1.258 brouard 14755: }
1.230 brouard 14756: break;
1.258 brouard 14757: case 13:
1.332 brouard 14758: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14759: nresult++; /* Sum of resultlines */
1.342 brouard 14760: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14761: /* removefirstspace(&resultlineori); */
14762:
14763: if(strstr(resultlineori,"v") !=0){
14764: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14765: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14766: return 1;
14767: }
14768: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14769: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14770: if(nresult > MAXRESULTLINESPONE-1){
14771: 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);
14772: 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 14773: goto end;
14774: }
1.332 brouard 14775:
1.310 brouard 14776: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14777: fprintf(ficparo,"result: %s\n",resultline);
14778: fprintf(ficres,"result: %s\n",resultline);
14779: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14780: } else
14781: goto end;
1.307 brouard 14782: break;
14783: case 14:
14784: printf("Error: Unknown command '%s'\n",line);
14785: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14786: if(line[0] == ' ' || line[0] == '\n'){
14787: printf("It should not be an empty line '%s'\n",line);
14788: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14789: }
1.307 brouard 14790: if(ncovmodel >=2 && nresult==0 ){
14791: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14792: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14793: }
1.307 brouard 14794: /* goto end; */
14795: break;
1.308 brouard 14796: case 15:
14797: printf("End of resultlines.\n");
14798: fprintf(ficlog,"End of resultlines.\n");
14799: break;
14800: default: /* parameterline =0 */
1.307 brouard 14801: nresult=1;
14802: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14803: } /* End switch parameterline */
14804: }while(endishere==0); /* End do */
1.126 brouard 14805:
1.230 brouard 14806: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14807: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14808:
14809: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14810: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14811: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14812: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14813: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14814: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14815: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14816: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14817: }else{
1.270 brouard 14818: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14819: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14820: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14821: if(prvforecast==1){
14822: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14823: jprojd=jproj1;
14824: mprojd=mproj1;
14825: anprojd=anproj1;
14826: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14827: jprojf=jproj2;
14828: mprojf=mproj2;
14829: anprojf=anproj2;
14830: } else if(prvforecast == 2){
14831: dateprojd=dateintmean;
14832: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14833: dateprojf=dateintmean+yrfproj;
14834: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14835: }
14836: if(prvbackcast==1){
14837: datebackd=(jback1+12*mback1+365*anback1)/365;
14838: jbackd=jback1;
14839: mbackd=mback1;
14840: anbackd=anback1;
14841: datebackf=(jback2+12*mback2+365*anback2)/365;
14842: jbackf=jback2;
14843: mbackf=mback2;
14844: anbackf=anback2;
14845: } else if(prvbackcast == 2){
14846: datebackd=dateintmean;
14847: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14848: datebackf=dateintmean-yrbproj;
14849: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14850: }
14851:
1.350 brouard 14852: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 14853: }
14854: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14855: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14856: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14857:
1.225 brouard 14858: /*------------ free_vector -------------*/
14859: /* chdir(path); */
1.220 brouard 14860:
1.215 brouard 14861: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14862: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14863: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14864: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14865: free_lvector(num,firstobs,lastobs);
14866: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14867: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14868: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14869: fclose(ficparo);
14870: fclose(ficres);
1.220 brouard 14871:
14872:
1.186 brouard 14873: /* Other results (useful)*/
1.220 brouard 14874:
14875:
1.126 brouard 14876: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14877: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14878: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14879: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14880: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14881: fclose(ficrespl);
14882:
14883: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14884: /*#include "hpijx.h"*/
1.332 brouard 14885: /** 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?*/
14886: /* calls hpxij with combination k */
1.180 brouard 14887: hPijx(p, bage, fage);
1.145 brouard 14888: fclose(ficrespij);
1.227 brouard 14889:
1.220 brouard 14890: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14891: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14892: k=1;
1.126 brouard 14893: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14894:
1.269 brouard 14895: /* Prevalence for each covariate combination in probs[age][status][cov] */
14896: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14897: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14898: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14899: for(k=1;k<=ncovcombmax;k++)
14900: probs[i][j][k]=0.;
1.269 brouard 14901: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14902: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14903: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14904: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14905: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14906: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14907: for(k=1;k<=ncovcombmax;k++)
14908: mobaverages[i][j][k]=0.;
1.219 brouard 14909: mobaverage=mobaverages;
14910: if (mobilav!=0) {
1.235 brouard 14911: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14912: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14913: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14914: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14915: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14916: }
1.269 brouard 14917: } else if (mobilavproj !=0) {
1.235 brouard 14918: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14919: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14920: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14921: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14922: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14923: }
1.269 brouard 14924: }else{
14925: printf("Internal error moving average\n");
14926: fflush(stdout);
14927: exit(1);
1.219 brouard 14928: }
14929: }/* end if moving average */
1.227 brouard 14930:
1.126 brouard 14931: /*---------- Forecasting ------------------*/
1.296 brouard 14932: if(prevfcast==1){
14933: /* /\* if(stepm ==1){*\/ */
14934: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14935: /*This done previously after freqsummary.*/
14936: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14937: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14938:
14939: /* } else if (prvforecast==2){ */
14940: /* /\* if(stepm ==1){*\/ */
14941: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14942: /* } */
14943: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14944: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14945: }
1.269 brouard 14946:
1.296 brouard 14947: /* Prevbcasting */
14948: if(prevbcast==1){
1.219 brouard 14949: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14950: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14951: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14952:
14953: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14954:
14955: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14956:
1.219 brouard 14957: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14958: fclose(ficresplb);
14959:
1.222 brouard 14960: hBijx(p, bage, fage, mobaverage);
14961: fclose(ficrespijb);
1.219 brouard 14962:
1.296 brouard 14963: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14964: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14965: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14966: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14967: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14968: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14969:
14970:
1.269 brouard 14971: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14972:
14973:
1.269 brouard 14974: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14975: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14976: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14977: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14978: } /* end Prevbcasting */
1.268 brouard 14979:
1.186 brouard 14980:
14981: /* ------ Other prevalence ratios------------ */
1.126 brouard 14982:
1.215 brouard 14983: free_ivector(wav,1,imx);
14984: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14985: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14986: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14987:
14988:
1.127 brouard 14989: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14990:
1.201 brouard 14991: strcpy(filerese,"E_");
14992: strcat(filerese,fileresu);
1.126 brouard 14993: if((ficreseij=fopen(filerese,"w"))==NULL) {
14994: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14995: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14996: }
1.208 brouard 14997: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14998: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14999:
15000: pstamp(ficreseij);
1.219 brouard 15001:
1.351 brouard 15002: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
15003: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 15004:
1.351 brouard 15005: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
15006: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
15007: /* if(i1 != 1 && TKresult[nres]!= k) */
15008: /* continue; */
1.219 brouard 15009: fprintf(ficreseij,"\n#****** ");
1.235 brouard 15010: printf("\n#****** ");
1.351 brouard 15011: for(j=1;j<=cptcovs;j++){
15012: /* for(j=1;j<=cptcoveff;j++) { */
15013: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15014: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15015: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15016: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 15017: }
15018: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 15019: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
15020: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 15021: }
15022: fprintf(ficreseij,"******\n");
1.235 brouard 15023: printf("******\n");
1.219 brouard 15024:
15025: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15026: oldm=oldms;savm=savms;
1.330 brouard 15027: /* 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 15028: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 15029:
1.219 brouard 15030: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 15031: }
15032: fclose(ficreseij);
1.208 brouard 15033: printf("done evsij\n");fflush(stdout);
15034: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 15035:
1.218 brouard 15036:
1.227 brouard 15037: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 15038: /* Should be moved in a function */
1.201 brouard 15039: strcpy(filerest,"T_");
15040: strcat(filerest,fileresu);
1.127 brouard 15041: if((ficrest=fopen(filerest,"w"))==NULL) {
15042: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
15043: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
15044: }
1.208 brouard 15045: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
15046: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 15047: strcpy(fileresstde,"STDE_");
15048: strcat(fileresstde,fileresu);
1.126 brouard 15049: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 15050: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
15051: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 15052: }
1.227 brouard 15053: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
15054: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 15055:
1.201 brouard 15056: strcpy(filerescve,"CVE_");
15057: strcat(filerescve,fileresu);
1.126 brouard 15058: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 15059: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
15060: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 15061: }
1.227 brouard 15062: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
15063: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 15064:
1.201 brouard 15065: strcpy(fileresv,"V_");
15066: strcat(fileresv,fileresu);
1.126 brouard 15067: if((ficresvij=fopen(fileresv,"w"))==NULL) {
15068: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
15069: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
15070: }
1.227 brouard 15071: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
15072: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 15073:
1.235 brouard 15074: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
15075: if (cptcovn < 1){i1=1;}
15076:
1.334 brouard 15077: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
15078: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
15079: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
15080: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
15081: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
15082: /* */
15083: 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 15084: continue;
1.350 brouard 15085: printf("\n# model %s \n#****** Result for:", model); /* HERE model is empty */
1.321 brouard 15086: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
15087: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 15088: /* It might not be a good idea to mix dummies and quantitative */
15089: /* 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 *\/ */
15090: 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 */
15091: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
15092: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
15093: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
15094: * (V5 is quanti) V4 and V3 are dummies
15095: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
15096: * l=1 l=2
15097: * k=1 1 1 0 0
15098: * k=2 2 1 1 0
15099: * k=3 [1] [2] 0 1
15100: * k=4 2 2 1 1
15101: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
15102: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
15103: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
15104: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
15105: */
15106: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
15107: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
15108: /* We give up with the combinations!! */
1.342 brouard 15109: /* if(debugILK) */
15110: /* 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 15111:
15112: 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 15113: /* 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] */
15114: 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 */
15115: 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 */
15116: 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 15117: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15118: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15119: }else{
15120: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15121: }
15122: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15123: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15124: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15125: /* For each selected (single) quantitative value */
1.337 brouard 15126: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15127: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15128: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15129: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15130: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15131: }else{
15132: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15133: }
15134: }else{
15135: 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 */
15136: 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 */
15137: exit(1);
15138: }
1.335 brouard 15139: } /* End loop for each variable in the resultline */
1.334 brouard 15140: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15141: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15142: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15143: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15144: /* } */
1.208 brouard 15145: fprintf(ficrest,"******\n");
1.227 brouard 15146: fprintf(ficlog,"******\n");
15147: printf("******\n");
1.208 brouard 15148:
15149: fprintf(ficresstdeij,"\n#****** ");
15150: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15151: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15152: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15153: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15154: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15155: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15156: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15157: }
15158: 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 15159: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15160: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15161: }
1.208 brouard 15162: fprintf(ficresstdeij,"******\n");
15163: fprintf(ficrescveij,"******\n");
15164:
15165: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15166: /* pstamp(ficresvij); */
1.225 brouard 15167: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15168: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15169: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15170: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15171: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15172: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15173: }
1.208 brouard 15174: fprintf(ficresvij,"******\n");
15175:
15176: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15177: oldm=oldms;savm=savms;
1.235 brouard 15178: printf(" cvevsij ");
15179: fprintf(ficlog, " cvevsij ");
15180: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15181: printf(" end cvevsij \n ");
15182: fprintf(ficlog, " end cvevsij \n ");
15183:
15184: /*
15185: */
15186: /* goto endfree; */
15187:
15188: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15189: pstamp(ficrest);
15190:
1.269 brouard 15191: epj=vector(1,nlstate+1);
1.208 brouard 15192: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15193: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15194: cptcod= 0; /* To be deleted */
15195: printf("varevsij vpopbased=%d \n",vpopbased);
15196: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15197: 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 */
1.227 brouard 15198: fprintf(ficrest,"# Total life expectancy with std error and decomposition into time to be expected in each health state\n# (weighted average of eij where weights are ");
15199: if(vpopbased==1)
15200: 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);
15201: else
1.288 brouard 15202: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15203: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15204: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15205: fprintf(ficrest,"\n");
15206: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15207: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15208: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15209: for(age=bage; age <=fage ;age++){
1.235 brouard 15210: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15211: if (vpopbased==1) {
15212: if(mobilav ==0){
15213: for(i=1; i<=nlstate;i++)
15214: prlim[i][i]=probs[(int)age][i][k];
15215: }else{ /* mobilav */
15216: for(i=1; i<=nlstate;i++)
15217: prlim[i][i]=mobaverage[(int)age][i][k];
15218: }
15219: }
1.219 brouard 15220:
1.227 brouard 15221: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15222: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15223: /* printf(" age %4.0f ",age); */
15224: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15225: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15226: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15227: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15228: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15229: }
15230: epj[nlstate+1] +=epj[j];
15231: }
15232: /* printf(" age %4.0f \n",age); */
1.219 brouard 15233:
1.227 brouard 15234: for(i=1, vepp=0.;i <=nlstate;i++)
15235: for(j=1;j <=nlstate;j++)
15236: vepp += vareij[i][j][(int)age];
15237: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15238: for(j=1;j <=nlstate;j++){
15239: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15240: }
15241: fprintf(ficrest,"\n");
15242: }
1.208 brouard 15243: } /* End vpopbased */
1.269 brouard 15244: free_vector(epj,1,nlstate+1);
1.208 brouard 15245: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15246: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15247: printf("done selection\n");fflush(stdout);
15248: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15249:
1.335 brouard 15250: } /* End k selection or end covariate selection for nres */
1.227 brouard 15251:
15252: printf("done State-specific expectancies\n");fflush(stdout);
15253: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15254:
1.335 brouard 15255: /* variance-covariance of forward period prevalence */
1.269 brouard 15256: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15257:
1.227 brouard 15258:
1.290 brouard 15259: free_vector(weight,firstobs,lastobs);
1.351 brouard 15260: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 15261: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15262: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15263: free_matrix(anint,1,maxwav,firstobs,lastobs);
15264: free_matrix(mint,1,maxwav,firstobs,lastobs);
15265: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15266: free_ivector(tab,1,NCOVMAX);
15267: fclose(ficresstdeij);
15268: fclose(ficrescveij);
15269: fclose(ficresvij);
15270: fclose(ficrest);
15271: fclose(ficpar);
15272:
15273:
1.126 brouard 15274: /*---------- End : free ----------------*/
1.219 brouard 15275: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15276: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15277: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15278: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15279: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15280: } /* mle==-3 arrives here for freeing */
1.227 brouard 15281: /* endfree:*/
15282: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15283: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15284: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15285: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15286: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15287: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15288: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15289: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15290: free_matrix(matcov,1,npar,1,npar);
15291: free_matrix(hess,1,npar,1,npar);
15292: /*free_vector(delti,1,npar);*/
15293: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15294: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15295: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15296: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15297:
15298: free_ivector(ncodemax,1,NCOVMAX);
15299: free_ivector(ncodemaxwundef,1,NCOVMAX);
15300: free_ivector(Dummy,-1,NCOVMAX);
15301: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 15302: free_ivector(DummyV,-1,NCOVMAX);
15303: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15304: free_ivector(Typevar,-1,NCOVMAX);
15305: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15306: free_ivector(TvarsQ,1,NCOVMAX);
15307: free_ivector(TvarsQind,1,NCOVMAX);
15308: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15309: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15310: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15311: free_ivector(TvarFD,1,NCOVMAX);
15312: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15313: free_ivector(TvarF,1,NCOVMAX);
15314: free_ivector(TvarFind,1,NCOVMAX);
15315: free_ivector(TvarV,1,NCOVMAX);
15316: free_ivector(TvarVind,1,NCOVMAX);
15317: free_ivector(TvarA,1,NCOVMAX);
15318: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15319: free_ivector(TvarFQ,1,NCOVMAX);
15320: free_ivector(TvarFQind,1,NCOVMAX);
15321: free_ivector(TvarVD,1,NCOVMAX);
15322: free_ivector(TvarVDind,1,NCOVMAX);
15323: free_ivector(TvarVQ,1,NCOVMAX);
15324: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 15325: free_ivector(TvarAVVA,1,NCOVMAX);
15326: free_ivector(TvarAVVAind,1,NCOVMAX);
15327: free_ivector(TvarVVA,1,NCOVMAX);
15328: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15329: free_ivector(TvarVV,1,NCOVMAX);
15330: free_ivector(TvarVVind,1,NCOVMAX);
15331:
1.230 brouard 15332: free_ivector(Tvarsel,1,NCOVMAX);
15333: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15334: free_ivector(Tposprod,1,NCOVMAX);
15335: free_ivector(Tprod,1,NCOVMAX);
15336: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15337: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15338: free_ivector(Tage,1,NCOVMAX);
15339: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15340: free_ivector(TmodelInvind,1,NCOVMAX);
15341: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15342:
15343: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15344:
1.227 brouard 15345: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15346: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15347: fflush(fichtm);
15348: fflush(ficgp);
15349:
1.227 brouard 15350:
1.126 brouard 15351: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15352: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15353: 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 15354: }else{
15355: printf("End of Imach\n");
15356: fprintf(ficlog,"End of Imach\n");
15357: }
15358: printf("See log file on %s\n",filelog);
15359: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15360: /*(void) gettimeofday(&end_time,&tzp);*/
15361: rend_time = time(NULL);
15362: end_time = *localtime(&rend_time);
15363: /* tml = *localtime(&end_time.tm_sec); */
15364: strcpy(strtend,asctime(&end_time));
1.126 brouard 15365: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15366: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15367: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15368:
1.157 brouard 15369: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15370: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15371: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15372: /* printf("Total time was %d uSec.\n", total_usecs);*/
15373: /* if(fileappend(fichtm,optionfilehtm)){ */
15374: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15375: fclose(fichtm);
15376: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15377: fclose(fichtmcov);
15378: fclose(ficgp);
15379: fclose(ficlog);
15380: /*------ End -----------*/
1.227 brouard 15381:
1.281 brouard 15382:
15383: /* Executes gnuplot */
1.227 brouard 15384:
15385: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15386: #ifdef WIN32
1.227 brouard 15387: if (_chdir(pathcd) != 0)
15388: printf("Can't move to directory %s!\n",path);
15389: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15390: #else
1.227 brouard 15391: if(chdir(pathcd) != 0)
15392: printf("Can't move to directory %s!\n", path);
15393: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15394: #endif
1.126 brouard 15395: printf("Current directory %s!\n",pathcd);
15396: /*strcat(plotcmd,CHARSEPARATOR);*/
15397: sprintf(plotcmd,"gnuplot");
1.157 brouard 15398: #ifdef _WIN32
1.126 brouard 15399: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15400: #endif
15401: if(!stat(plotcmd,&info)){
1.158 brouard 15402: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15403: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15404: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15405: }else
15406: strcpy(pplotcmd,plotcmd);
1.157 brouard 15407: #ifdef __unix
1.126 brouard 15408: strcpy(plotcmd,GNUPLOTPROGRAM);
15409: if(!stat(plotcmd,&info)){
1.158 brouard 15410: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15411: }else
15412: strcpy(pplotcmd,plotcmd);
15413: #endif
15414: }else
15415: strcpy(pplotcmd,plotcmd);
15416:
15417: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15418: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15419: strcpy(pplotcmd,plotcmd);
1.227 brouard 15420:
1.126 brouard 15421: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15422: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15423: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15424: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15425: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15426: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15427: strcpy(plotcmd,pplotcmd);
15428: }
1.126 brouard 15429: }
1.158 brouard 15430: printf(" Successful, please wait...");
1.126 brouard 15431: while (z[0] != 'q') {
15432: /* chdir(path); */
1.154 brouard 15433: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15434: scanf("%s",z);
15435: /* if (z[0] == 'c') system("./imach"); */
15436: if (z[0] == 'e') {
1.158 brouard 15437: #ifdef __APPLE__
1.152 brouard 15438: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15439: #elif __linux
15440: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15441: #else
1.152 brouard 15442: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15443: #endif
15444: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15445: system(pplotcmd);
1.126 brouard 15446: }
15447: else if (z[0] == 'g') system(plotcmd);
15448: else if (z[0] == 'q') exit(0);
15449: }
1.227 brouard 15450: end:
1.126 brouard 15451: while (z[0] != 'q') {
1.195 brouard 15452: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15453: scanf("%s",z);
15454: }
1.283 brouard 15455: printf("End\n");
1.282 brouard 15456: exit(0);
1.126 brouard 15457: }
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