Annotation of imach/src/imach.c, revision 1.353
1.353 ! brouard 1: /* $Id: imach.c,v 1.352 2023/04/29 10:46:21 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.353 ! brouard 4: Revision 1.352 2023/04/29 10:46:21 brouard
! 5: *** empty log message ***
! 6:
1.352 brouard 7: Revision 1.351 2023/04/29 10:43:47 brouard
8: Summary: 099r45
9:
1.351 brouard 10: Revision 1.350 2023/04/24 11:38:06 brouard
11: *** empty log message ***
12:
1.350 brouard 13: Revision 1.349 2023/01/31 09:19:37 brouard
14: Summary: Improvements in models with age*Vn*Vm
15:
1.348 brouard 16: Revision 1.347 2022/09/18 14:36:44 brouard
17: Summary: version 0.99r42
18:
1.347 brouard 19: Revision 1.346 2022/09/16 13:52:36 brouard
20: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
21:
1.346 brouard 22: Revision 1.345 2022/09/16 13:40:11 brouard
23: Summary: Version 0.99r41
24:
25: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
26:
1.345 brouard 27: Revision 1.344 2022/09/14 19:33:30 brouard
28: Summary: version 0.99r40
29:
30: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
31:
1.344 brouard 32: Revision 1.343 2022/09/14 14:22:16 brouard
33: Summary: version 0.99r39
34:
35: * imach.c (Module): Version 0.99r39 with colored dummy covariates
36: (fixed or time varying), using new last columns of
37: ILK_parameter.txt file.
38:
1.343 brouard 39: Revision 1.342 2022/09/11 19:54:09 brouard
40: Summary: 0.99r38
41:
42: * imach.c (Module): Adding timevarying products of any kinds,
43: should work before shifting cotvar from ncovcol+nqv columns in
44: order to have a correspondance between the column of cotvar and
45: the id of column.
46: (Module): Some cleaning and adding covariates in ILK.txt
47:
1.342 brouard 48: Revision 1.341 2022/09/11 07:58:42 brouard
49: Summary: Version 0.99r38
50:
51: After adding change in cotvar.
52:
1.341 brouard 53: Revision 1.340 2022/09/11 07:53:11 brouard
54: Summary: Version imach 0.99r37
55:
56: * imach.c (Module): Adding timevarying products of any kinds,
57: should work before shifting cotvar from ncovcol+nqv columns in
58: order to have a correspondance between the column of cotvar and
59: the id of column.
60:
1.340 brouard 61: Revision 1.339 2022/09/09 17:55:22 brouard
62: Summary: version 0.99r37
63:
64: * imach.c (Module): Many improvements for fixing products of fixed
65: timevarying as well as fixed * fixed, and test with quantitative
66: covariate.
67:
1.339 brouard 68: Revision 1.338 2022/09/04 17:40:33 brouard
69: Summary: 0.99r36
70:
71: * imach.c (Module): Now the easy runs i.e. without result or
72: model=1+age only did not work. The defautl combination should be 1
73: and not 0 because everything hasn't been tranformed yet.
74:
1.338 brouard 75: Revision 1.337 2022/09/02 14:26:02 brouard
76: Summary: version 0.99r35
77:
78: * src/imach.c: Version 0.99r35 because it outputs same results with
79: 1+age+V1+V1*age for females and 1+age for females only
80: (education=1 noweight)
81:
1.337 brouard 82: Revision 1.336 2022/08/31 09:52:36 brouard
83: *** empty log message ***
84:
1.336 brouard 85: Revision 1.335 2022/08/31 08:23:16 brouard
86: Summary: improvements...
87:
1.335 brouard 88: Revision 1.334 2022/08/25 09:08:41 brouard
89: Summary: In progress for quantitative
90:
1.334 brouard 91: Revision 1.333 2022/08/21 09:10:30 brouard
92: * src/imach.c (Module): Version 0.99r33 A lot of changes in
93: reassigning covariates: my first idea was that people will always
94: use the first covariate V1 into the model but in fact they are
95: producing data with many covariates and can use an equation model
96: with some of the covariate; it means that in a model V2+V3 instead
97: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
98: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
99: the equation model is restricted to two variables only (V2, V3)
100: and the combination for V2 should be codtabm(k,1) instead of
101: (codtabm(k,2), and the code should be
102: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
103: made. All of these should be simplified once a day like we did in
104: hpxij() for example by using precov[nres] which is computed in
105: decoderesult for each nres of each resultline. Loop should be done
106: on the equation model globally by distinguishing only product with
107: age (which are changing with age) and no more on type of
108: covariates, single dummies, single covariates.
109:
1.333 brouard 110: Revision 1.332 2022/08/21 09:06:25 brouard
111: Summary: Version 0.99r33
112:
113: * src/imach.c (Module): Version 0.99r33 A lot of changes in
114: reassigning covariates: my first idea was that people will always
115: use the first covariate V1 into the model but in fact they are
116: producing data with many covariates and can use an equation model
117: with some of the covariate; it means that in a model V2+V3 instead
118: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
119: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
120: the equation model is restricted to two variables only (V2, V3)
121: and the combination for V2 should be codtabm(k,1) instead of
122: (codtabm(k,2), and the code should be
123: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
124: made. All of these should be simplified once a day like we did in
125: hpxij() for example by using precov[nres] which is computed in
126: decoderesult for each nres of each resultline. Loop should be done
127: on the equation model globally by distinguishing only product with
128: age (which are changing with age) and no more on type of
129: covariates, single dummies, single covariates.
130:
1.332 brouard 131: Revision 1.331 2022/08/07 05:40:09 brouard
132: *** empty log message ***
133:
1.331 brouard 134: Revision 1.330 2022/08/06 07:18:25 brouard
135: Summary: last 0.99r31
136:
137: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
138:
1.330 brouard 139: Revision 1.329 2022/08/03 17:29:54 brouard
140: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
141:
1.329 brouard 142: Revision 1.328 2022/07/27 17:40:48 brouard
143: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
144:
1.328 brouard 145: Revision 1.327 2022/07/27 14:47:35 brouard
146: Summary: Still a problem for one-step probabilities in case of quantitative variables
147:
1.327 brouard 148: Revision 1.326 2022/07/26 17:33:55 brouard
149: Summary: some test with nres=1
150:
1.326 brouard 151: Revision 1.325 2022/07/25 14:27:23 brouard
152: Summary: r30
153:
154: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
155: coredumped, revealed by Feiuno, thank you.
156:
1.325 brouard 157: Revision 1.324 2022/07/23 17:44:26 brouard
158: *** empty log message ***
159:
1.324 brouard 160: Revision 1.323 2022/07/22 12:30:08 brouard
161: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
162:
1.323 brouard 163: Revision 1.322 2022/07/22 12:27:48 brouard
164: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
165:
1.322 brouard 166: Revision 1.321 2022/07/22 12:04:24 brouard
167: Summary: r28
168:
169: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
170:
1.321 brouard 171: Revision 1.320 2022/06/02 05:10:11 brouard
172: *** empty log message ***
173:
1.320 brouard 174: Revision 1.319 2022/06/02 04:45:11 brouard
175: * imach.c (Module): Adding the Wald tests from the log to the main
176: htm for better display of the maximum likelihood estimators.
177:
1.319 brouard 178: Revision 1.318 2022/05/24 08:10:59 brouard
179: * imach.c (Module): Some attempts to find a bug of wrong estimates
180: of confidencce intervals with product in the equation modelC
181:
1.318 brouard 182: Revision 1.317 2022/05/15 15:06:23 brouard
183: * imach.c (Module): Some minor improvements
184:
1.317 brouard 185: Revision 1.316 2022/05/11 15:11:31 brouard
186: Summary: r27
187:
1.316 brouard 188: Revision 1.315 2022/05/11 15:06:32 brouard
189: *** empty log message ***
190:
1.315 brouard 191: Revision 1.314 2022/04/13 17:43:09 brouard
192: * imach.c (Module): Adding link to text data files
193:
1.314 brouard 194: Revision 1.313 2022/04/11 15:57:42 brouard
195: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
196:
1.313 brouard 197: Revision 1.312 2022/04/05 21:24:39 brouard
198: *** empty log message ***
199:
1.312 brouard 200: Revision 1.311 2022/04/05 21:03:51 brouard
201: Summary: Fixed quantitative covariates
202:
203: Fixed covariates (dummy or quantitative)
204: with missing values have never been allowed but are ERRORS and
205: program quits. Standard deviations of fixed covariates were
206: wrongly computed. Mean and standard deviations of time varying
207: covariates are still not computed.
208:
1.311 brouard 209: Revision 1.310 2022/03/17 08:45:53 brouard
210: Summary: 99r25
211:
212: Improving detection of errors: result lines should be compatible with
213: the model.
214:
1.310 brouard 215: Revision 1.309 2021/05/20 12:39:14 brouard
216: Summary: Version 0.99r24
217:
1.309 brouard 218: Revision 1.308 2021/03/31 13:11:57 brouard
219: Summary: Version 0.99r23
220:
221:
222: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
223:
1.308 brouard 224: Revision 1.307 2021/03/08 18:11:32 brouard
225: Summary: 0.99r22 fixed bug on result:
226:
1.307 brouard 227: Revision 1.306 2021/02/20 15:44:02 brouard
228: Summary: Version 0.99r21
229:
230: * imach.c (Module): Fix bug on quitting after result lines!
231: (Module): Version 0.99r21
232:
1.306 brouard 233: Revision 1.305 2021/02/20 15:28:30 brouard
234: * imach.c (Module): Fix bug on quitting after result lines!
235:
1.305 brouard 236: Revision 1.304 2021/02/12 11:34:20 brouard
237: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
238:
1.304 brouard 239: Revision 1.303 2021/02/11 19:50:15 brouard
240: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
241:
1.303 brouard 242: Revision 1.302 2020/02/22 21:00:05 brouard
243: * (Module): imach.c Update mle=-3 (for computing Life expectancy
244: and life table from the data without any state)
245:
1.302 brouard 246: Revision 1.301 2019/06/04 13:51:20 brouard
247: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
248:
1.301 brouard 249: Revision 1.300 2019/05/22 19:09:45 brouard
250: Summary: version 0.99r19 of May 2019
251:
1.300 brouard 252: Revision 1.299 2019/05/22 18:37:08 brouard
253: Summary: Cleaned 0.99r19
254:
1.299 brouard 255: Revision 1.298 2019/05/22 18:19:56 brouard
256: *** empty log message ***
257:
1.298 brouard 258: Revision 1.297 2019/05/22 17:56:10 brouard
259: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
260:
1.297 brouard 261: Revision 1.296 2019/05/20 13:03:18 brouard
262: Summary: Projection syntax simplified
263:
264:
265: We can now start projections, forward or backward, from the mean date
266: of inteviews up to or down to a number of years of projection:
267: prevforecast=1 yearsfproj=15.3 mobil_average=0
268: or
269: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
270: or
271: prevbackcast=1 yearsbproj=12.3 mobil_average=1
272: or
273: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
274:
1.296 brouard 275: Revision 1.295 2019/05/18 09:52:50 brouard
276: Summary: doxygen tex bug
277:
1.295 brouard 278: Revision 1.294 2019/05/16 14:54:33 brouard
279: Summary: There was some wrong lines added
280:
1.294 brouard 281: Revision 1.293 2019/05/09 15:17:34 brouard
282: *** empty log message ***
283:
1.293 brouard 284: Revision 1.292 2019/05/09 14:17:20 brouard
285: Summary: Some updates
286:
1.292 brouard 287: Revision 1.291 2019/05/09 13:44:18 brouard
288: Summary: Before ncovmax
289:
1.291 brouard 290: Revision 1.290 2019/05/09 13:39:37 brouard
291: Summary: 0.99r18 unlimited number of individuals
292:
293: 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.
294:
1.290 brouard 295: Revision 1.289 2018/12/13 09:16:26 brouard
296: Summary: Bug for young ages (<-30) will be in r17
297:
1.289 brouard 298: Revision 1.288 2018/05/02 20:58:27 brouard
299: Summary: Some bugs fixed
300:
1.288 brouard 301: Revision 1.287 2018/05/01 17:57:25 brouard
302: Summary: Bug fixed by providing frequencies only for non missing covariates
303:
1.287 brouard 304: Revision 1.286 2018/04/27 14:27:04 brouard
305: Summary: some minor bugs
306:
1.286 brouard 307: Revision 1.285 2018/04/21 21:02:16 brouard
308: Summary: Some bugs fixed, valgrind tested
309:
1.285 brouard 310: Revision 1.284 2018/04/20 05:22:13 brouard
311: Summary: Computing mean and stdeviation of fixed quantitative variables
312:
1.284 brouard 313: Revision 1.283 2018/04/19 14:49:16 brouard
314: Summary: Some minor bugs fixed
315:
1.283 brouard 316: Revision 1.282 2018/02/27 22:50:02 brouard
317: *** empty log message ***
318:
1.282 brouard 319: Revision 1.281 2018/02/27 19:25:23 brouard
320: Summary: Adding second argument for quitting
321:
1.281 brouard 322: Revision 1.280 2018/02/21 07:58:13 brouard
323: Summary: 0.99r15
324:
325: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
326:
1.280 brouard 327: Revision 1.279 2017/07/20 13:35:01 brouard
328: Summary: temporary working
329:
1.279 brouard 330: Revision 1.278 2017/07/19 14:09:02 brouard
331: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
332:
1.278 brouard 333: Revision 1.277 2017/07/17 08:53:49 brouard
334: Summary: BOM files can be read now
335:
1.277 brouard 336: Revision 1.276 2017/06/30 15:48:31 brouard
337: Summary: Graphs improvements
338:
1.276 brouard 339: Revision 1.275 2017/06/30 13:39:33 brouard
340: Summary: Saito's color
341:
1.275 brouard 342: Revision 1.274 2017/06/29 09:47:08 brouard
343: Summary: Version 0.99r14
344:
1.274 brouard 345: Revision 1.273 2017/06/27 11:06:02 brouard
346: Summary: More documentation on projections
347:
1.273 brouard 348: Revision 1.272 2017/06/27 10:22:40 brouard
349: Summary: Color of backprojection changed from 6 to 5(yellow)
350:
1.272 brouard 351: Revision 1.271 2017/06/27 10:17:50 brouard
352: Summary: Some bug with rint
353:
1.271 brouard 354: Revision 1.270 2017/05/24 05:45:29 brouard
355: *** empty log message ***
356:
1.270 brouard 357: Revision 1.269 2017/05/23 08:39:25 brouard
358: Summary: Code into subroutine, cleanings
359:
1.269 brouard 360: Revision 1.268 2017/05/18 20:09:32 brouard
361: Summary: backprojection and confidence intervals of backprevalence
362:
1.268 brouard 363: Revision 1.267 2017/05/13 10:25:05 brouard
364: Summary: temporary save for backprojection
365:
1.267 brouard 366: Revision 1.266 2017/05/13 07:26:12 brouard
367: Summary: Version 0.99r13 (improvements and bugs fixed)
368:
1.266 brouard 369: Revision 1.265 2017/04/26 16:22:11 brouard
370: Summary: imach 0.99r13 Some bugs fixed
371:
1.265 brouard 372: Revision 1.264 2017/04/26 06:01:29 brouard
373: Summary: Labels in graphs
374:
1.264 brouard 375: Revision 1.263 2017/04/24 15:23:15 brouard
376: Summary: to save
377:
1.263 brouard 378: Revision 1.262 2017/04/18 16:48:12 brouard
379: *** empty log message ***
380:
1.262 brouard 381: Revision 1.261 2017/04/05 10:14:09 brouard
382: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
383:
1.261 brouard 384: Revision 1.260 2017/04/04 17:46:59 brouard
385: Summary: Gnuplot indexations fixed (humm)
386:
1.260 brouard 387: Revision 1.259 2017/04/04 13:01:16 brouard
388: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
389:
1.259 brouard 390: Revision 1.258 2017/04/03 10:17:47 brouard
391: Summary: Version 0.99r12
392:
393: Some cleanings, conformed with updated documentation.
394:
1.258 brouard 395: Revision 1.257 2017/03/29 16:53:30 brouard
396: Summary: Temp
397:
1.257 brouard 398: Revision 1.256 2017/03/27 05:50:23 brouard
399: Summary: Temporary
400:
1.256 brouard 401: Revision 1.255 2017/03/08 16:02:28 brouard
402: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
403:
1.255 brouard 404: Revision 1.254 2017/03/08 07:13:00 brouard
405: Summary: Fixing data parameter line
406:
1.254 brouard 407: Revision 1.253 2016/12/15 11:59:41 brouard
408: Summary: 0.99 in progress
409:
1.253 brouard 410: Revision 1.252 2016/09/15 21:15:37 brouard
411: *** empty log message ***
412:
1.252 brouard 413: Revision 1.251 2016/09/15 15:01:13 brouard
414: Summary: not working
415:
1.251 brouard 416: Revision 1.250 2016/09/08 16:07:27 brouard
417: Summary: continue
418:
1.250 brouard 419: Revision 1.249 2016/09/07 17:14:18 brouard
420: Summary: Starting values from frequencies
421:
1.249 brouard 422: Revision 1.248 2016/09/07 14:10:18 brouard
423: *** empty log message ***
424:
1.248 brouard 425: Revision 1.247 2016/09/02 11:11:21 brouard
426: *** empty log message ***
427:
1.247 brouard 428: Revision 1.246 2016/09/02 08:49:22 brouard
429: *** empty log message ***
430:
1.246 brouard 431: Revision 1.245 2016/09/02 07:25:01 brouard
432: *** empty log message ***
433:
1.245 brouard 434: Revision 1.244 2016/09/02 07:17:34 brouard
435: *** empty log message ***
436:
1.244 brouard 437: Revision 1.243 2016/09/02 06:45:35 brouard
438: *** empty log message ***
439:
1.243 brouard 440: Revision 1.242 2016/08/30 15:01:20 brouard
441: Summary: Fixing a lots
442:
1.242 brouard 443: Revision 1.241 2016/08/29 17:17:25 brouard
444: Summary: gnuplot problem in Back projection to fix
445:
1.241 brouard 446: Revision 1.240 2016/08/29 07:53:18 brouard
447: Summary: Better
448:
1.240 brouard 449: Revision 1.239 2016/08/26 15:51:03 brouard
450: Summary: Improvement in Powell output in order to copy and paste
451:
452: Author:
453:
1.239 brouard 454: Revision 1.238 2016/08/26 14:23:35 brouard
455: Summary: Starting tests of 0.99
456:
1.238 brouard 457: Revision 1.237 2016/08/26 09:20:19 brouard
458: Summary: to valgrind
459:
1.237 brouard 460: Revision 1.236 2016/08/25 10:50:18 brouard
461: *** empty log message ***
462:
1.236 brouard 463: Revision 1.235 2016/08/25 06:59:23 brouard
464: *** empty log message ***
465:
1.235 brouard 466: Revision 1.234 2016/08/23 16:51:20 brouard
467: *** empty log message ***
468:
1.234 brouard 469: Revision 1.233 2016/08/23 07:40:50 brouard
470: Summary: not working
471:
1.233 brouard 472: Revision 1.232 2016/08/22 14:20:21 brouard
473: Summary: not working
474:
1.232 brouard 475: Revision 1.231 2016/08/22 07:17:15 brouard
476: Summary: not working
477:
1.231 brouard 478: Revision 1.230 2016/08/22 06:55:53 brouard
479: Summary: Not working
480:
1.230 brouard 481: Revision 1.229 2016/07/23 09:45:53 brouard
482: Summary: Completing for func too
483:
1.229 brouard 484: Revision 1.228 2016/07/22 17:45:30 brouard
485: Summary: Fixing some arrays, still debugging
486:
1.227 brouard 487: Revision 1.226 2016/07/12 18:42:34 brouard
488: Summary: temp
489:
1.226 brouard 490: Revision 1.225 2016/07/12 08:40:03 brouard
491: Summary: saving but not running
492:
1.225 brouard 493: Revision 1.224 2016/07/01 13:16:01 brouard
494: Summary: Fixes
495:
1.224 brouard 496: Revision 1.223 2016/02/19 09:23:35 brouard
497: Summary: temporary
498:
1.223 brouard 499: Revision 1.222 2016/02/17 08:14:50 brouard
500: Summary: Probably last 0.98 stable version 0.98r6
501:
1.222 brouard 502: Revision 1.221 2016/02/15 23:35:36 brouard
503: Summary: minor bug
504:
1.220 brouard 505: Revision 1.219 2016/02/15 00:48:12 brouard
506: *** empty log message ***
507:
1.219 brouard 508: Revision 1.218 2016/02/12 11:29:23 brouard
509: Summary: 0.99 Back projections
510:
1.218 brouard 511: Revision 1.217 2015/12/23 17:18:31 brouard
512: Summary: Experimental backcast
513:
1.217 brouard 514: Revision 1.216 2015/12/18 17:32:11 brouard
515: Summary: 0.98r4 Warning and status=-2
516:
517: Version 0.98r4 is now:
518: - displaying an error when status is -1, date of interview unknown and date of death known;
519: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
520: Older changes concerning s=-2, dating from 2005 have been supersed.
521:
1.216 brouard 522: Revision 1.215 2015/12/16 08:52:24 brouard
523: Summary: 0.98r4 working
524:
1.215 brouard 525: Revision 1.214 2015/12/16 06:57:54 brouard
526: Summary: temporary not working
527:
1.214 brouard 528: Revision 1.213 2015/12/11 18:22:17 brouard
529: Summary: 0.98r4
530:
1.213 brouard 531: Revision 1.212 2015/11/21 12:47:24 brouard
532: Summary: minor typo
533:
1.212 brouard 534: Revision 1.211 2015/11/21 12:41:11 brouard
535: Summary: 0.98r3 with some graph of projected cross-sectional
536:
537: Author: Nicolas Brouard
538:
1.211 brouard 539: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 540: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 541: Summary: Adding ftolpl parameter
542: Author: N Brouard
543:
544: We had difficulties to get smoothed confidence intervals. It was due
545: to the period prevalence which wasn't computed accurately. The inner
546: parameter ftolpl is now an outer parameter of the .imach parameter
547: file after estepm. If ftolpl is small 1.e-4 and estepm too,
548: computation are long.
549:
1.209 brouard 550: Revision 1.208 2015/11/17 14:31:57 brouard
551: Summary: temporary
552:
1.208 brouard 553: Revision 1.207 2015/10/27 17:36:57 brouard
554: *** empty log message ***
555:
1.207 brouard 556: Revision 1.206 2015/10/24 07:14:11 brouard
557: *** empty log message ***
558:
1.206 brouard 559: Revision 1.205 2015/10/23 15:50:53 brouard
560: Summary: 0.98r3 some clarification for graphs on likelihood contributions
561:
1.205 brouard 562: Revision 1.204 2015/10/01 16:20:26 brouard
563: Summary: Some new graphs of contribution to likelihood
564:
1.204 brouard 565: Revision 1.203 2015/09/30 17:45:14 brouard
566: Summary: looking at better estimation of the hessian
567:
568: Also a better criteria for convergence to the period prevalence And
569: therefore adding the number of years needed to converge. (The
570: prevalence in any alive state shold sum to one
571:
1.203 brouard 572: Revision 1.202 2015/09/22 19:45:16 brouard
573: Summary: Adding some overall graph on contribution to likelihood. Might change
574:
1.202 brouard 575: Revision 1.201 2015/09/15 17:34:58 brouard
576: Summary: 0.98r0
577:
578: - Some new graphs like suvival functions
579: - Some bugs fixed like model=1+age+V2.
580:
1.201 brouard 581: Revision 1.200 2015/09/09 16:53:55 brouard
582: Summary: Big bug thanks to Flavia
583:
584: Even model=1+age+V2. did not work anymore
585:
1.200 brouard 586: Revision 1.199 2015/09/07 14:09:23 brouard
587: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
588:
1.199 brouard 589: Revision 1.198 2015/09/03 07:14:39 brouard
590: Summary: 0.98q5 Flavia
591:
1.198 brouard 592: Revision 1.197 2015/09/01 18:24:39 brouard
593: *** empty log message ***
594:
1.197 brouard 595: Revision 1.196 2015/08/18 23:17:52 brouard
596: Summary: 0.98q5
597:
1.196 brouard 598: Revision 1.195 2015/08/18 16:28:39 brouard
599: Summary: Adding a hack for testing purpose
600:
601: After reading the title, ftol and model lines, if the comment line has
602: a q, starting with #q, the answer at the end of the run is quit. It
603: permits to run test files in batch with ctest. The former workaround was
604: $ echo q | imach foo.imach
605:
1.195 brouard 606: Revision 1.194 2015/08/18 13:32:00 brouard
607: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
608:
1.194 brouard 609: Revision 1.193 2015/08/04 07:17:42 brouard
610: Summary: 0.98q4
611:
1.193 brouard 612: Revision 1.192 2015/07/16 16:49:02 brouard
613: Summary: Fixing some outputs
614:
1.192 brouard 615: Revision 1.191 2015/07/14 10:00:33 brouard
616: Summary: Some fixes
617:
1.191 brouard 618: Revision 1.190 2015/05/05 08:51:13 brouard
619: Summary: Adding digits in output parameters (7 digits instead of 6)
620:
621: Fix 1+age+.
622:
1.190 brouard 623: Revision 1.189 2015/04/30 14:45:16 brouard
624: Summary: 0.98q2
625:
1.189 brouard 626: Revision 1.188 2015/04/30 08:27:53 brouard
627: *** empty log message ***
628:
1.188 brouard 629: Revision 1.187 2015/04/29 09:11:15 brouard
630: *** empty log message ***
631:
1.187 brouard 632: Revision 1.186 2015/04/23 12:01:52 brouard
633: Summary: V1*age is working now, version 0.98q1
634:
635: Some codes had been disabled in order to simplify and Vn*age was
636: working in the optimization phase, ie, giving correct MLE parameters,
637: but, as usual, outputs were not correct and program core dumped.
638:
1.186 brouard 639: Revision 1.185 2015/03/11 13:26:42 brouard
640: Summary: Inclusion of compile and links command line for Intel Compiler
641:
1.185 brouard 642: Revision 1.184 2015/03/11 11:52:39 brouard
643: Summary: Back from Windows 8. Intel Compiler
644:
1.184 brouard 645: Revision 1.183 2015/03/10 20:34:32 brouard
646: Summary: 0.98q0, trying with directest, mnbrak fixed
647:
648: We use directest instead of original Powell test; probably no
649: incidence on the results, but better justifications;
650: We fixed Numerical Recipes mnbrak routine which was wrong and gave
651: wrong results.
652:
1.183 brouard 653: Revision 1.182 2015/02/12 08:19:57 brouard
654: Summary: Trying to keep directest which seems simpler and more general
655: Author: Nicolas Brouard
656:
1.182 brouard 657: Revision 1.181 2015/02/11 23:22:24 brouard
658: Summary: Comments on Powell added
659:
660: Author:
661:
1.181 brouard 662: Revision 1.180 2015/02/11 17:33:45 brouard
663: Summary: Finishing move from main to function (hpijx and prevalence_limit)
664:
1.180 brouard 665: Revision 1.179 2015/01/04 09:57:06 brouard
666: Summary: back to OS/X
667:
1.179 brouard 668: Revision 1.178 2015/01/04 09:35:48 brouard
669: *** empty log message ***
670:
1.178 brouard 671: Revision 1.177 2015/01/03 18:40:56 brouard
672: Summary: Still testing ilc32 on OSX
673:
1.177 brouard 674: Revision 1.176 2015/01/03 16:45:04 brouard
675: *** empty log message ***
676:
1.176 brouard 677: Revision 1.175 2015/01/03 16:33:42 brouard
678: *** empty log message ***
679:
1.175 brouard 680: Revision 1.174 2015/01/03 16:15:49 brouard
681: Summary: Still in cross-compilation
682:
1.174 brouard 683: Revision 1.173 2015/01/03 12:06:26 brouard
684: Summary: trying to detect cross-compilation
685:
1.173 brouard 686: Revision 1.172 2014/12/27 12:07:47 brouard
687: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
688:
1.172 brouard 689: Revision 1.171 2014/12/23 13:26:59 brouard
690: Summary: Back from Visual C
691:
692: Still problem with utsname.h on Windows
693:
1.171 brouard 694: Revision 1.170 2014/12/23 11:17:12 brouard
695: Summary: Cleaning some \%% back to %%
696:
697: The escape was mandatory for a specific compiler (which one?), but too many warnings.
698:
1.170 brouard 699: Revision 1.169 2014/12/22 23:08:31 brouard
700: Summary: 0.98p
701:
702: Outputs some informations on compiler used, OS etc. Testing on different platforms.
703:
1.169 brouard 704: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 705: Summary: update
1.169 brouard 706:
1.168 brouard 707: Revision 1.167 2014/12/22 13:50:56 brouard
708: Summary: Testing uname and compiler version and if compiled 32 or 64
709:
710: Testing on Linux 64
711:
1.167 brouard 712: Revision 1.166 2014/12/22 11:40:47 brouard
713: *** empty log message ***
714:
1.166 brouard 715: Revision 1.165 2014/12/16 11:20:36 brouard
716: Summary: After compiling on Visual C
717:
718: * imach.c (Module): Merging 1.61 to 1.162
719:
1.165 brouard 720: Revision 1.164 2014/12/16 10:52:11 brouard
721: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
722:
723: * imach.c (Module): Merging 1.61 to 1.162
724:
1.164 brouard 725: Revision 1.163 2014/12/16 10:30:11 brouard
726: * imach.c (Module): Merging 1.61 to 1.162
727:
1.163 brouard 728: Revision 1.162 2014/09/25 11:43:39 brouard
729: Summary: temporary backup 0.99!
730:
1.162 brouard 731: Revision 1.1 2014/09/16 11:06:58 brouard
732: Summary: With some code (wrong) for nlopt
733:
734: Author:
735:
736: Revision 1.161 2014/09/15 20:41:41 brouard
737: Summary: Problem with macro SQR on Intel compiler
738:
1.161 brouard 739: Revision 1.160 2014/09/02 09:24:05 brouard
740: *** empty log message ***
741:
1.160 brouard 742: Revision 1.159 2014/09/01 10:34:10 brouard
743: Summary: WIN32
744: Author: Brouard
745:
1.159 brouard 746: Revision 1.158 2014/08/27 17:11:51 brouard
747: *** empty log message ***
748:
1.158 brouard 749: Revision 1.157 2014/08/27 16:26:55 brouard
750: Summary: Preparing windows Visual studio version
751: Author: Brouard
752:
753: In order to compile on Visual studio, time.h is now correct and time_t
754: and tm struct should be used. difftime should be used but sometimes I
755: just make the differences in raw time format (time(&now).
756: Trying to suppress #ifdef LINUX
757: Add xdg-open for __linux in order to open default browser.
758:
1.157 brouard 759: Revision 1.156 2014/08/25 20:10:10 brouard
760: *** empty log message ***
761:
1.156 brouard 762: Revision 1.155 2014/08/25 18:32:34 brouard
763: Summary: New compile, minor changes
764: Author: Brouard
765:
1.155 brouard 766: Revision 1.154 2014/06/20 17:32:08 brouard
767: Summary: Outputs now all graphs of convergence to period prevalence
768:
1.154 brouard 769: Revision 1.153 2014/06/20 16:45:46 brouard
770: Summary: If 3 live state, convergence to period prevalence on same graph
771: Author: Brouard
772:
1.153 brouard 773: Revision 1.152 2014/06/18 17:54:09 brouard
774: Summary: open browser, use gnuplot on same dir than imach if not found in the path
775:
1.152 brouard 776: Revision 1.151 2014/06/18 16:43:30 brouard
777: *** empty log message ***
778:
1.151 brouard 779: Revision 1.150 2014/06/18 16:42:35 brouard
780: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
781: Author: brouard
782:
1.150 brouard 783: Revision 1.149 2014/06/18 15:51:14 brouard
784: Summary: Some fixes in parameter files errors
785: Author: Nicolas Brouard
786:
1.149 brouard 787: Revision 1.148 2014/06/17 17:38:48 brouard
788: Summary: Nothing new
789: Author: Brouard
790:
791: Just a new packaging for OS/X version 0.98nS
792:
1.148 brouard 793: Revision 1.147 2014/06/16 10:33:11 brouard
794: *** empty log message ***
795:
1.147 brouard 796: Revision 1.146 2014/06/16 10:20:28 brouard
797: Summary: Merge
798: Author: Brouard
799:
800: Merge, before building revised version.
801:
1.146 brouard 802: Revision 1.145 2014/06/10 21:23:15 brouard
803: Summary: Debugging with valgrind
804: Author: Nicolas Brouard
805:
806: Lot of changes in order to output the results with some covariates
807: After the Edimburgh REVES conference 2014, it seems mandatory to
808: improve the code.
809: No more memory valgrind error but a lot has to be done in order to
810: continue the work of splitting the code into subroutines.
811: Also, decodemodel has been improved. Tricode is still not
812: optimal. nbcode should be improved. Documentation has been added in
813: the source code.
814:
1.144 brouard 815: Revision 1.143 2014/01/26 09:45:38 brouard
816: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
817:
818: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
819: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
820:
1.143 brouard 821: Revision 1.142 2014/01/26 03:57:36 brouard
822: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
823:
824: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
825:
1.142 brouard 826: Revision 1.141 2014/01/26 02:42:01 brouard
827: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
828:
1.141 brouard 829: Revision 1.140 2011/09/02 10:37:54 brouard
830: Summary: times.h is ok with mingw32 now.
831:
1.140 brouard 832: Revision 1.139 2010/06/14 07:50:17 brouard
833: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
834: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
835:
1.139 brouard 836: Revision 1.138 2010/04/30 18:19:40 brouard
837: *** empty log message ***
838:
1.138 brouard 839: Revision 1.137 2010/04/29 18:11:38 brouard
840: (Module): Checking covariates for more complex models
841: than V1+V2. A lot of change to be done. Unstable.
842:
1.137 brouard 843: Revision 1.136 2010/04/26 20:30:53 brouard
844: (Module): merging some libgsl code. Fixing computation
845: of likelione (using inter/intrapolation if mle = 0) in order to
846: get same likelihood as if mle=1.
847: Some cleaning of code and comments added.
848:
1.136 brouard 849: Revision 1.135 2009/10/29 15:33:14 brouard
850: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
851:
1.135 brouard 852: Revision 1.134 2009/10/29 13:18:53 brouard
853: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
854:
1.134 brouard 855: Revision 1.133 2009/07/06 10:21:25 brouard
856: just nforces
857:
1.133 brouard 858: Revision 1.132 2009/07/06 08:22:05 brouard
859: Many tings
860:
1.132 brouard 861: Revision 1.131 2009/06/20 16:22:47 brouard
862: Some dimensions resccaled
863:
1.131 brouard 864: Revision 1.130 2009/05/26 06:44:34 brouard
865: (Module): Max Covariate is now set to 20 instead of 8. A
866: lot of cleaning with variables initialized to 0. Trying to make
867: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
868:
1.130 brouard 869: Revision 1.129 2007/08/31 13:49:27 lievre
870: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
871:
1.129 lievre 872: Revision 1.128 2006/06/30 13:02:05 brouard
873: (Module): Clarifications on computing e.j
874:
1.128 brouard 875: Revision 1.127 2006/04/28 18:11:50 brouard
876: (Module): Yes the sum of survivors was wrong since
877: imach-114 because nhstepm was no more computed in the age
878: loop. Now we define nhstepma in the age loop.
879: (Module): In order to speed up (in case of numerous covariates) we
880: compute health expectancies (without variances) in a first step
881: and then all the health expectancies with variances or standard
882: deviation (needs data from the Hessian matrices) which slows the
883: computation.
884: In the future we should be able to stop the program is only health
885: expectancies and graph are needed without standard deviations.
886:
1.127 brouard 887: Revision 1.126 2006/04/28 17:23:28 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: Version 0.98h
892:
1.126 brouard 893: Revision 1.125 2006/04/04 15:20:31 lievre
894: Errors in calculation of health expectancies. Age was not initialized.
895: Forecasting file added.
896:
897: Revision 1.124 2006/03/22 17:13:53 lievre
898: Parameters are printed with %lf instead of %f (more numbers after the comma).
899: The log-likelihood is printed in the log file
900:
901: Revision 1.123 2006/03/20 10:52:43 brouard
902: * imach.c (Module): <title> changed, corresponds to .htm file
903: name. <head> headers where missing.
904:
905: * imach.c (Module): Weights can have a decimal point as for
906: English (a comma might work with a correct LC_NUMERIC environment,
907: otherwise the weight is truncated).
908: Modification of warning when the covariates values are not 0 or
909: 1.
910: Version 0.98g
911:
912: Revision 1.122 2006/03/20 09:45:41 brouard
913: (Module): Weights can have a decimal point as for
914: English (a comma might work with a correct LC_NUMERIC environment,
915: otherwise the weight is truncated).
916: Modification of warning when the covariates values are not 0 or
917: 1.
918: Version 0.98g
919:
920: Revision 1.121 2006/03/16 17:45:01 lievre
921: * imach.c (Module): Comments concerning covariates added
922:
923: * imach.c (Module): refinements in the computation of lli if
924: status=-2 in order to have more reliable computation if stepm is
925: not 1 month. Version 0.98f
926:
927: Revision 1.120 2006/03/16 15:10:38 lievre
928: (Module): refinements in the computation of lli if
929: status=-2 in order to have more reliable computation if stepm is
930: not 1 month. Version 0.98f
931:
932: Revision 1.119 2006/03/15 17:42:26 brouard
933: (Module): Bug if status = -2, the loglikelihood was
934: computed as likelihood omitting the logarithm. Version O.98e
935:
936: Revision 1.118 2006/03/14 18:20:07 brouard
937: (Module): varevsij Comments added explaining the second
938: table of variances if popbased=1 .
939: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
940: (Module): Function pstamp added
941: (Module): Version 0.98d
942:
943: Revision 1.117 2006/03/14 17:16:22 brouard
944: (Module): varevsij Comments added explaining the second
945: table of variances if popbased=1 .
946: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
947: (Module): Function pstamp added
948: (Module): Version 0.98d
949:
950: Revision 1.116 2006/03/06 10:29:27 brouard
951: (Module): Variance-covariance wrong links and
952: varian-covariance of ej. is needed (Saito).
953:
954: Revision 1.115 2006/02/27 12:17:45 brouard
955: (Module): One freematrix added in mlikeli! 0.98c
956:
957: Revision 1.114 2006/02/26 12:57:58 brouard
958: (Module): Some improvements in processing parameter
959: filename with strsep.
960:
961: Revision 1.113 2006/02/24 14:20:24 brouard
962: (Module): Memory leaks checks with valgrind and:
963: datafile was not closed, some imatrix were not freed and on matrix
964: allocation too.
965:
966: Revision 1.112 2006/01/30 09:55:26 brouard
967: (Module): Back to gnuplot.exe instead of wgnuplot.exe
968:
969: Revision 1.111 2006/01/25 20:38:18 brouard
970: (Module): Lots of cleaning and bugs added (Gompertz)
971: (Module): Comments can be added in data file. Missing date values
972: can be a simple dot '.'.
973:
974: Revision 1.110 2006/01/25 00:51:50 brouard
975: (Module): Lots of cleaning and bugs added (Gompertz)
976:
977: Revision 1.109 2006/01/24 19:37:15 brouard
978: (Module): Comments (lines starting with a #) are allowed in data.
979:
980: Revision 1.108 2006/01/19 18:05:42 lievre
981: Gnuplot problem appeared...
982: To be fixed
983:
984: Revision 1.107 2006/01/19 16:20:37 brouard
985: Test existence of gnuplot in imach path
986:
987: Revision 1.106 2006/01/19 13:24:36 brouard
988: Some cleaning and links added in html output
989:
990: Revision 1.105 2006/01/05 20:23:19 lievre
991: *** empty log message ***
992:
993: Revision 1.104 2005/09/30 16:11:43 lievre
994: (Module): sump fixed, loop imx fixed, and simplifications.
995: (Module): If the status is missing at the last wave but we know
996: that the person is alive, then we can code his/her status as -2
997: (instead of missing=-1 in earlier versions) and his/her
998: contributions to the likelihood is 1 - Prob of dying from last
999: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1000: the healthy state at last known wave). Version is 0.98
1001:
1002: Revision 1.103 2005/09/30 15:54:49 lievre
1003: (Module): sump fixed, loop imx fixed, and simplifications.
1004:
1005: Revision 1.102 2004/09/15 17:31:30 brouard
1006: Add the possibility to read data file including tab characters.
1007:
1008: Revision 1.101 2004/09/15 10:38:38 brouard
1009: Fix on curr_time
1010:
1011: Revision 1.100 2004/07/12 18:29:06 brouard
1012: Add version for Mac OS X. Just define UNIX in Makefile
1013:
1014: Revision 1.99 2004/06/05 08:57:40 brouard
1015: *** empty log message ***
1016:
1017: Revision 1.98 2004/05/16 15:05:56 brouard
1018: New version 0.97 . First attempt to estimate force of mortality
1019: directly from the data i.e. without the need of knowing the health
1020: state at each age, but using a Gompertz model: log u =a + b*age .
1021: This is the basic analysis of mortality and should be done before any
1022: other analysis, in order to test if the mortality estimated from the
1023: cross-longitudinal survey is different from the mortality estimated
1024: from other sources like vital statistic data.
1025:
1026: The same imach parameter file can be used but the option for mle should be -3.
1027:
1.324 brouard 1028: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1029: former routines in order to include the new code within the former code.
1030:
1031: The output is very simple: only an estimate of the intercept and of
1032: the slope with 95% confident intervals.
1033:
1034: Current limitations:
1035: A) Even if you enter covariates, i.e. with the
1036: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1037: B) There is no computation of Life Expectancy nor Life Table.
1038:
1039: Revision 1.97 2004/02/20 13:25:42 lievre
1040: Version 0.96d. Population forecasting command line is (temporarily)
1041: suppressed.
1042:
1043: Revision 1.96 2003/07/15 15:38:55 brouard
1044: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1045: rewritten within the same printf. Workaround: many printfs.
1046:
1047: Revision 1.95 2003/07/08 07:54:34 brouard
1048: * imach.c (Repository):
1049: (Repository): Using imachwizard code to output a more meaningful covariance
1050: matrix (cov(a12,c31) instead of numbers.
1051:
1052: Revision 1.94 2003/06/27 13:00:02 brouard
1053: Just cleaning
1054:
1055: Revision 1.93 2003/06/25 16:33:55 brouard
1056: (Module): On windows (cygwin) function asctime_r doesn't
1057: exist so I changed back to asctime which exists.
1058: (Module): Version 0.96b
1059:
1060: Revision 1.92 2003/06/25 16:30:45 brouard
1061: (Module): On windows (cygwin) function asctime_r doesn't
1062: exist so I changed back to asctime which exists.
1063:
1064: Revision 1.91 2003/06/25 15:30:29 brouard
1065: * imach.c (Repository): Duplicated warning errors corrected.
1066: (Repository): Elapsed time after each iteration is now output. It
1067: helps to forecast when convergence will be reached. Elapsed time
1068: is stamped in powell. We created a new html file for the graphs
1069: concerning matrix of covariance. It has extension -cov.htm.
1070:
1071: Revision 1.90 2003/06/24 12:34:15 brouard
1072: (Module): Some bugs corrected for windows. Also, when
1073: mle=-1 a template is output in file "or"mypar.txt with the design
1074: of the covariance matrix to be input.
1075:
1076: Revision 1.89 2003/06/24 12:30:52 brouard
1077: (Module): Some bugs corrected for windows. Also, when
1078: mle=-1 a template is output in file "or"mypar.txt with the design
1079: of the covariance matrix to be input.
1080:
1081: Revision 1.88 2003/06/23 17:54:56 brouard
1082: * 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.
1083:
1084: Revision 1.87 2003/06/18 12:26:01 brouard
1085: Version 0.96
1086:
1087: Revision 1.86 2003/06/17 20:04:08 brouard
1088: (Module): Change position of html and gnuplot routines and added
1089: routine fileappend.
1090:
1091: Revision 1.85 2003/06/17 13:12:43 brouard
1092: * imach.c (Repository): Check when date of death was earlier that
1093: current date of interview. It may happen when the death was just
1094: prior to the death. In this case, dh was negative and likelihood
1095: was wrong (infinity). We still send an "Error" but patch by
1096: assuming that the date of death was just one stepm after the
1097: interview.
1098: (Repository): Because some people have very long ID (first column)
1099: we changed int to long in num[] and we added a new lvector for
1100: memory allocation. But we also truncated to 8 characters (left
1101: truncation)
1102: (Repository): No more line truncation errors.
1103:
1104: Revision 1.84 2003/06/13 21:44:43 brouard
1105: * imach.c (Repository): Replace "freqsummary" at a correct
1106: place. It differs from routine "prevalence" which may be called
1107: many times. Probs is memory consuming and must be used with
1108: parcimony.
1109: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1110:
1111: Revision 1.83 2003/06/10 13:39:11 lievre
1112: *** empty log message ***
1113:
1114: Revision 1.82 2003/06/05 15:57:20 brouard
1115: Add log in imach.c and fullversion number is now printed.
1116:
1117: */
1118: /*
1119: Interpolated Markov Chain
1120:
1121: Short summary of the programme:
1122:
1.227 brouard 1123: This program computes Healthy Life Expectancies or State-specific
1124: (if states aren't health statuses) Expectancies from
1125: cross-longitudinal data. Cross-longitudinal data consist in:
1126:
1127: -1- a first survey ("cross") where individuals from different ages
1128: are interviewed on their health status or degree of disability (in
1129: the case of a health survey which is our main interest)
1130:
1131: -2- at least a second wave of interviews ("longitudinal") which
1132: measure each change (if any) in individual health status. Health
1133: expectancies are computed from the time spent in each health state
1134: according to a model. More health states you consider, more time is
1135: necessary to reach the Maximum Likelihood of the parameters involved
1136: in the model. The simplest model is the multinomial logistic model
1137: where pij is the probability to be observed in state j at the second
1138: wave conditional to be observed in state i at the first
1139: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1140: etc , where 'age' is age and 'sex' is a covariate. If you want to
1141: have a more complex model than "constant and age", you should modify
1142: the program where the markup *Covariates have to be included here
1143: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1144: convergence.
1145:
1146: The advantage of this computer programme, compared to a simple
1147: multinomial logistic model, is clear when the delay between waves is not
1148: identical for each individual. Also, if a individual missed an
1149: intermediate interview, the information is lost, but taken into
1150: account using an interpolation or extrapolation.
1151:
1152: hPijx is the probability to be observed in state i at age x+h
1153: conditional to the observed state i at age x. The delay 'h' can be
1154: split into an exact number (nh*stepm) of unobserved intermediate
1155: states. This elementary transition (by month, quarter,
1156: semester or year) is modelled as a multinomial logistic. The hPx
1157: matrix is simply the matrix product of nh*stepm elementary matrices
1158: and the contribution of each individual to the likelihood is simply
1159: hPijx.
1160:
1161: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1162: of the life expectancies. It also computes the period (stable) prevalence.
1163:
1164: Back prevalence and projections:
1.227 brouard 1165:
1166: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1167: double agemaxpar, double ftolpl, int *ncvyearp, double
1168: dateprev1,double dateprev2, int firstpass, int lastpass, int
1169: mobilavproj)
1170:
1171: Computes the back prevalence limit for any combination of
1172: covariate values k at any age between ageminpar and agemaxpar and
1173: returns it in **bprlim. In the loops,
1174:
1175: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1176: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1177:
1178: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1179: Computes for any combination of covariates k and any age between bage and fage
1180: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1181: oldm=oldms;savm=savms;
1.227 brouard 1182:
1.267 brouard 1183: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1184: Computes the transition matrix starting at age 'age' over
1185: 'nhstepm*hstepm*stepm' months (i.e. until
1186: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1187: nhstepm*hstepm matrices.
1188:
1189: Returns p3mat[i][j][h] after calling
1190: p3mat[i][j][h]=matprod2(newm,
1191: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1192: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1193: oldm);
1.226 brouard 1194:
1195: Important routines
1196:
1197: - func (or funcone), computes logit (pij) distinguishing
1198: o fixed variables (single or product dummies or quantitative);
1199: o varying variables by:
1200: (1) wave (single, product dummies, quantitative),
1201: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1202: % fixed dummy (treated) or quantitative (not done because time-consuming);
1203: % varying dummy (not done) or quantitative (not done);
1204: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1205: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1206: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1207: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1208: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1209:
1.226 brouard 1210:
1211:
1.324 brouard 1212: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1213: Institut national d'études démographiques, Paris.
1.126 brouard 1214: This software have been partly granted by Euro-REVES, a concerted action
1215: from the European Union.
1216: It is copyrighted identically to a GNU software product, ie programme and
1217: software can be distributed freely for non commercial use. Latest version
1218: can be accessed at http://euroreves.ined.fr/imach .
1219:
1220: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1221: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1222:
1223: **********************************************************************/
1224: /*
1225: main
1226: read parameterfile
1227: read datafile
1228: concatwav
1229: freqsummary
1230: if (mle >= 1)
1231: mlikeli
1232: print results files
1233: if mle==1
1234: computes hessian
1235: read end of parameter file: agemin, agemax, bage, fage, estepm
1236: begin-prev-date,...
1237: open gnuplot file
1238: open html file
1.145 brouard 1239: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1240: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1241: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1242: freexexit2 possible for memory heap.
1243:
1244: h Pij x | pij_nom ficrestpij
1245: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1246: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1247: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1248:
1249: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1250: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1251: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1252: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1253: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1254:
1.126 brouard 1255: forecasting if prevfcast==1 prevforecast call prevalence()
1256: health expectancies
1257: Variance-covariance of DFLE
1258: prevalence()
1259: movingaverage()
1260: varevsij()
1261: if popbased==1 varevsij(,popbased)
1262: total life expectancies
1263: Variance of period (stable) prevalence
1264: end
1265: */
1266:
1.187 brouard 1267: /* #define DEBUG */
1268: /* #define DEBUGBRENT */
1.203 brouard 1269: /* #define DEBUGLINMIN */
1270: /* #define DEBUGHESS */
1271: #define DEBUGHESSIJ
1.224 brouard 1272: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1273: #define POWELL /* Instead of NLOPT */
1.224 brouard 1274: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1275: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1276: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1277: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1278:
1279: #include <math.h>
1280: #include <stdio.h>
1281: #include <stdlib.h>
1282: #include <string.h>
1.226 brouard 1283: #include <ctype.h>
1.159 brouard 1284:
1285: #ifdef _WIN32
1286: #include <io.h>
1.172 brouard 1287: #include <windows.h>
1288: #include <tchar.h>
1.159 brouard 1289: #else
1.126 brouard 1290: #include <unistd.h>
1.159 brouard 1291: #endif
1.126 brouard 1292:
1293: #include <limits.h>
1294: #include <sys/types.h>
1.171 brouard 1295:
1296: #if defined(__GNUC__)
1297: #include <sys/utsname.h> /* Doesn't work on Windows */
1298: #endif
1299:
1.126 brouard 1300: #include <sys/stat.h>
1301: #include <errno.h>
1.159 brouard 1302: /* extern int errno; */
1.126 brouard 1303:
1.157 brouard 1304: /* #ifdef LINUX */
1305: /* #include <time.h> */
1306: /* #include "timeval.h" */
1307: /* #else */
1308: /* #include <sys/time.h> */
1309: /* #endif */
1310:
1.126 brouard 1311: #include <time.h>
1312:
1.136 brouard 1313: #ifdef GSL
1314: #include <gsl/gsl_errno.h>
1315: #include <gsl/gsl_multimin.h>
1316: #endif
1317:
1.167 brouard 1318:
1.162 brouard 1319: #ifdef NLOPT
1320: #include <nlopt.h>
1321: typedef struct {
1322: double (* function)(double [] );
1323: } myfunc_data ;
1324: #endif
1325:
1.126 brouard 1326: /* #include <libintl.h> */
1327: /* #define _(String) gettext (String) */
1328:
1.349 brouard 1329: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1330:
1331: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1332: #define GNUPLOTVERSION 5.1
1333: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1334: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1335: #define FILENAMELENGTH 256
1.126 brouard 1336:
1337: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1338: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1339:
1.349 brouard 1340: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1341: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1342:
1343: #define NINTERVMAX 8
1.144 brouard 1344: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1345: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1346: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1347: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1348: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1349: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1350: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1351: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1352: /* #define AGESUP 130 */
1.288 brouard 1353: /* #define AGESUP 150 */
1354: #define AGESUP 200
1.268 brouard 1355: #define AGEINF 0
1.218 brouard 1356: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1357: #define AGEBASE 40
1.194 brouard 1358: #define AGEOVERFLOW 1.e20
1.164 brouard 1359: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1360: #ifdef _WIN32
1361: #define DIRSEPARATOR '\\'
1362: #define CHARSEPARATOR "\\"
1363: #define ODIRSEPARATOR '/'
1364: #else
1.126 brouard 1365: #define DIRSEPARATOR '/'
1366: #define CHARSEPARATOR "/"
1367: #define ODIRSEPARATOR '\\'
1368: #endif
1369:
1.353 ! brouard 1370: /* $Id: imach.c,v 1.352 2023/04/29 10:46:21 brouard Exp $ */
1.126 brouard 1371: /* $State: Exp $ */
1.196 brouard 1372: #include "version.h"
1373: char version[]=__IMACH_VERSION__;
1.352 brouard 1374: 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";
1.353 ! brouard 1375: char fullversion[]="$Revision: 1.352 $ $Date: 2023/04/29 10:46:21 $";
1.126 brouard 1376: char strstart[80];
1377: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1378: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1379: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1380: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1381: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1382: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1383: 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 1384: 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 1385: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1386: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1387: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1388: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1389: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1390: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1391: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1392: 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 1393: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1394: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1395: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1396: 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 */
1397: 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 */
1398: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1399: 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 1400: int nsd=0; /**< Total number of single dummy variables (output) */
1401: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1402: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1403: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1404: int ntveff=0; /**< ntveff number of effective time varying variables */
1405: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1406: int cptcov=0; /* Working variable */
1.334 brouard 1407: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1408: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1409: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1410: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1411: int nlstate=2; /* Number of live states */
1412: int ndeath=1; /* Number of dead states */
1.130 brouard 1413: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1414: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1415: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1416: int popbased=0;
1417:
1418: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1419: int maxwav=0; /* Maxim number of waves */
1420: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1421: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1422: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1423: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1424: int mle=1, weightopt=0;
1.126 brouard 1425: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1426: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1427: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1428: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1429: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1430: int selected(int kvar); /* Is covariate kvar selected for printing results */
1431:
1.130 brouard 1432: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1433: double **matprod2(); /* test */
1.126 brouard 1434: double **oldm, **newm, **savm; /* Working pointers to matrices */
1435: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1436: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1437:
1.136 brouard 1438: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1439: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1440: FILE *ficlog, *ficrespow;
1.130 brouard 1441: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1442: double fretone; /* Only one call to likelihood */
1.130 brouard 1443: long ipmx=0; /* Number of contributions */
1.126 brouard 1444: double sw; /* Sum of weights */
1445: char filerespow[FILENAMELENGTH];
1446: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1447: FILE *ficresilk;
1448: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1449: FILE *ficresprobmorprev;
1450: FILE *fichtm, *fichtmcov; /* Html File */
1451: FILE *ficreseij;
1452: char filerese[FILENAMELENGTH];
1453: FILE *ficresstdeij;
1454: char fileresstde[FILENAMELENGTH];
1455: FILE *ficrescveij;
1456: char filerescve[FILENAMELENGTH];
1457: FILE *ficresvij;
1458: char fileresv[FILENAMELENGTH];
1.269 brouard 1459:
1.126 brouard 1460: char title[MAXLINE];
1.234 brouard 1461: char model[MAXLINE]; /**< The model line */
1.217 brouard 1462: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1463: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1464: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1465: char command[FILENAMELENGTH];
1466: int outcmd=0;
1467:
1.217 brouard 1468: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1469: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1470: char filelog[FILENAMELENGTH]; /* Log file */
1471: char filerest[FILENAMELENGTH];
1472: char fileregp[FILENAMELENGTH];
1473: char popfile[FILENAMELENGTH];
1474:
1475: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1476:
1.157 brouard 1477: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1478: /* struct timezone tzp; */
1479: /* extern int gettimeofday(); */
1480: struct tm tml, *gmtime(), *localtime();
1481:
1482: extern time_t time();
1483:
1484: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1485: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1486: time_t rlast_btime; /* raw time */
1.157 brouard 1487: struct tm tm;
1488:
1.126 brouard 1489: char strcurr[80], strfor[80];
1490:
1491: char *endptr;
1492: long lval;
1493: double dval;
1494:
1495: #define NR_END 1
1496: #define FREE_ARG char*
1497: #define FTOL 1.0e-10
1498:
1499: #define NRANSI
1.240 brouard 1500: #define ITMAX 200
1501: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1502:
1503: #define TOL 2.0e-4
1504:
1505: #define CGOLD 0.3819660
1506: #define ZEPS 1.0e-10
1507: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1508:
1509: #define GOLD 1.618034
1510: #define GLIMIT 100.0
1511: #define TINY 1.0e-20
1512:
1513: static double maxarg1,maxarg2;
1514: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1515: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1516:
1517: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1518: #define rint(a) floor(a+0.5)
1.166 brouard 1519: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1520: #define mytinydouble 1.0e-16
1.166 brouard 1521: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1522: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1523: /* static double dsqrarg; */
1524: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1525: static double sqrarg;
1526: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1527: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1528: int agegomp= AGEGOMP;
1529:
1530: int imx;
1531: int stepm=1;
1532: /* Stepm, step in month: minimum step interpolation*/
1533:
1534: int estepm;
1535: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1536:
1537: int m,nb;
1538: long *num;
1.197 brouard 1539: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1540: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1541: covariate for which somebody answered excluding
1542: undefined. Usually 2: 0 and 1. */
1543: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1544: covariate for which somebody answered including
1545: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1546: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1547: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1548: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1549: 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 1550: double *ageexmed,*agecens;
1551: double dateintmean=0;
1.296 brouard 1552: double anprojd, mprojd, jprojd; /* For eventual projections */
1553: double anprojf, mprojf, jprojf;
1.126 brouard 1554:
1.296 brouard 1555: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1556: double anbackf, mbackf, jbackf;
1557: double jintmean,mintmean,aintmean;
1.126 brouard 1558: double *weight;
1559: int **s; /* Status */
1.141 brouard 1560: double *agedc;
1.145 brouard 1561: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1562: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1563: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1564: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1565: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1566: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1567: double idx;
1568: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1569: /* Some documentation */
1570: /* Design original data
1571: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1572: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1573: * ntv=3 nqtv=1
1.330 brouard 1574: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1575: * For time varying covariate, quanti or dummies
1576: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1577: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1578: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1579: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1580: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1581: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1582: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1583: * k= 1 2 3 4 5 6 7 8 9 10 11
1584: */
1585: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1586: /* 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
1587: # States 1=Coresidence, 2 Living alone, 3 Institution
1588: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1589: */
1.349 brouard 1590: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1591: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1592: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1593: /* fixed or varying), 1 for age product, 2 for*/
1594: /* product without age, 3 for age and double product */
1595: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1596: /*(single or product without age), 2 dummy*/
1597: /* with age product, 3 quant with age product*/
1598: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1599: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1600: /*TnsdVar[Tvar] 1 2 3 */
1601: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1602: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1603: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1604: /* nsq 1 2 */ /* Counting single quantit tv */
1605: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1606: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1607: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1608: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1609: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1610: /* 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"*/
1611: /* 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}*/
1612: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>}
1613: /* 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}*/
1614: /* 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 1615: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1616: /* 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 1617: /* 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 1618: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1619: /* Type */
1620: /* V 1 2 3 4 5 */
1621: /* F F V V V */
1622: /* D Q D D Q */
1623: /* */
1624: int *TvarsD;
1.330 brouard 1625: int *TnsdVar;
1.234 brouard 1626: int *TvarsDind;
1627: int *TvarsQ;
1628: int *TvarsQind;
1629:
1.318 brouard 1630: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1631: int nresult=0;
1.258 brouard 1632: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1633: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1634: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1635: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1636: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1637: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1638: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1639: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1640: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1641: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1642: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1643:
1644: /* 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
1645: # States 1=Coresidence, 2 Living alone, 3 Institution
1646: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1647: */
1.234 brouard 1648: /* 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 1649: 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 */
1650: 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 */
1651: 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 */
1652: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1653: 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 */
1654: 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 1655: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1656: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1657: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1658: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1659: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1660: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1661: 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 */
1662: 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 1663: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1664: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1665: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1666: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1667: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1668: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1669: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1670: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1671: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1672: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1673: /* 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 1674: int *Tvarsel; /**< Selected covariates for output */
1675: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1676: 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 1677: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1678: 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 1679: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1680: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1681: int *Tage;
1.227 brouard 1682: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1683: 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 1684: 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*/
1685: 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 1686: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1687: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1688: int **Tvard;
1.330 brouard 1689: int **Tvardk;
1.227 brouard 1690: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1691: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1692: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1693: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1694: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1695: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1696: double *lsurv, *lpop, *tpop;
1697:
1.231 brouard 1698: #define FD 1; /* Fixed dummy covariate */
1699: #define FQ 2; /* Fixed quantitative covariate */
1700: #define FP 3; /* Fixed product covariate */
1701: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1702: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1703: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1704: #define VD 10; /* Varying dummy covariate */
1705: #define VQ 11; /* Varying quantitative covariate */
1706: #define VP 12; /* Varying product covariate */
1707: #define VPDD 13; /* Varying product dummy*dummy covariate */
1708: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1709: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1710: #define APFD 16; /* Age product * fixed dummy covariate */
1711: #define APFQ 17; /* Age product * fixed quantitative covariate */
1712: #define APVD 18; /* Age product * varying dummy covariate */
1713: #define APVQ 19; /* Age product * varying quantitative covariate */
1714:
1715: #define FTYPE 1; /* Fixed covariate */
1716: #define VTYPE 2; /* Varying covariate (loop in wave) */
1717: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1718:
1719: struct kmodel{
1720: int maintype; /* main type */
1721: int subtype; /* subtype */
1722: };
1723: struct kmodel modell[NCOVMAX];
1724:
1.143 brouard 1725: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1726: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1727:
1728: /**************** split *************************/
1729: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1730: {
1731: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1732: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1733: */
1734: char *ss; /* pointer */
1.186 brouard 1735: int l1=0, l2=0; /* length counters */
1.126 brouard 1736:
1737: l1 = strlen(path ); /* length of path */
1738: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1739: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1740: if ( ss == NULL ) { /* no directory, so determine current directory */
1741: strcpy( name, path ); /* we got the fullname name because no directory */
1742: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1743: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1744: /* get current working directory */
1745: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1746: #ifdef WIN32
1747: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1748: #else
1749: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1750: #endif
1.126 brouard 1751: return( GLOCK_ERROR_GETCWD );
1752: }
1753: /* got dirc from getcwd*/
1754: printf(" DIRC = %s \n",dirc);
1.205 brouard 1755: } else { /* strip directory from path */
1.126 brouard 1756: ss++; /* after this, the filename */
1757: l2 = strlen( ss ); /* length of filename */
1758: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1759: strcpy( name, ss ); /* save file name */
1760: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1761: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1762: printf(" DIRC2 = %s \n",dirc);
1763: }
1764: /* We add a separator at the end of dirc if not exists */
1765: l1 = strlen( dirc ); /* length of directory */
1766: if( dirc[l1-1] != DIRSEPARATOR ){
1767: dirc[l1] = DIRSEPARATOR;
1768: dirc[l1+1] = 0;
1769: printf(" DIRC3 = %s \n",dirc);
1770: }
1771: ss = strrchr( name, '.' ); /* find last / */
1772: if (ss >0){
1773: ss++;
1774: strcpy(ext,ss); /* save extension */
1775: l1= strlen( name);
1776: l2= strlen(ss)+1;
1777: strncpy( finame, name, l1-l2);
1778: finame[l1-l2]= 0;
1779: }
1780:
1781: return( 0 ); /* we're done */
1782: }
1783:
1784:
1785: /******************************************/
1786:
1787: void replace_back_to_slash(char *s, char*t)
1788: {
1789: int i;
1790: int lg=0;
1791: i=0;
1792: lg=strlen(t);
1793: for(i=0; i<= lg; i++) {
1794: (s[i] = t[i]);
1795: if (t[i]== '\\') s[i]='/';
1796: }
1797: }
1798:
1.132 brouard 1799: char *trimbb(char *out, char *in)
1.137 brouard 1800: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1801: char *s;
1802: s=out;
1803: while (*in != '\0'){
1.137 brouard 1804: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1805: in++;
1806: }
1807: *out++ = *in++;
1808: }
1809: *out='\0';
1810: return s;
1811: }
1812:
1.351 brouard 1813: char *trimbtab(char *out, char *in)
1814: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1815: char *s;
1816: s=out;
1817: while (*in != '\0'){
1818: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1819: in++;
1820: }
1821: *out++ = *in++;
1822: }
1823: *out='\0';
1824: return s;
1825: }
1826:
1.187 brouard 1827: /* char *substrchaine(char *out, char *in, char *chain) */
1828: /* { */
1829: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1830: /* char *s, *t; */
1831: /* t=in;s=out; */
1832: /* while ((*in != *chain) && (*in != '\0')){ */
1833: /* *out++ = *in++; */
1834: /* } */
1835:
1836: /* /\* *in matches *chain *\/ */
1837: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1838: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1839: /* } */
1840: /* in--; chain--; */
1841: /* while ( (*in != '\0')){ */
1842: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1843: /* *out++ = *in++; */
1844: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1845: /* } */
1846: /* *out='\0'; */
1847: /* out=s; */
1848: /* return out; */
1849: /* } */
1850: char *substrchaine(char *out, char *in, char *chain)
1851: {
1852: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1853: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1854:
1855: char *strloc;
1856:
1.349 brouard 1857: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1858: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1859: 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 1860: if(strloc != NULL){
1.349 brouard 1861: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1862: 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)*/
1863: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1864: }
1.349 brouard 1865: 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 1866: return out;
1867: }
1868:
1869:
1.145 brouard 1870: char *cutl(char *blocc, char *alocc, char *in, char occ)
1871: {
1.187 brouard 1872: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1873: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1874: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1875: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1876: */
1.160 brouard 1877: char *s, *t;
1.145 brouard 1878: t=in;s=in;
1879: while ((*in != occ) && (*in != '\0')){
1880: *alocc++ = *in++;
1881: }
1882: if( *in == occ){
1883: *(alocc)='\0';
1884: s=++in;
1885: }
1886:
1887: if (s == t) {/* occ not found */
1888: *(alocc-(in-s))='\0';
1889: in=s;
1890: }
1891: while ( *in != '\0'){
1892: *blocc++ = *in++;
1893: }
1894:
1895: *blocc='\0';
1896: return t;
1897: }
1.137 brouard 1898: char *cutv(char *blocc, char *alocc, char *in, char occ)
1899: {
1.187 brouard 1900: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1901: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1902: gives blocc="abcdef2ghi" and alocc="j".
1903: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1904: */
1905: char *s, *t;
1906: t=in;s=in;
1907: while (*in != '\0'){
1908: while( *in == occ){
1909: *blocc++ = *in++;
1910: s=in;
1911: }
1912: *blocc++ = *in++;
1913: }
1914: if (s == t) /* occ not found */
1915: *(blocc-(in-s))='\0';
1916: else
1917: *(blocc-(in-s)-1)='\0';
1918: in=s;
1919: while ( *in != '\0'){
1920: *alocc++ = *in++;
1921: }
1922:
1923: *alocc='\0';
1924: return s;
1925: }
1926:
1.126 brouard 1927: int nbocc(char *s, char occ)
1928: {
1929: int i,j=0;
1930: int lg=20;
1931: i=0;
1932: lg=strlen(s);
1933: for(i=0; i<= lg; i++) {
1.234 brouard 1934: if (s[i] == occ ) j++;
1.126 brouard 1935: }
1936: return j;
1937: }
1938:
1.349 brouard 1939: int nboccstr(char *textin, char *chain)
1940: {
1941: /* Counts the number of occurence of "chain" in string textin */
1942: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1943: char *strloc;
1944:
1945: int i,j=0;
1946:
1947: i=0;
1948:
1949: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1950: for(;;) {
1951: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1952: if(strloc != NULL){
1953: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1954: j++;
1955: }else
1956: break;
1957: }
1958: return j;
1959:
1960: }
1.137 brouard 1961: /* void cutv(char *u,char *v, char*t, char occ) */
1962: /* { */
1963: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1964: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1965: /* gives u="abcdef2ghi" and v="j" *\/ */
1966: /* int i,lg,j,p=0; */
1967: /* i=0; */
1968: /* lg=strlen(t); */
1969: /* for(j=0; j<=lg-1; j++) { */
1970: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1971: /* } */
1.126 brouard 1972:
1.137 brouard 1973: /* for(j=0; j<p; j++) { */
1974: /* (u[j] = t[j]); */
1975: /* } */
1976: /* u[p]='\0'; */
1.126 brouard 1977:
1.137 brouard 1978: /* for(j=0; j<= lg; j++) { */
1979: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1980: /* } */
1981: /* } */
1.126 brouard 1982:
1.160 brouard 1983: #ifdef _WIN32
1984: char * strsep(char **pp, const char *delim)
1985: {
1986: char *p, *q;
1987:
1988: if ((p = *pp) == NULL)
1989: return 0;
1990: if ((q = strpbrk (p, delim)) != NULL)
1991: {
1992: *pp = q + 1;
1993: *q = '\0';
1994: }
1995: else
1996: *pp = 0;
1997: return p;
1998: }
1999: #endif
2000:
1.126 brouard 2001: /********************** nrerror ********************/
2002:
2003: void nrerror(char error_text[])
2004: {
2005: fprintf(stderr,"ERREUR ...\n");
2006: fprintf(stderr,"%s\n",error_text);
2007: exit(EXIT_FAILURE);
2008: }
2009: /*********************** vector *******************/
2010: double *vector(int nl, int nh)
2011: {
2012: double *v;
2013: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2014: if (!v) nrerror("allocation failure in vector");
2015: return v-nl+NR_END;
2016: }
2017:
2018: /************************ free vector ******************/
2019: void free_vector(double*v, int nl, int nh)
2020: {
2021: free((FREE_ARG)(v+nl-NR_END));
2022: }
2023:
2024: /************************ivector *******************************/
2025: int *ivector(long nl,long nh)
2026: {
2027: int *v;
2028: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2029: if (!v) nrerror("allocation failure in ivector");
2030: return v-nl+NR_END;
2031: }
2032:
2033: /******************free ivector **************************/
2034: void free_ivector(int *v, long nl, long nh)
2035: {
2036: free((FREE_ARG)(v+nl-NR_END));
2037: }
2038:
2039: /************************lvector *******************************/
2040: long *lvector(long nl,long nh)
2041: {
2042: long *v;
2043: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2044: if (!v) nrerror("allocation failure in ivector");
2045: return v-nl+NR_END;
2046: }
2047:
2048: /******************free lvector **************************/
2049: void free_lvector(long *v, long nl, long nh)
2050: {
2051: free((FREE_ARG)(v+nl-NR_END));
2052: }
2053:
2054: /******************* imatrix *******************************/
2055: int **imatrix(long nrl, long nrh, long ncl, long nch)
2056: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2057: {
2058: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2059: int **m;
2060:
2061: /* allocate pointers to rows */
2062: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2063: if (!m) nrerror("allocation failure 1 in matrix()");
2064: m += NR_END;
2065: m -= nrl;
2066:
2067:
2068: /* allocate rows and set pointers to them */
2069: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2070: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2071: m[nrl] += NR_END;
2072: m[nrl] -= ncl;
2073:
2074: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2075:
2076: /* return pointer to array of pointers to rows */
2077: return m;
2078: }
2079:
2080: /****************** free_imatrix *************************/
2081: void free_imatrix(m,nrl,nrh,ncl,nch)
2082: int **m;
2083: long nch,ncl,nrh,nrl;
2084: /* free an int matrix allocated by imatrix() */
2085: {
2086: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2087: free((FREE_ARG) (m+nrl-NR_END));
2088: }
2089:
2090: /******************* matrix *******************************/
2091: double **matrix(long nrl, long nrh, long ncl, long nch)
2092: {
2093: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2094: double **m;
2095:
2096: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2097: if (!m) nrerror("allocation failure 1 in matrix()");
2098: m += NR_END;
2099: m -= nrl;
2100:
2101: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2102: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2103: m[nrl] += NR_END;
2104: m[nrl] -= ncl;
2105:
2106: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2107: return m;
1.145 brouard 2108: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2109: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2110: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2111: */
2112: }
2113:
2114: /*************************free matrix ************************/
2115: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2116: {
2117: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2118: free((FREE_ARG)(m+nrl-NR_END));
2119: }
2120:
2121: /******************* ma3x *******************************/
2122: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2123: {
2124: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2125: double ***m;
2126:
2127: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2128: if (!m) nrerror("allocation failure 1 in matrix()");
2129: m += NR_END;
2130: m -= nrl;
2131:
2132: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2133: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2134: m[nrl] += NR_END;
2135: m[nrl] -= ncl;
2136:
2137: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2138:
2139: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2140: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2141: m[nrl][ncl] += NR_END;
2142: m[nrl][ncl] -= nll;
2143: for (j=ncl+1; j<=nch; j++)
2144: m[nrl][j]=m[nrl][j-1]+nlay;
2145:
2146: for (i=nrl+1; i<=nrh; i++) {
2147: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2148: for (j=ncl+1; j<=nch; j++)
2149: m[i][j]=m[i][j-1]+nlay;
2150: }
2151: return m;
2152: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2153: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2154: */
2155: }
2156:
2157: /*************************free ma3x ************************/
2158: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2159: {
2160: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2161: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2162: free((FREE_ARG)(m+nrl-NR_END));
2163: }
2164:
2165: /*************** function subdirf ***********/
2166: char *subdirf(char fileres[])
2167: {
2168: /* Caution optionfilefiname is hidden */
2169: strcpy(tmpout,optionfilefiname);
2170: strcat(tmpout,"/"); /* Add to the right */
2171: strcat(tmpout,fileres);
2172: return tmpout;
2173: }
2174:
2175: /*************** function subdirf2 ***********/
2176: char *subdirf2(char fileres[], char *preop)
2177: {
1.314 brouard 2178: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2179: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2180: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2181: /* Caution optionfilefiname is hidden */
2182: strcpy(tmpout,optionfilefiname);
2183: strcat(tmpout,"/");
2184: strcat(tmpout,preop);
2185: strcat(tmpout,fileres);
2186: return tmpout;
2187: }
2188:
2189: /*************** function subdirf3 ***********/
2190: char *subdirf3(char fileres[], char *preop, char *preop2)
2191: {
2192:
2193: /* Caution optionfilefiname is hidden */
2194: strcpy(tmpout,optionfilefiname);
2195: strcat(tmpout,"/");
2196: strcat(tmpout,preop);
2197: strcat(tmpout,preop2);
2198: strcat(tmpout,fileres);
2199: return tmpout;
2200: }
1.213 brouard 2201:
2202: /*************** function subdirfext ***********/
2203: char *subdirfext(char fileres[], char *preop, char *postop)
2204: {
2205:
2206: strcpy(tmpout,preop);
2207: strcat(tmpout,fileres);
2208: strcat(tmpout,postop);
2209: return tmpout;
2210: }
1.126 brouard 2211:
1.213 brouard 2212: /*************** function subdirfext3 ***********/
2213: char *subdirfext3(char fileres[], char *preop, char *postop)
2214: {
2215:
2216: /* Caution optionfilefiname is hidden */
2217: strcpy(tmpout,optionfilefiname);
2218: strcat(tmpout,"/");
2219: strcat(tmpout,preop);
2220: strcat(tmpout,fileres);
2221: strcat(tmpout,postop);
2222: return tmpout;
2223: }
2224:
1.162 brouard 2225: char *asc_diff_time(long time_sec, char ascdiff[])
2226: {
2227: long sec_left, days, hours, minutes;
2228: days = (time_sec) / (60*60*24);
2229: sec_left = (time_sec) % (60*60*24);
2230: hours = (sec_left) / (60*60) ;
2231: sec_left = (sec_left) %(60*60);
2232: minutes = (sec_left) /60;
2233: sec_left = (sec_left) % (60);
2234: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2235: return ascdiff;
2236: }
2237:
1.126 brouard 2238: /***************** f1dim *************************/
2239: extern int ncom;
2240: extern double *pcom,*xicom;
2241: extern double (*nrfunc)(double []);
2242:
2243: double f1dim(double x)
2244: {
2245: int j;
2246: double f;
2247: double *xt;
2248:
2249: xt=vector(1,ncom);
2250: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2251: f=(*nrfunc)(xt);
2252: free_vector(xt,1,ncom);
2253: return f;
2254: }
2255:
2256: /*****************brent *************************/
2257: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2258: {
2259: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2260: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2261: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2262: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2263: * returned function value.
2264: */
1.126 brouard 2265: int iter;
2266: double a,b,d,etemp;
1.159 brouard 2267: double fu=0,fv,fw,fx;
1.164 brouard 2268: double ftemp=0.;
1.126 brouard 2269: double p,q,r,tol1,tol2,u,v,w,x,xm;
2270: double e=0.0;
2271:
2272: a=(ax < cx ? ax : cx);
2273: b=(ax > cx ? ax : cx);
2274: x=w=v=bx;
2275: fw=fv=fx=(*f)(x);
2276: for (iter=1;iter<=ITMAX;iter++) {
2277: xm=0.5*(a+b);
2278: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2279: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2280: printf(".");fflush(stdout);
2281: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2282: #ifdef DEBUGBRENT
1.126 brouard 2283: 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);
2284: 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);
2285: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2286: #endif
2287: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2288: *xmin=x;
2289: return fx;
2290: }
2291: ftemp=fu;
2292: if (fabs(e) > tol1) {
2293: r=(x-w)*(fx-fv);
2294: q=(x-v)*(fx-fw);
2295: p=(x-v)*q-(x-w)*r;
2296: q=2.0*(q-r);
2297: if (q > 0.0) p = -p;
2298: q=fabs(q);
2299: etemp=e;
2300: e=d;
2301: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2302: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2303: else {
1.224 brouard 2304: d=p/q;
2305: u=x+d;
2306: if (u-a < tol2 || b-u < tol2)
2307: d=SIGN(tol1,xm-x);
1.126 brouard 2308: }
2309: } else {
2310: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2311: }
2312: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2313: fu=(*f)(u);
2314: if (fu <= fx) {
2315: if (u >= x) a=x; else b=x;
2316: SHFT(v,w,x,u)
1.183 brouard 2317: SHFT(fv,fw,fx,fu)
2318: } else {
2319: if (u < x) a=u; else b=u;
2320: if (fu <= fw || w == x) {
1.224 brouard 2321: v=w;
2322: w=u;
2323: fv=fw;
2324: fw=fu;
1.183 brouard 2325: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2326: v=u;
2327: fv=fu;
1.183 brouard 2328: }
2329: }
1.126 brouard 2330: }
2331: nrerror("Too many iterations in brent");
2332: *xmin=x;
2333: return fx;
2334: }
2335:
2336: /****************** mnbrak ***********************/
2337:
2338: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2339: double (*func)(double))
1.183 brouard 2340: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2341: the downhill direction (defined by the function as evaluated at the initial points) and returns
2342: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2343: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2344: */
1.126 brouard 2345: double ulim,u,r,q, dum;
2346: double fu;
1.187 brouard 2347:
2348: double scale=10.;
2349: int iterscale=0;
2350:
2351: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2352: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2353:
2354:
2355: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2356: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2357: /* *bx = *ax - (*ax - *bx)/scale; */
2358: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2359: /* } */
2360:
1.126 brouard 2361: if (*fb > *fa) {
2362: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2363: SHFT(dum,*fb,*fa,dum)
2364: }
1.126 brouard 2365: *cx=(*bx)+GOLD*(*bx-*ax);
2366: *fc=(*func)(*cx);
1.183 brouard 2367: #ifdef DEBUG
1.224 brouard 2368: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2369: 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 2370: #endif
1.224 brouard 2371: 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 2372: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2373: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2374: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2375: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2376: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2377: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2378: fu=(*func)(u);
1.163 brouard 2379: #ifdef DEBUG
2380: /* f(x)=A(x-u)**2+f(u) */
2381: double A, fparabu;
2382: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2383: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2384: 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);
2385: 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 2386: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2387: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2388: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2389: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2390: #endif
1.184 brouard 2391: #ifdef MNBRAKORIGINAL
1.183 brouard 2392: #else
1.191 brouard 2393: /* if (fu > *fc) { */
2394: /* #ifdef DEBUG */
2395: /* printf("mnbrak4 fu > fc \n"); */
2396: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2397: /* #endif */
2398: /* /\* 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 *\\/ *\/ */
2399: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2400: /* dum=u; /\* Shifting c and u *\/ */
2401: /* u = *cx; */
2402: /* *cx = dum; */
2403: /* dum = fu; */
2404: /* fu = *fc; */
2405: /* *fc =dum; */
2406: /* } else { /\* end *\/ */
2407: /* #ifdef DEBUG */
2408: /* printf("mnbrak3 fu < fc \n"); */
2409: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2410: /* #endif */
2411: /* dum=u; /\* Shifting c and u *\/ */
2412: /* u = *cx; */
2413: /* *cx = dum; */
2414: /* dum = fu; */
2415: /* fu = *fc; */
2416: /* *fc =dum; */
2417: /* } */
1.224 brouard 2418: #ifdef DEBUGMNBRAK
2419: double A, fparabu;
2420: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2421: fparabu= *fa - A*(*ax-u)*(*ax-u);
2422: 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);
2423: 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 2424: #endif
1.191 brouard 2425: dum=u; /* Shifting c and u */
2426: u = *cx;
2427: *cx = dum;
2428: dum = fu;
2429: fu = *fc;
2430: *fc =dum;
1.183 brouard 2431: #endif
1.162 brouard 2432: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2433: #ifdef DEBUG
1.224 brouard 2434: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2435: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2436: #endif
1.126 brouard 2437: fu=(*func)(u);
2438: if (fu < *fc) {
1.183 brouard 2439: #ifdef DEBUG
1.224 brouard 2440: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2441: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2442: #endif
2443: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2444: SHFT(*fb,*fc,fu,(*func)(u))
2445: #ifdef DEBUG
2446: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2447: #endif
2448: }
1.162 brouard 2449: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2450: #ifdef DEBUG
1.224 brouard 2451: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2452: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2453: #endif
1.126 brouard 2454: u=ulim;
2455: fu=(*func)(u);
1.183 brouard 2456: } else { /* u could be left to b (if r > q parabola has a maximum) */
2457: #ifdef DEBUG
1.224 brouard 2458: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2459: 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 2460: #endif
1.126 brouard 2461: u=(*cx)+GOLD*(*cx-*bx);
2462: fu=(*func)(u);
1.224 brouard 2463: #ifdef DEBUG
2464: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2465: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2466: #endif
1.183 brouard 2467: } /* end tests */
1.126 brouard 2468: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2469: SHFT(*fa,*fb,*fc,fu)
2470: #ifdef DEBUG
1.224 brouard 2471: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2472: 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 2473: #endif
2474: } /* 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 2475: }
2476:
2477: /*************** linmin ************************/
1.162 brouard 2478: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2479: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2480: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2481: the value of func at the returned location p . This is actually all accomplished by calling the
2482: routines mnbrak and brent .*/
1.126 brouard 2483: int ncom;
2484: double *pcom,*xicom;
2485: double (*nrfunc)(double []);
2486:
1.224 brouard 2487: #ifdef LINMINORIGINAL
1.126 brouard 2488: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2489: #else
2490: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2491: #endif
1.126 brouard 2492: {
2493: double brent(double ax, double bx, double cx,
2494: double (*f)(double), double tol, double *xmin);
2495: double f1dim(double x);
2496: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2497: double *fc, double (*func)(double));
2498: int j;
2499: double xx,xmin,bx,ax;
2500: double fx,fb,fa;
1.187 brouard 2501:
1.203 brouard 2502: #ifdef LINMINORIGINAL
2503: #else
2504: double scale=10., axs, xxs; /* Scale added for infinity */
2505: #endif
2506:
1.126 brouard 2507: ncom=n;
2508: pcom=vector(1,n);
2509: xicom=vector(1,n);
2510: nrfunc=func;
2511: for (j=1;j<=n;j++) {
2512: pcom[j]=p[j];
1.202 brouard 2513: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2514: }
1.187 brouard 2515:
1.203 brouard 2516: #ifdef LINMINORIGINAL
2517: xx=1.;
2518: #else
2519: axs=0.0;
2520: xxs=1.;
2521: do{
2522: xx= xxs;
2523: #endif
1.187 brouard 2524: ax=0.;
2525: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2526: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2527: /* 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)) */
2528: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2529: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2530: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2531: /* 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 2532: #ifdef LINMINORIGINAL
2533: #else
2534: if (fx != fx){
1.224 brouard 2535: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2536: printf("|");
2537: fprintf(ficlog,"|");
1.203 brouard 2538: #ifdef DEBUGLINMIN
1.224 brouard 2539: 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 2540: #endif
2541: }
1.224 brouard 2542: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2543: #endif
2544:
1.191 brouard 2545: #ifdef DEBUGLINMIN
2546: 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 2547: 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 2548: #endif
1.224 brouard 2549: #ifdef LINMINORIGINAL
2550: #else
1.317 brouard 2551: if(fb == fx){ /* Flat function in the direction */
2552: xmin=xx;
1.224 brouard 2553: *flat=1;
1.317 brouard 2554: }else{
1.224 brouard 2555: *flat=0;
2556: #endif
2557: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2558: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2559: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2560: /* fmin = f(p[j] + xmin * xi[j]) */
2561: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2562: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2563: #ifdef DEBUG
1.224 brouard 2564: 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);
2565: 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);
2566: #endif
2567: #ifdef LINMINORIGINAL
2568: #else
2569: }
1.126 brouard 2570: #endif
1.191 brouard 2571: #ifdef DEBUGLINMIN
2572: printf("linmin end ");
1.202 brouard 2573: fprintf(ficlog,"linmin end ");
1.191 brouard 2574: #endif
1.126 brouard 2575: for (j=1;j<=n;j++) {
1.203 brouard 2576: #ifdef LINMINORIGINAL
2577: xi[j] *= xmin;
2578: #else
2579: #ifdef DEBUGLINMIN
2580: if(xxs <1.0)
2581: printf(" before xi[%d]=%12.8f", j,xi[j]);
2582: #endif
2583: 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) */
2584: #ifdef DEBUGLINMIN
2585: if(xxs <1.0)
2586: 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 );
2587: #endif
2588: #endif
1.187 brouard 2589: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2590: }
1.191 brouard 2591: #ifdef DEBUGLINMIN
1.203 brouard 2592: printf("\n");
1.191 brouard 2593: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2594: 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 2595: for (j=1;j<=n;j++) {
1.202 brouard 2596: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2597: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2598: if(j % ncovmodel == 0){
1.191 brouard 2599: printf("\n");
1.202 brouard 2600: fprintf(ficlog,"\n");
2601: }
1.191 brouard 2602: }
1.203 brouard 2603: #else
1.191 brouard 2604: #endif
1.126 brouard 2605: free_vector(xicom,1,n);
2606: free_vector(pcom,1,n);
2607: }
2608:
2609:
2610: /*************** powell ************************/
1.162 brouard 2611: /*
1.317 brouard 2612: Minimization of a function func of n variables. Input consists in an initial starting point
2613: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2614: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2615: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2616: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2617: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2618: */
1.224 brouard 2619: #ifdef LINMINORIGINAL
2620: #else
2621: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2622: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2623: #endif
1.126 brouard 2624: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2625: double (*func)(double []))
2626: {
1.224 brouard 2627: #ifdef LINMINORIGINAL
2628: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2629: double (*func)(double []));
1.224 brouard 2630: #else
1.241 brouard 2631: void linmin(double p[], double xi[], int n, double *fret,
2632: double (*func)(double []),int *flat);
1.224 brouard 2633: #endif
1.239 brouard 2634: int i,ibig,j,jk,k;
1.126 brouard 2635: double del,t,*pt,*ptt,*xit;
1.181 brouard 2636: double directest;
1.126 brouard 2637: double fp,fptt;
2638: double *xits;
2639: int niterf, itmp;
1.349 brouard 2640: int Bigter=0, nBigterf=1;
2641:
1.126 brouard 2642: pt=vector(1,n);
2643: ptt=vector(1,n);
2644: xit=vector(1,n);
2645: xits=vector(1,n);
2646: *fret=(*func)(p);
2647: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2648: rcurr_time = time(NULL);
2649: fp=(*fret); /* Initialisation */
1.126 brouard 2650: for (*iter=1;;++(*iter)) {
2651: ibig=0;
2652: del=0.0;
1.157 brouard 2653: rlast_time=rcurr_time;
1.349 brouard 2654: rlast_btime=rcurr_time;
1.157 brouard 2655: /* (void) gettimeofday(&curr_time,&tzp); */
2656: rcurr_time = time(NULL);
2657: curr_time = *localtime(&rcurr_time);
1.337 brouard 2658: /* 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); */
2659: /* 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 2660: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
2661: 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);
2662: 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);
2663: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2664: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2665: for (i=1;i<=n;i++) {
1.126 brouard 2666: fprintf(ficrespow," %.12lf", p[i]);
2667: }
1.239 brouard 2668: fprintf(ficrespow,"\n");fflush(ficrespow);
2669: printf("\n#model= 1 + age ");
2670: fprintf(ficlog,"\n#model= 1 + age ");
2671: if(nagesqr==1){
1.241 brouard 2672: printf(" + age*age ");
2673: fprintf(ficlog," + age*age ");
1.239 brouard 2674: }
2675: for(j=1;j <=ncovmodel-2;j++){
2676: if(Typevar[j]==0) {
2677: printf(" + V%d ",Tvar[j]);
2678: fprintf(ficlog," + V%d ",Tvar[j]);
2679: }else if(Typevar[j]==1) {
2680: printf(" + V%d*age ",Tvar[j]);
2681: fprintf(ficlog," + V%d*age ",Tvar[j]);
2682: }else if(Typevar[j]==2) {
2683: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2684: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 2685: }else if(Typevar[j]==3) {
2686: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2687: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2688: }
2689: }
1.126 brouard 2690: printf("\n");
1.239 brouard 2691: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2692: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2693: fprintf(ficlog,"\n");
1.239 brouard 2694: for(i=1,jk=1; i <=nlstate; i++){
2695: for(k=1; k <=(nlstate+ndeath); k++){
2696: if (k != i) {
2697: printf("%d%d ",i,k);
2698: fprintf(ficlog,"%d%d ",i,k);
2699: for(j=1; j <=ncovmodel; j++){
2700: printf("%12.7f ",p[jk]);
2701: fprintf(ficlog,"%12.7f ",p[jk]);
2702: jk++;
2703: }
2704: printf("\n");
2705: fprintf(ficlog,"\n");
2706: }
2707: }
2708: }
1.241 brouard 2709: if(*iter <=3 && *iter >1){
1.157 brouard 2710: tml = *localtime(&rcurr_time);
2711: strcpy(strcurr,asctime(&tml));
2712: rforecast_time=rcurr_time;
1.126 brouard 2713: itmp = strlen(strcurr);
2714: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2715: strcurr[itmp-1]='\0';
1.162 brouard 2716: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2717: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 2718: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
2719: niterf=nBigterf*ncovmodel;
2720: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2721: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2722: forecast_time = *localtime(&rforecast_time);
2723: strcpy(strfor,asctime(&forecast_time));
2724: itmp = strlen(strfor);
2725: if(strfor[itmp-1]=='\n')
2726: strfor[itmp-1]='\0';
1.349 brouard 2727: 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);
2728: 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 2729: }
2730: }
1.187 brouard 2731: for (i=1;i<=n;i++) { /* For each direction i */
2732: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2733: fptt=(*fret);
2734: #ifdef DEBUG
1.203 brouard 2735: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2736: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2737: #endif
1.203 brouard 2738: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2739: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2740: #ifdef LINMINORIGINAL
1.188 brouard 2741: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2742: #else
2743: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2744: flatdir[i]=flat; /* Function is vanishing in that direction i */
2745: #endif
2746: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2747: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2748: /* because that direction will be replaced unless the gain del is small */
2749: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2750: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2751: /* with the new direction. */
2752: del=fabs(fptt-(*fret));
2753: ibig=i;
1.126 brouard 2754: }
2755: #ifdef DEBUG
2756: printf("%d %.12e",i,(*fret));
2757: fprintf(ficlog,"%d %.12e",i,(*fret));
2758: for (j=1;j<=n;j++) {
1.224 brouard 2759: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2760: printf(" x(%d)=%.12e",j,xit[j]);
2761: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2762: }
2763: for(j=1;j<=n;j++) {
1.225 brouard 2764: printf(" p(%d)=%.12e",j,p[j]);
2765: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2766: }
2767: printf("\n");
2768: fprintf(ficlog,"\n");
2769: #endif
1.187 brouard 2770: } /* end loop on each direction i */
2771: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2772: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2773: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2774: for(j=1;j<=n;j++) {
2775: if(flatdir[j] >0){
2776: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2777: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2778: }
1.319 brouard 2779: /* printf("\n"); */
2780: /* fprintf(ficlog,"\n"); */
2781: }
1.243 brouard 2782: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2783: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2784: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2785: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2786: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2787: /* decreased of more than 3.84 */
2788: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2789: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2790: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2791:
1.188 brouard 2792: /* Starting the program with initial values given by a former maximization will simply change */
2793: /* the scales of the directions and the directions, because the are reset to canonical directions */
2794: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2795: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2796: #ifdef DEBUG
2797: int k[2],l;
2798: k[0]=1;
2799: k[1]=-1;
2800: printf("Max: %.12e",(*func)(p));
2801: fprintf(ficlog,"Max: %.12e",(*func)(p));
2802: for (j=1;j<=n;j++) {
2803: printf(" %.12e",p[j]);
2804: fprintf(ficlog," %.12e",p[j]);
2805: }
2806: printf("\n");
2807: fprintf(ficlog,"\n");
2808: for(l=0;l<=1;l++) {
2809: for (j=1;j<=n;j++) {
2810: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2811: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2812: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2813: }
2814: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2815: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2816: }
2817: #endif
2818:
2819: free_vector(xit,1,n);
2820: free_vector(xits,1,n);
2821: free_vector(ptt,1,n);
2822: free_vector(pt,1,n);
2823: return;
1.192 brouard 2824: } /* enough precision */
1.240 brouard 2825: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2826: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2827: ptt[j]=2.0*p[j]-pt[j];
2828: xit[j]=p[j]-pt[j];
2829: pt[j]=p[j];
2830: }
1.181 brouard 2831: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2832: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2833: if (*iter <=4) {
1.225 brouard 2834: #else
2835: #endif
1.224 brouard 2836: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2837: #else
1.161 brouard 2838: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2839: #endif
1.162 brouard 2840: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2841: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2842: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2843: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2844: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2845: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2846: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2847: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2848: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2849: /* Even if f3 <f1, directest can be negative and t >0 */
2850: /* mu² and del² are equal when f3=f1 */
2851: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2852: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2853: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2854: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2855: #ifdef NRCORIGINAL
2856: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2857: #else
2858: 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 2859: t= t- del*SQR(fp-fptt);
1.183 brouard 2860: #endif
1.202 brouard 2861: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2862: #ifdef DEBUG
1.181 brouard 2863: 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);
2864: 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 2865: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2866: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2867: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2868: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2869: 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);
2870: 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);
2871: #endif
1.183 brouard 2872: #ifdef POWELLORIGINAL
2873: if (t < 0.0) { /* Then we use it for new direction */
2874: #else
1.182 brouard 2875: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2876: 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 2877: 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 2878: 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 2879: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2880: }
1.181 brouard 2881: if (directest < 0.0) { /* Then we use it for new direction */
2882: #endif
1.191 brouard 2883: #ifdef DEBUGLINMIN
1.234 brouard 2884: printf("Before linmin in direction P%d-P0\n",n);
2885: for (j=1;j<=n;j++) {
2886: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2887: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2888: if(j % ncovmodel == 0){
2889: printf("\n");
2890: fprintf(ficlog,"\n");
2891: }
2892: }
1.224 brouard 2893: #endif
2894: #ifdef LINMINORIGINAL
1.234 brouard 2895: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2896: #else
1.234 brouard 2897: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2898: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2899: #endif
1.234 brouard 2900:
1.191 brouard 2901: #ifdef DEBUGLINMIN
1.234 brouard 2902: for (j=1;j<=n;j++) {
2903: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2904: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2905: if(j % ncovmodel == 0){
2906: printf("\n");
2907: fprintf(ficlog,"\n");
2908: }
2909: }
1.224 brouard 2910: #endif
1.234 brouard 2911: for (j=1;j<=n;j++) {
2912: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2913: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2914: }
1.224 brouard 2915: #ifdef LINMINORIGINAL
2916: #else
1.234 brouard 2917: for (j=1, flatd=0;j<=n;j++) {
2918: if(flatdir[j]>0)
2919: flatd++;
2920: }
2921: if(flatd >0){
1.255 brouard 2922: printf("%d flat directions: ",flatd);
2923: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2924: for (j=1;j<=n;j++) {
2925: if(flatdir[j]>0){
2926: printf("%d ",j);
2927: fprintf(ficlog,"%d ",j);
2928: }
2929: }
2930: printf("\n");
2931: fprintf(ficlog,"\n");
1.319 brouard 2932: #ifdef FLATSUP
2933: free_vector(xit,1,n);
2934: free_vector(xits,1,n);
2935: free_vector(ptt,1,n);
2936: free_vector(pt,1,n);
2937: return;
2938: #endif
1.234 brouard 2939: }
1.191 brouard 2940: #endif
1.234 brouard 2941: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2942: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2943:
1.126 brouard 2944: #ifdef DEBUG
1.234 brouard 2945: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2946: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2947: for(j=1;j<=n;j++){
2948: printf(" %lf",xit[j]);
2949: fprintf(ficlog," %lf",xit[j]);
2950: }
2951: printf("\n");
2952: fprintf(ficlog,"\n");
1.126 brouard 2953: #endif
1.192 brouard 2954: } /* end of t or directest negative */
1.224 brouard 2955: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2956: #else
1.234 brouard 2957: } /* end if (fptt < fp) */
1.192 brouard 2958: #endif
1.225 brouard 2959: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2960: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2961: #else
1.224 brouard 2962: #endif
1.234 brouard 2963: } /* loop iteration */
1.126 brouard 2964: }
1.234 brouard 2965:
1.126 brouard 2966: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2967:
1.235 brouard 2968: 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 2969: {
1.338 brouard 2970: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2971: * (and selected quantitative values in nres)
2972: * by left multiplying the unit
2973: * matrix by transitions matrix until convergence is reached with precision ftolpl
2974: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2975: * Wx is row vector: population in state 1, population in state 2, population dead
2976: * or prevalence in state 1, prevalence in state 2, 0
2977: * newm is the matrix after multiplications, its rows are identical at a factor.
2978: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2979: * Output is prlim.
2980: * Initial matrix pimij
2981: */
1.206 brouard 2982: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2983: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2984: /* 0, 0 , 1} */
2985: /*
2986: * and after some iteration: */
2987: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2988: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2989: /* 0, 0 , 1} */
2990: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2991: /* {0.51571254859325999, 0.4842874514067399, */
2992: /* 0.51326036147820708, 0.48673963852179264} */
2993: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2994:
1.332 brouard 2995: int i, ii,j,k, k1;
1.209 brouard 2996: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2997: /* double **matprod2(); */ /* test */
1.218 brouard 2998: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2999: double **newm;
1.209 brouard 3000: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 3001: int ncvloop=0;
1.288 brouard 3002: int first=0;
1.169 brouard 3003:
1.209 brouard 3004: min=vector(1,nlstate);
3005: max=vector(1,nlstate);
3006: meandiff=vector(1,nlstate);
3007:
1.218 brouard 3008: /* Starting with matrix unity */
1.126 brouard 3009: for (ii=1;ii<=nlstate+ndeath;ii++)
3010: for (j=1;j<=nlstate+ndeath;j++){
3011: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3012: }
1.169 brouard 3013:
3014: cov[1]=1.;
3015:
3016: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 3017: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 3018: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 3019: ncvloop++;
1.126 brouard 3020: newm=savm;
3021: /* Covariates have to be included here again */
1.138 brouard 3022: cov[2]=agefin;
1.319 brouard 3023: if(nagesqr==1){
3024: cov[3]= agefin*agefin;
3025: }
1.332 brouard 3026: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3027: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3028: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3029: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3030: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3031: }else{
3032: cov[2+nagesqr+k1]=precov[nres][k1];
3033: }
3034: }/* End of loop on model equation */
3035:
3036: /* Start of old code (replaced by a loop on position in the model equation */
3037: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3038: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3039: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3040: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3041: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3042: /* * k 1 2 3 4 5 6 7 8 */
3043: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3044: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3045: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3046: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3047: /* *nsd=3 (1) (2) (3) */
3048: /* *TvarsD[nsd] [1]=2 1 3 */
3049: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3050: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3051: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3052: /* *Tvard[] [1][1]=1 [2][1]=1 */
3053: /* * [1][2]=3 [2][2]=2 */
3054: /* *Tprod[](=k) [1]=1 [2]=8 */
3055: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3056: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3057: /* *TvarsDpType */
3058: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3059: /* * nsd=1 (1) (2) */
3060: /* *TvarsD[nsd] 3 2 */
3061: /* *TnsdVar (3)=1 (2)=2 */
3062: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3063: /* *Tage[] [1]=2 [2]= 3 */
3064: /* *\/ */
3065: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3066: /* /\* 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)); *\/ */
3067: /* } */
3068: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3069: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3070: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3071: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3072: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3073: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3074: /* /\* 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]); *\/ */
3075: /* } */
3076: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3077: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3078: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3079: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3080: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3081: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3082: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3083: /* } */
3084: /* /\* 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]); *\/ */
3085: /* } */
3086: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3087: /* /\* 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]); *\/ */
3088: /* if(Dummy[Tvard[k][1]]==0){ */
3089: /* if(Dummy[Tvard[k][2]]==0){ */
3090: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3091: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3092: /* }else{ */
3093: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3094: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3095: /* } */
3096: /* }else{ */
3097: /* if(Dummy[Tvard[k][2]]==0){ */
3098: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3099: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3100: /* }else{ */
3101: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3102: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3103: /* } */
3104: /* } */
3105: /* } /\* End product without age *\/ */
3106: /* ENd of old code */
1.138 brouard 3107: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3108: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3109: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3110: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3111: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3112: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3113: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3114:
1.126 brouard 3115: savm=oldm;
3116: oldm=newm;
1.209 brouard 3117:
3118: for(j=1; j<=nlstate; j++){
3119: max[j]=0.;
3120: min[j]=1.;
3121: }
3122: for(i=1;i<=nlstate;i++){
3123: sumnew=0;
3124: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3125: for(j=1; j<=nlstate; j++){
3126: prlim[i][j]= newm[i][j]/(1-sumnew);
3127: max[j]=FMAX(max[j],prlim[i][j]);
3128: min[j]=FMIN(min[j],prlim[i][j]);
3129: }
3130: }
3131:
1.126 brouard 3132: maxmax=0.;
1.209 brouard 3133: for(j=1; j<=nlstate; j++){
3134: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3135: maxmax=FMAX(maxmax,meandiff[j]);
3136: /* 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 3137: } /* j loop */
1.203 brouard 3138: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3139: /* 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 3140: if(maxmax < ftolpl){
1.209 brouard 3141: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3142: free_vector(min,1,nlstate);
3143: free_vector(max,1,nlstate);
3144: free_vector(meandiff,1,nlstate);
1.126 brouard 3145: return prlim;
3146: }
1.288 brouard 3147: } /* agefin loop */
1.208 brouard 3148: /* After some age loop it doesn't converge */
1.288 brouard 3149: if(!first){
3150: first=1;
3151: 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 3152: 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);
3153: }else if (first >=1 && first <10){
3154: 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);
3155: first++;
3156: }else if (first ==10){
3157: 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);
3158: 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");
3159: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3160: first++;
1.288 brouard 3161: }
3162:
1.209 brouard 3163: /* 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); */
3164: free_vector(min,1,nlstate);
3165: free_vector(max,1,nlstate);
3166: free_vector(meandiff,1,nlstate);
1.208 brouard 3167:
1.169 brouard 3168: return prlim; /* should not reach here */
1.126 brouard 3169: }
3170:
1.217 brouard 3171:
3172: /**** Back Prevalence limit (stable or period prevalence) ****************/
3173:
1.218 brouard 3174: /* 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) */
3175: /* 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 3176: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3177: {
1.264 brouard 3178: /* 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 3179: matrix by transitions matrix until convergence is reached with precision ftolpl */
3180: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3181: /* Wx is row vector: population in state 1, population in state 2, population dead */
3182: /* or prevalence in state 1, prevalence in state 2, 0 */
3183: /* newm is the matrix after multiplications, its rows are identical at a factor */
3184: /* Initial matrix pimij */
3185: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3186: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3187: /* 0, 0 , 1} */
3188: /*
3189: * and after some iteration: */
3190: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3191: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3192: /* 0, 0 , 1} */
3193: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3194: /* {0.51571254859325999, 0.4842874514067399, */
3195: /* 0.51326036147820708, 0.48673963852179264} */
3196: /* If we start from prlim again, prlim tends to a constant matrix */
3197:
1.332 brouard 3198: int i, ii,j,k, k1;
1.247 brouard 3199: int first=0;
1.217 brouard 3200: double *min, *max, *meandiff, maxmax,sumnew=0.;
3201: /* double **matprod2(); */ /* test */
3202: double **out, cov[NCOVMAX+1], **bmij();
3203: double **newm;
1.218 brouard 3204: double **dnewm, **doldm, **dsavm; /* for use */
3205: double **oldm, **savm; /* for use */
3206:
1.217 brouard 3207: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3208: int ncvloop=0;
3209:
3210: min=vector(1,nlstate);
3211: max=vector(1,nlstate);
3212: meandiff=vector(1,nlstate);
3213:
1.266 brouard 3214: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3215: oldm=oldms; savm=savms;
3216:
3217: /* Starting with matrix unity */
3218: for (ii=1;ii<=nlstate+ndeath;ii++)
3219: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3220: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3221: }
3222:
3223: cov[1]=1.;
3224:
3225: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3226: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3227: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3228: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3229: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3230: ncvloop++;
1.218 brouard 3231: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3232: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3233: /* Covariates have to be included here again */
3234: cov[2]=agefin;
1.319 brouard 3235: if(nagesqr==1){
1.217 brouard 3236: cov[3]= agefin*agefin;;
1.319 brouard 3237: }
1.332 brouard 3238: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3239: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3240: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3241: }else{
1.332 brouard 3242: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3243: }
1.332 brouard 3244: }/* End of loop on model equation */
3245:
3246: /* Old code */
3247:
3248: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3249: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3250: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3251: /* /\* 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)); *\/ */
3252: /* } */
3253: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3254: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3255: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3256: /* /\* /\\* 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])]); *\\/ *\/ */
3257: /* /\* } *\/ */
3258: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3259: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3260: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3261: /* /\* 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]); *\/ */
3262: /* } */
3263: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3264: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3265: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3266: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3267: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3268: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3269: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3270: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3271: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3272: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3273: /* } */
3274: /* /\* 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]); *\/ */
3275: /* } */
3276: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3277: /* /\* 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]); *\/ */
3278: /* if(Dummy[Tvard[k][1]]==0){ */
3279: /* if(Dummy[Tvard[k][2]]==0){ */
3280: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3281: /* }else{ */
3282: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3283: /* } */
3284: /* }else{ */
3285: /* if(Dummy[Tvard[k][2]]==0){ */
3286: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3287: /* }else{ */
3288: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3289: /* } */
3290: /* } */
3291: /* } */
1.217 brouard 3292:
3293: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3294: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3295: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3296: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3297: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3298: /* ij should be linked to the correct index of cov */
3299: /* age and covariate values ij are in 'cov', but we need to pass
3300: * ij for the observed prevalence at age and status and covariate
3301: * number: prevacurrent[(int)agefin][ii][ij]
3302: */
3303: /* 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 *\/ */
3304: /* 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 *\/ */
3305: 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 3306: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3307: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3308: /* for(i=1; i<=nlstate+ndeath; i++) { */
3309: /* printf("%d newm= ",i); */
3310: /* for(j=1;j<=nlstate+ndeath;j++) { */
3311: /* printf("%f ",newm[i][j]); */
3312: /* } */
3313: /* printf("oldm * "); */
3314: /* for(j=1;j<=nlstate+ndeath;j++) { */
3315: /* printf("%f ",oldm[i][j]); */
3316: /* } */
1.268 brouard 3317: /* printf(" bmmij "); */
1.266 brouard 3318: /* for(j=1;j<=nlstate+ndeath;j++) { */
3319: /* printf("%f ",pmmij[i][j]); */
3320: /* } */
3321: /* printf("\n"); */
3322: /* } */
3323: /* } */
1.217 brouard 3324: savm=oldm;
3325: oldm=newm;
1.266 brouard 3326:
1.217 brouard 3327: for(j=1; j<=nlstate; j++){
3328: max[j]=0.;
3329: min[j]=1.;
3330: }
3331: for(j=1; j<=nlstate; j++){
3332: for(i=1;i<=nlstate;i++){
1.234 brouard 3333: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3334: bprlim[i][j]= newm[i][j];
3335: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3336: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3337: }
3338: }
1.218 brouard 3339:
1.217 brouard 3340: maxmax=0.;
3341: for(i=1; i<=nlstate; i++){
1.318 brouard 3342: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3343: maxmax=FMAX(maxmax,meandiff[i]);
3344: /* 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 3345: } /* i loop */
1.217 brouard 3346: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3347: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3348: if(maxmax < ftolpl){
1.220 brouard 3349: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3350: free_vector(min,1,nlstate);
3351: free_vector(max,1,nlstate);
3352: free_vector(meandiff,1,nlstate);
3353: return bprlim;
3354: }
1.288 brouard 3355: } /* agefin loop */
1.217 brouard 3356: /* After some age loop it doesn't converge */
1.288 brouard 3357: if(!first){
1.247 brouard 3358: first=1;
3359: 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\
3360: 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);
3361: }
3362: 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 3363: 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);
3364: /* 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); */
3365: free_vector(min,1,nlstate);
3366: free_vector(max,1,nlstate);
3367: free_vector(meandiff,1,nlstate);
3368:
3369: return bprlim; /* should not reach here */
3370: }
3371:
1.126 brouard 3372: /*************** transition probabilities ***************/
3373:
3374: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3375: {
1.138 brouard 3376: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3377: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3378: model to the ncovmodel covariates (including constant and age).
3379: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3380: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3381: ncth covariate in the global vector x is given by the formula:
3382: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3383: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3384: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3385: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3386: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3387: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3388: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3389: */
3390: double s1, lnpijopii;
1.126 brouard 3391: /*double t34;*/
1.164 brouard 3392: int i,j, nc, ii, jj;
1.126 brouard 3393:
1.223 brouard 3394: for(i=1; i<= nlstate; i++){
3395: for(j=1; j<i;j++){
3396: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3397: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3398: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3399: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3400: }
3401: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3402: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3403: }
3404: for(j=i+1; j<=nlstate+ndeath;j++){
3405: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3406: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3407: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3408: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3409: }
3410: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3411: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3412: }
3413: }
1.218 brouard 3414:
1.223 brouard 3415: for(i=1; i<= nlstate; i++){
3416: s1=0;
3417: for(j=1; j<i; j++){
1.339 brouard 3418: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3419: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3420: }
3421: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3422: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3423: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3424: }
3425: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3426: ps[i][i]=1./(s1+1.);
3427: /* Computing other pijs */
3428: for(j=1; j<i; j++)
1.325 brouard 3429: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3430: for(j=i+1; j<=nlstate+ndeath; j++)
3431: ps[i][j]= exp(ps[i][j])*ps[i][i];
3432: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3433: } /* end i */
1.218 brouard 3434:
1.223 brouard 3435: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3436: for(jj=1; jj<= nlstate+ndeath; jj++){
3437: ps[ii][jj]=0;
3438: ps[ii][ii]=1;
3439: }
3440: }
1.294 brouard 3441:
3442:
1.223 brouard 3443: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3444: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3445: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3446: /* } */
3447: /* printf("\n "); */
3448: /* } */
3449: /* printf("\n ");printf("%lf ",cov[2]);*/
3450: /*
3451: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3452: goto end;*/
1.266 brouard 3453: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3454: }
3455:
1.218 brouard 3456: /*************** backward transition probabilities ***************/
3457:
3458: /* 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 ) */
3459: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3460: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3461: {
1.302 brouard 3462: /* 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 3463: * 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 3464: */
1.218 brouard 3465: int i, ii, j,k;
1.222 brouard 3466:
3467: double **out, **pmij();
3468: double sumnew=0.;
1.218 brouard 3469: double agefin;
1.292 brouard 3470: 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 3471: double **dnewm, **dsavm, **doldm;
3472: double **bbmij;
3473:
1.218 brouard 3474: doldm=ddoldms; /* global pointers */
1.222 brouard 3475: dnewm=ddnewms;
3476: dsavm=ddsavms;
1.318 brouard 3477:
3478: /* Debug */
3479: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3480: agefin=cov[2];
1.268 brouard 3481: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3482: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3483: the observed prevalence (with this covariate ij) at beginning of transition */
3484: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3485:
3486: /* P_x */
1.325 brouard 3487: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3488: /* outputs pmmij which is a stochastic matrix in row */
3489:
3490: /* Diag(w_x) */
1.292 brouard 3491: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3492: sumnew=0.;
1.269 brouard 3493: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3494: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3495: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3496: sumnew+=prevacurrent[(int)agefin][ii][ij];
3497: }
3498: if(sumnew >0.01){ /* At least some value in the prevalence */
3499: for (ii=1;ii<=nlstate+ndeath;ii++){
3500: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3501: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3502: }
3503: }else{
3504: for (ii=1;ii<=nlstate+ndeath;ii++){
3505: for (j=1;j<=nlstate+ndeath;j++)
3506: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3507: }
3508: /* if(sumnew <0.9){ */
3509: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3510: /* } */
3511: }
3512: k3=0.0; /* We put the last diagonal to 0 */
3513: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3514: doldm[ii][ii]= k3;
3515: }
3516: /* End doldm, At the end doldm is diag[(w_i)] */
3517:
1.292 brouard 3518: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3519: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3520:
1.292 brouard 3521: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3522: /* 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 3523: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3524: sumnew=0.;
1.222 brouard 3525: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3526: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3527: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3528: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3529: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3530: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3531: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3532: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3533: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3534: /* }else */
1.268 brouard 3535: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3536: } /*End ii */
3537: } /* 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 */
3538:
1.292 brouard 3539: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3540: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3541: /* end bmij */
1.266 brouard 3542: return ps; /*pointer is unchanged */
1.218 brouard 3543: }
1.217 brouard 3544: /*************** transition probabilities ***************/
3545:
1.218 brouard 3546: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3547: {
3548: /* According to parameters values stored in x and the covariate's values stored in cov,
3549: computes the probability to be observed in state j being in state i by appying the
3550: model to the ncovmodel covariates (including constant and age).
3551: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3552: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3553: ncth covariate in the global vector x is given by the formula:
3554: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3555: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3556: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3557: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3558: Outputs ps[i][j] the probability to be observed in j being in j according to
3559: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3560: */
3561: double s1, lnpijopii;
3562: /*double t34;*/
3563: int i,j, nc, ii, jj;
3564:
1.234 brouard 3565: for(i=1; i<= nlstate; i++){
3566: for(j=1; j<i;j++){
3567: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3568: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3569: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3570: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3571: }
3572: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3573: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3574: }
3575: for(j=i+1; j<=nlstate+ndeath;j++){
3576: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3577: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3578: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3579: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3580: }
3581: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3582: }
3583: }
3584:
3585: for(i=1; i<= nlstate; i++){
3586: s1=0;
3587: for(j=1; j<i; j++){
3588: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3589: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3590: }
3591: for(j=i+1; j<=nlstate+ndeath; j++){
3592: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3593: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3594: }
3595: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3596: ps[i][i]=1./(s1+1.);
3597: /* Computing other pijs */
3598: for(j=1; j<i; j++)
3599: ps[i][j]= exp(ps[i][j])*ps[i][i];
3600: for(j=i+1; j<=nlstate+ndeath; j++)
3601: ps[i][j]= exp(ps[i][j])*ps[i][i];
3602: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3603: } /* end i */
3604:
3605: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3606: for(jj=1; jj<= nlstate+ndeath; jj++){
3607: ps[ii][jj]=0;
3608: ps[ii][ii]=1;
3609: }
3610: }
1.296 brouard 3611: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3612: for(jj=1; jj<= nlstate+ndeath; jj++){
3613: s1=0.;
3614: for(ii=1; ii<= nlstate+ndeath; ii++){
3615: s1+=ps[ii][jj];
3616: }
3617: for(ii=1; ii<= nlstate; ii++){
3618: ps[ii][jj]=ps[ii][jj]/s1;
3619: }
3620: }
3621: /* Transposition */
3622: for(jj=1; jj<= nlstate+ndeath; jj++){
3623: for(ii=jj; ii<= nlstate+ndeath; ii++){
3624: s1=ps[ii][jj];
3625: ps[ii][jj]=ps[jj][ii];
3626: ps[jj][ii]=s1;
3627: }
3628: }
3629: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3630: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3631: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3632: /* } */
3633: /* printf("\n "); */
3634: /* } */
3635: /* printf("\n ");printf("%lf ",cov[2]);*/
3636: /*
3637: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3638: goto end;*/
3639: return ps;
1.217 brouard 3640: }
3641:
3642:
1.126 brouard 3643: /**************** Product of 2 matrices ******************/
3644:
1.145 brouard 3645: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3646: {
3647: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3648: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3649: /* in, b, out are matrice of pointers which should have been initialized
3650: before: only the contents of out is modified. The function returns
3651: a pointer to pointers identical to out */
1.145 brouard 3652: int i, j, k;
1.126 brouard 3653: for(i=nrl; i<= nrh; i++)
1.145 brouard 3654: for(k=ncolol; k<=ncoloh; k++){
3655: out[i][k]=0.;
3656: for(j=ncl; j<=nch; j++)
3657: out[i][k] +=in[i][j]*b[j][k];
3658: }
1.126 brouard 3659: return out;
3660: }
3661:
3662:
3663: /************* Higher Matrix Product ***************/
3664:
1.235 brouard 3665: 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 3666: {
1.336 brouard 3667: /* Already optimized with precov.
3668: 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 3669: 'nhstepm*hstepm*stepm' months (i.e. until
3670: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3671: nhstepm*hstepm matrices.
3672: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3673: (typically every 2 years instead of every month which is too big
3674: for the memory).
3675: Model is determined by parameters x and covariates have to be
3676: included manually here.
3677:
3678: */
3679:
1.330 brouard 3680: int i, j, d, h, k, k1;
1.131 brouard 3681: double **out, cov[NCOVMAX+1];
1.126 brouard 3682: double **newm;
1.187 brouard 3683: double agexact;
1.214 brouard 3684: double agebegin, ageend;
1.126 brouard 3685:
3686: /* Hstepm could be zero and should return the unit matrix */
3687: for (i=1;i<=nlstate+ndeath;i++)
3688: for (j=1;j<=nlstate+ndeath;j++){
3689: oldm[i][j]=(i==j ? 1.0 : 0.0);
3690: po[i][j][0]=(i==j ? 1.0 : 0.0);
3691: }
3692: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3693: for(h=1; h <=nhstepm; h++){
3694: for(d=1; d <=hstepm; d++){
3695: newm=savm;
3696: /* Covariates have to be included here again */
3697: cov[1]=1.;
1.214 brouard 3698: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3699: cov[2]=agexact;
1.319 brouard 3700: if(nagesqr==1){
1.227 brouard 3701: cov[3]= agexact*agexact;
1.319 brouard 3702: }
1.330 brouard 3703: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3704: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3705: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3706: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3707: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3708: }else{
3709: cov[2+nagesqr+k1]=precov[nres][k1];
3710: }
3711: }/* End of loop on model equation */
3712: /* Old code */
3713: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3714: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3715: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3716: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3717: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3718: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3719: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3720: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3721: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3722: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3723: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3724: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3725: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3726: /* /\* 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]])); *\/ */
3727: /* 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); */
3728: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3729: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3730: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3731: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3732: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3733: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3734: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3735: /* 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]]); */
3736: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3737: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3738: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3739: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3740: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3741: /* 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]); */
3742: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3743:
3744: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3745: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3746: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3747: /* /\* *\/ */
1.330 brouard 3748: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3749: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3750: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3751: /* /\*cptcovage=2 1 2 *\/ */
3752: /* /\*Tage[k]= 5 8 *\/ */
3753: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3754: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3755: /* 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]]); */
3756: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3757: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3758: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3759: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3760: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3761: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3762: /* /\* 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); *\/ */
3763: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3764: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3765: /* /\* } *\/ */
3766: /* /\* 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]); *\/ */
3767: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3768: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3769: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3770: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3771: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3772: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3773: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3774: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3775: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3776:
1.332 brouard 3777: /* /\* 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])]); *\/ */
3778: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3779: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3780: /* 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]]); */
3781: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3782:
3783: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3784: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3785: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3786: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3787: /* /\* 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]])]; *\/ */
3788: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3789: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3790: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3791: /* /\* } *\/ */
3792: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3793: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3794: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3795: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3796: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3797: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3798: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3799: /* /\* } *\/ */
3800: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3801: /* }/\*end of products *\/ */
3802: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3803: /* for (k=1; k<=cptcovn;k++) */
3804: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3805: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3806: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3807: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3808: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3809:
3810:
1.126 brouard 3811: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3812: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3813: /* right multiplication of oldm by the current matrix */
1.126 brouard 3814: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3815: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3816: /* if((int)age == 70){ */
3817: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3818: /* for(i=1; i<=nlstate+ndeath; i++) { */
3819: /* printf("%d pmmij ",i); */
3820: /* for(j=1;j<=nlstate+ndeath;j++) { */
3821: /* printf("%f ",pmmij[i][j]); */
3822: /* } */
3823: /* printf(" oldm "); */
3824: /* for(j=1;j<=nlstate+ndeath;j++) { */
3825: /* printf("%f ",oldm[i][j]); */
3826: /* } */
3827: /* printf("\n"); */
3828: /* } */
3829: /* } */
1.126 brouard 3830: savm=oldm;
3831: oldm=newm;
3832: }
3833: for(i=1; i<=nlstate+ndeath; i++)
3834: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3835: po[i][j][h]=newm[i][j];
3836: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3837: }
1.128 brouard 3838: /*printf("h=%d ",h);*/
1.126 brouard 3839: } /* end h */
1.267 brouard 3840: /* printf("\n H=%d \n",h); */
1.126 brouard 3841: return po;
3842: }
3843:
1.217 brouard 3844: /************* Higher Back Matrix Product ***************/
1.218 brouard 3845: /* 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 3846: 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 3847: {
1.332 brouard 3848: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3849: computes the transition matrix starting at age 'age' over
1.217 brouard 3850: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3851: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3852: nhstepm*hstepm matrices.
3853: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3854: (typically every 2 years instead of every month which is too big
1.217 brouard 3855: for the memory).
1.218 brouard 3856: Model is determined by parameters x and covariates have to be
1.266 brouard 3857: included manually here. Then we use a call to bmij(x and cov)
3858: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3859: */
1.217 brouard 3860:
1.332 brouard 3861: int i, j, d, h, k, k1;
1.266 brouard 3862: double **out, cov[NCOVMAX+1], **bmij();
3863: double **newm, ***newmm;
1.217 brouard 3864: double agexact;
3865: double agebegin, ageend;
1.222 brouard 3866: double **oldm, **savm;
1.217 brouard 3867:
1.266 brouard 3868: newmm=po; /* To be saved */
3869: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3870: /* Hstepm could be zero and should return the unit matrix */
3871: for (i=1;i<=nlstate+ndeath;i++)
3872: for (j=1;j<=nlstate+ndeath;j++){
3873: oldm[i][j]=(i==j ? 1.0 : 0.0);
3874: po[i][j][0]=(i==j ? 1.0 : 0.0);
3875: }
3876: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3877: for(h=1; h <=nhstepm; h++){
3878: for(d=1; d <=hstepm; d++){
3879: newm=savm;
3880: /* Covariates have to be included here again */
3881: cov[1]=1.;
1.271 brouard 3882: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3883: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3884: /* Debug */
3885: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3886: cov[2]=agexact;
1.332 brouard 3887: if(nagesqr==1){
1.222 brouard 3888: cov[3]= agexact*agexact;
1.332 brouard 3889: }
3890: /** New code */
3891: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3892: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3893: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3894: }else{
1.332 brouard 3895: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3896: }
1.332 brouard 3897: }/* End of loop on model equation */
3898: /** End of new code */
3899: /** This was old code */
3900: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3901: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3902: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3903: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3904: /* /\* 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)); *\/ */
3905: /* } */
3906: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3907: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3908: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3909: /* /\* 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]); *\/ */
3910: /* } */
3911: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3912: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3913: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3914: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3915: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3916: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3917: /* } */
3918: /* /\* 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]); *\/ */
3919: /* } */
3920: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3921: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3922: /* if(Dummy[Tvard[k][1]]==0){ */
3923: /* if(Dummy[Tvard[k][2]]==0){ */
3924: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3925: /* }else{ */
3926: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3927: /* } */
3928: /* }else{ */
3929: /* if(Dummy[Tvard[k][2]]==0){ */
3930: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3931: /* }else{ */
3932: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3933: /* } */
3934: /* } */
3935: /* } */
3936: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3937: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3938: /** End of old code */
3939:
1.218 brouard 3940: /* Careful transposed matrix */
1.266 brouard 3941: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3942: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3943: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3944: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3945: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3946: /* if((int)age == 70){ */
3947: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3948: /* for(i=1; i<=nlstate+ndeath; i++) { */
3949: /* printf("%d pmmij ",i); */
3950: /* for(j=1;j<=nlstate+ndeath;j++) { */
3951: /* printf("%f ",pmmij[i][j]); */
3952: /* } */
3953: /* printf(" oldm "); */
3954: /* for(j=1;j<=nlstate+ndeath;j++) { */
3955: /* printf("%f ",oldm[i][j]); */
3956: /* } */
3957: /* printf("\n"); */
3958: /* } */
3959: /* } */
3960: savm=oldm;
3961: oldm=newm;
3962: }
3963: for(i=1; i<=nlstate+ndeath; i++)
3964: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3965: po[i][j][h]=newm[i][j];
1.268 brouard 3966: /* if(h==nhstepm) */
3967: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3968: }
1.268 brouard 3969: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3970: } /* end h */
1.268 brouard 3971: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3972: return po;
3973: }
3974:
3975:
1.162 brouard 3976: #ifdef NLOPT
3977: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3978: double fret;
3979: double *xt;
3980: int j;
3981: myfunc_data *d2 = (myfunc_data *) pd;
3982: /* xt = (p1-1); */
3983: xt=vector(1,n);
3984: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3985:
3986: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3987: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3988: printf("Function = %.12lf ",fret);
3989: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3990: printf("\n");
3991: free_vector(xt,1,n);
3992: return fret;
3993: }
3994: #endif
1.126 brouard 3995:
3996: /*************** log-likelihood *************/
3997: double func( double *x)
3998: {
1.336 brouard 3999: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 4000: int ioffset=0;
1.339 brouard 4001: int ipos=0,iposold=0,ncovv=0;
4002:
1.340 brouard 4003: double cotvarv, cotvarvold;
1.226 brouard 4004: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
4005: double **out;
4006: double lli; /* Individual log likelihood */
4007: int s1, s2;
1.228 brouard 4008: 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 4009:
1.226 brouard 4010: double bbh, survp;
4011: double agexact;
1.336 brouard 4012: double agebegin, ageend;
1.226 brouard 4013: /*extern weight */
4014: /* We are differentiating ll according to initial status */
4015: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4016: /*for(i=1;i<imx;i++)
4017: printf(" %d\n",s[4][i]);
4018: */
1.162 brouard 4019:
1.226 brouard 4020: ++countcallfunc;
1.162 brouard 4021:
1.226 brouard 4022: cov[1]=1.;
1.126 brouard 4023:
1.226 brouard 4024: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4025: ioffset=0;
1.226 brouard 4026: if(mle==1){
4027: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4028: /* Computes the values of the ncovmodel covariates of the model
4029: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4030: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4031: to be observed in j being in i according to the model.
4032: */
1.243 brouard 4033: ioffset=2+nagesqr ;
1.233 brouard 4034: /* Fixed */
1.345 brouard 4035: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4036: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4037: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4038: /* 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 4039: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4040: 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 4041: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4042: }
1.226 brouard 4043: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4044: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4045: has been calculated etc */
4046: /* For an individual i, wav[i] gives the number of effective waves */
4047: /* We compute the contribution to Likelihood of each effective transition
4048: mw[mi][i] is real wave of the mi th effectve wave */
4049: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4050: s2=s[mw[mi+1][i]][i];
1.341 brouard 4051: 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 4052: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4053: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4054: */
1.336 brouard 4055: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4056: /* Wave varying (but not age varying) */
1.339 brouard 4057: /* 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*\/ */
4058: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4059: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4060: /* } */
1.340 brouard 4061: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4062: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4063: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4064: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4065: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4066: }else{ /* fixed covariate */
1.345 brouard 4067: 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 4068: }
1.339 brouard 4069: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4070: cotvarvold=cotvarv;
4071: }else{ /* A second product */
4072: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4073: }
4074: iposold=ipos;
1.340 brouard 4075: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4076: }
1.339 brouard 4077: /* for products of time varying to be done */
1.234 brouard 4078: for (ii=1;ii<=nlstate+ndeath;ii++)
4079: for (j=1;j<=nlstate+ndeath;j++){
4080: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4081: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4082: }
1.336 brouard 4083:
4084: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4085: 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 4086: for(d=0; d<dh[mi][i]; d++){
4087: newm=savm;
4088: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4089: cov[2]=agexact;
4090: if(nagesqr==1)
4091: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 4092: /* for (kk=1; kk<=cptcovage;kk++) { */
4093: /* if(!FixedV[Tvar[Tage[kk]]]) */
4094: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
4095: /* else */
4096: /* 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) *\/ */
4097: /* } */
4098: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4099: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4100: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4101: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4102: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4103: }else{ /* fixed covariate */
4104: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4105: }
4106: if(ipos!=iposold){ /* Not a product or first of a product */
4107: cotvarvold=cotvarv;
4108: }else{ /* A second product */
4109: cotvarv=cotvarv*cotvarvold;
4110: }
4111: iposold=ipos;
4112: cov[ioffset+ipos]=cotvarv*agexact;
4113: /* For products */
1.234 brouard 4114: }
1.349 brouard 4115:
1.234 brouard 4116: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4117: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4118: savm=oldm;
4119: oldm=newm;
4120: } /* end mult */
4121:
4122: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4123: /* But now since version 0.9 we anticipate for bias at large stepm.
4124: * If stepm is larger than one month (smallest stepm) and if the exact delay
4125: * (in months) between two waves is not a multiple of stepm, we rounded to
4126: * the nearest (and in case of equal distance, to the lowest) interval but now
4127: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4128: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4129: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4130: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4131: * -stepm/2 to stepm/2 .
4132: * For stepm=1 the results are the same as for previous versions of Imach.
4133: * For stepm > 1 the results are less biased than in previous versions.
4134: */
1.234 brouard 4135: s1=s[mw[mi][i]][i];
4136: s2=s[mw[mi+1][i]][i];
4137: bbh=(double)bh[mi][i]/(double)stepm;
4138: /* bias bh is positive if real duration
4139: * is higher than the multiple of stepm and negative otherwise.
4140: */
4141: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4142: if( s2 > nlstate){
4143: /* i.e. if s2 is a death state and if the date of death is known
4144: then the contribution to the likelihood is the probability to
4145: die between last step unit time and current step unit time,
4146: which is also equal to probability to die before dh
4147: minus probability to die before dh-stepm .
4148: In version up to 0.92 likelihood was computed
4149: as if date of death was unknown. Death was treated as any other
4150: health state: the date of the interview describes the actual state
4151: and not the date of a change in health state. The former idea was
4152: to consider that at each interview the state was recorded
4153: (healthy, disable or death) and IMaCh was corrected; but when we
4154: introduced the exact date of death then we should have modified
4155: the contribution of an exact death to the likelihood. This new
4156: contribution is smaller and very dependent of the step unit
4157: stepm. It is no more the probability to die between last interview
4158: and month of death but the probability to survive from last
4159: interview up to one month before death multiplied by the
4160: probability to die within a month. Thanks to Chris
4161: Jackson for correcting this bug. Former versions increased
4162: mortality artificially. The bad side is that we add another loop
4163: which slows down the processing. The difference can be up to 10%
4164: lower mortality.
4165: */
4166: /* If, at the beginning of the maximization mostly, the
4167: cumulative probability or probability to be dead is
4168: constant (ie = 1) over time d, the difference is equal to
4169: 0. out[s1][3] = savm[s1][3]: probability, being at state
4170: s1 at precedent wave, to be dead a month before current
4171: wave is equal to probability, being at state s1 at
4172: precedent wave, to be dead at mont of the current
4173: wave. Then the observed probability (that this person died)
4174: is null according to current estimated parameter. In fact,
4175: it should be very low but not zero otherwise the log go to
4176: infinity.
4177: */
1.183 brouard 4178: /* #ifdef INFINITYORIGINAL */
4179: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4180: /* #else */
4181: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4182: /* lli=log(mytinydouble); */
4183: /* else */
4184: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4185: /* #endif */
1.226 brouard 4186: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4187:
1.226 brouard 4188: } else if ( s2==-1 ) { /* alive */
4189: for (j=1,survp=0. ; j<=nlstate; j++)
4190: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4191: /*survp += out[s1][j]; */
4192: lli= log(survp);
4193: }
1.336 brouard 4194: /* else if (s2==-4) { */
4195: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4196: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4197: /* lli= log(survp); */
4198: /* } */
4199: /* else if (s2==-5) { */
4200: /* for (j=1,survp=0. ; j<=2; j++) */
4201: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4202: /* lli= log(survp); */
4203: /* } */
1.226 brouard 4204: else{
4205: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4206: /* 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 */
4207: }
4208: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4209: /*if(lli ==000.0)*/
1.340 brouard 4210: /* 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 4211: ipmx +=1;
4212: sw += weight[i];
4213: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4214: /* if (lli < log(mytinydouble)){ */
4215: /* 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); */
4216: /* 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]); */
4217: /* } */
4218: } /* end of wave */
4219: } /* end of individual */
4220: } else if(mle==2){
4221: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4222: ioffset=2+nagesqr ;
4223: for (k=1; k<=ncovf;k++)
4224: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4225: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4226: for(k=1; k <= ncovv ; k++){
1.341 brouard 4227: 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 4228: }
1.226 brouard 4229: for (ii=1;ii<=nlstate+ndeath;ii++)
4230: for (j=1;j<=nlstate+ndeath;j++){
4231: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4232: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4233: }
4234: for(d=0; d<=dh[mi][i]; d++){
4235: newm=savm;
4236: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4237: cov[2]=agexact;
4238: if(nagesqr==1)
4239: cov[3]= agexact*agexact;
4240: for (kk=1; kk<=cptcovage;kk++) {
4241: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4242: }
4243: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4244: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4245: savm=oldm;
4246: oldm=newm;
4247: } /* end mult */
4248:
4249: s1=s[mw[mi][i]][i];
4250: s2=s[mw[mi+1][i]][i];
4251: bbh=(double)bh[mi][i]/(double)stepm;
4252: 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 */
4253: ipmx +=1;
4254: sw += weight[i];
4255: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4256: } /* end of wave */
4257: } /* end of individual */
4258: } else if(mle==3){ /* exponential inter-extrapolation */
4259: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4260: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4261: for(mi=1; mi<= wav[i]-1; mi++){
4262: for (ii=1;ii<=nlstate+ndeath;ii++)
4263: for (j=1;j<=nlstate+ndeath;j++){
4264: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4265: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4266: }
4267: for(d=0; d<dh[mi][i]; d++){
4268: newm=savm;
4269: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4270: cov[2]=agexact;
4271: if(nagesqr==1)
4272: cov[3]= agexact*agexact;
4273: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4274: if(!FixedV[Tvar[Tage[kk]]])
4275: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4276: else
1.341 brouard 4277: 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 4278: }
4279: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4280: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4281: savm=oldm;
4282: oldm=newm;
4283: } /* end mult */
4284:
4285: s1=s[mw[mi][i]][i];
4286: s2=s[mw[mi+1][i]][i];
4287: bbh=(double)bh[mi][i]/(double)stepm;
4288: 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 */
4289: ipmx +=1;
4290: sw += weight[i];
4291: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4292: } /* end of wave */
4293: } /* end of individual */
4294: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4295: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4296: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4297: for(mi=1; mi<= wav[i]-1; mi++){
4298: for (ii=1;ii<=nlstate+ndeath;ii++)
4299: for (j=1;j<=nlstate+ndeath;j++){
4300: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4301: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4302: }
4303: for(d=0; d<dh[mi][i]; d++){
4304: newm=savm;
4305: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4306: cov[2]=agexact;
4307: if(nagesqr==1)
4308: cov[3]= agexact*agexact;
4309: for (kk=1; kk<=cptcovage;kk++) {
4310: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4311: }
1.126 brouard 4312:
1.226 brouard 4313: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4314: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4315: savm=oldm;
4316: oldm=newm;
4317: } /* end mult */
4318:
4319: s1=s[mw[mi][i]][i];
4320: s2=s[mw[mi+1][i]][i];
4321: if( s2 > nlstate){
4322: lli=log(out[s1][s2] - savm[s1][s2]);
4323: } else if ( s2==-1 ) { /* alive */
4324: for (j=1,survp=0. ; j<=nlstate; j++)
4325: survp += out[s1][j];
4326: lli= log(survp);
4327: }else{
4328: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4329: }
4330: ipmx +=1;
4331: sw += weight[i];
4332: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4333: /* 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 4334: } /* end of wave */
4335: } /* end of individual */
4336: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4337: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4338: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4339: for(mi=1; mi<= wav[i]-1; mi++){
4340: for (ii=1;ii<=nlstate+ndeath;ii++)
4341: for (j=1;j<=nlstate+ndeath;j++){
4342: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4343: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4344: }
4345: for(d=0; d<dh[mi][i]; d++){
4346: newm=savm;
4347: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4348: cov[2]=agexact;
4349: if(nagesqr==1)
4350: cov[3]= agexact*agexact;
4351: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4352: if(!FixedV[Tvar[Tage[kk]]])
4353: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4354: else
1.341 brouard 4355: 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 4356: }
1.126 brouard 4357:
1.226 brouard 4358: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4359: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4360: savm=oldm;
4361: oldm=newm;
4362: } /* end mult */
4363:
4364: s1=s[mw[mi][i]][i];
4365: s2=s[mw[mi+1][i]][i];
4366: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4367: ipmx +=1;
4368: sw += weight[i];
4369: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4370: /*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]);*/
4371: } /* end of wave */
4372: } /* end of individual */
4373: } /* End of if */
4374: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4375: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4376: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4377: return -l;
1.126 brouard 4378: }
4379:
4380: /*************** log-likelihood *************/
4381: double funcone( double *x)
4382: {
1.228 brouard 4383: /* Same as func but slower because of a lot of printf and if */
1.349 brouard 4384: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4385: int ioffset=0;
1.339 brouard 4386: int ipos=0,iposold=0,ncovv=0;
4387:
1.340 brouard 4388: double cotvarv, cotvarvold;
1.131 brouard 4389: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4390: double **out;
4391: double lli; /* Individual log likelihood */
4392: double llt;
4393: int s1, s2;
1.228 brouard 4394: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4395:
1.126 brouard 4396: double bbh, survp;
1.187 brouard 4397: double agexact;
1.214 brouard 4398: double agebegin, ageend;
1.126 brouard 4399: /*extern weight */
4400: /* We are differentiating ll according to initial status */
4401: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4402: /*for(i=1;i<imx;i++)
4403: printf(" %d\n",s[4][i]);
4404: */
4405: cov[1]=1.;
4406:
4407: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4408: ioffset=0;
4409: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4410: /* Computes the values of the ncovmodel covariates of the model
4411: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4412: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4413: to be observed in j being in i according to the model.
4414: */
1.243 brouard 4415: /* ioffset=2+nagesqr+cptcovage; */
4416: ioffset=2+nagesqr;
1.232 brouard 4417: /* Fixed */
1.224 brouard 4418: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4419: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 4420: 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 4421: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4422: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4423: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4424: 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 4425: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4426: /* cov[2+6]=covar[Tvar[6]][i]; */
4427: /* cov[2+6]=covar[2][i]; V2 */
4428: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4429: /* cov[2+7]=covar[Tvar[7]][i]; */
4430: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4431: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4432: /* cov[2+9]=covar[Tvar[9]][i]; */
4433: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4434: }
1.336 brouard 4435: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4436: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4437: has been calculated etc */
4438: /* For an individual i, wav[i] gives the number of effective waves */
4439: /* We compute the contribution to Likelihood of each effective transition
4440: mw[mi][i] is real wave of the mi th effectve wave */
4441: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4442: s2=s[mw[mi+1][i]][i];
1.341 brouard 4443: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4444: */
4445: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4446: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4447: /* 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?)*\/ */
4448: /* } */
1.231 brouard 4449: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4450: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4451: /* } */
1.225 brouard 4452:
1.233 brouard 4453:
4454: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4455: /* 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 */
4456: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4457: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4458: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4459: /* } */
4460:
4461: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4462: /* model V1+V3+age*V1+age*V3+V1*V3 */
4463: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4464: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4465: /* We need the position of the time varying or product in the model */
4466: /* 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 */
4467: /* TvarVV gives the variable name */
1.340 brouard 4468: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4469: * k= 1 2 3 4 5 6 7 8 9
4470: * varying 1 2 3 4 5
4471: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4472: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4473: * TvarVVind 2 3 7 7 8 8 9 9
4474: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4475: */
1.345 brouard 4476: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 4477: * 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 4478: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 4479: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4480: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
4481: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
4482: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4483: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4484: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4485: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4486: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4487: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4488: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4489: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4490: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4491: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4492: * 12 13 14 15 16
4493: * 17 18 19 20 21
4494: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
4495: * 2 3 4 6 7
4496: * 9 11 12 13 14
4497: * cptcovage=5+5 total of covariates with age
4498: * Tage[cptcovage] age*V2=12 13 14 15 16
4499: *1 17 18 19 20 21 gives the position in model of covariates associated with age
4500: *3 Tage[cptcovage] age*V3*V2=6
4501: *3 age*V2=12 13 14 15 16
4502: *3 age*V6*V3=18 19 20 21
4503: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4504: * 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
4505: * 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
4506: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4507: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4508: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
4509: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
4510: * 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
4511: * Tvar= {2, 3, 4, 6, 7,
4512: * 9, 10, 11, 12, 13, 14,
4513: * Tvar[12]=2, 3, 4, 6, 7,
4514: * Tvar[17]=9, 11, 12, 13, 14}
4515: * Typevar[1]@21 = {0, 0, 0, 0, 0,
4516: * 2, 2, 2, 2, 2, 2,
4517: * 3 3, 2, 2, 2, 2, 2,
4518: * 1, 1, 1, 1, 1,
4519: * 3, 3, 3, 3, 3}
4520: * 3 2, 3, 3, 3, 3}
4521: * 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
4522: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4523: * 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}
4524: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4525: * cptcovprod=11 (6+5)
4526: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
4527: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
4528: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
4529: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
4530: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4531: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4532: * cptcovdageprod=5 for gnuplot printing
4533: * cptcovprodvage=6
4534: * ncova=15 1 2 3 4 5
4535: * 6 7 8 9 10 11 12 13 14 15
4536: * TvarA 2 3 4 6 7
4537: * 6 2 6 7 7 3 6 4 7 4
4538: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4539: * ncovf 1 2 3
1.349 brouard 4540: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4541: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4542: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4543: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4544: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4545: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4546: * 3 1 2 3 4 5 6 7 8 9 10 11 12
4547: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
4548: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
4549: * 3 cptcovprodvage=6
4550: * 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
4551: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
4552: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
4553: * TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
4554: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
4555: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4556: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
4557: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
4558: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
4559: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
4560: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
4561: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4562: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 4563: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
4564: * 2, 3, 4, 6, 7,
4565: * 6, 8, 9, 10, 11}
1.345 brouard 4566: * TvarFind[itv] 0 0 0
4567: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
4568: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4569: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4570: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 4571: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4572: */
4573:
1.349 brouard 4574: 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 */
4575: 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 4576: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4577: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4578: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4579: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.340 brouard 4580: }else{ /* fixed covariate */
1.345 brouard 4581: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
1.349 brouard 4582: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.340 brouard 4583: }
1.339 brouard 4584: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4585: cotvarvold=cotvarv;
4586: }else{ /* A second product */
4587: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4588: }
4589: iposold=ipos;
1.340 brouard 4590: cov[ioffset+ipos]=cotvarv;
1.339 brouard 4591: /* For products */
4592: }
4593: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4594: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4595: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4596: /* /\* 1 2 3 4 5 *\/ */
4597: /* /\*itv 1 *\/ */
4598: /* /\* TvarVInd[1]= 2 *\/ */
4599: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4600: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4601: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4602: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4603: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4604: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4605: /* /\* 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]); *\/ */
4606: /* } */
1.232 brouard 4607: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4608: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4609: /* /\* 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]); *\/ */
4610: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4611: /* } */
1.126 brouard 4612: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4613: for (j=1;j<=nlstate+ndeath;j++){
4614: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4615: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4616: }
1.214 brouard 4617:
4618: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4619: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4620: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4621: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4622: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4623: and mw[mi+1][i]. dh depends on stepm.*/
4624: newm=savm;
1.247 brouard 4625: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4626: cov[2]=agexact;
4627: if(nagesqr==1)
4628: cov[3]= agexact*agexact;
1.349 brouard 4629: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4630: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4631: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4632: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4633: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4634: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4635: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4636: }else{ /* fixed covariate */
4637: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4638: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4639: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4640: }
4641: if(ipos!=iposold){ /* Not a product or first of a product */
4642: cotvarvold=cotvarv;
4643: }else{ /* A second product */
4644: /* printf("DEBUG * \n"); */
4645: cotvarv=cotvarv*cotvarvold;
4646: }
4647: iposold=ipos;
4648: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4649: cov[ioffset+ipos]=cotvarv*agexact;
4650: /* For products */
1.242 brouard 4651: }
1.349 brouard 4652:
1.242 brouard 4653: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4654: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4655: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4656: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4657: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4658: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4659: savm=oldm;
4660: oldm=newm;
1.126 brouard 4661: } /* end mult */
1.336 brouard 4662: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4663: /* But now since version 0.9 we anticipate for bias at large stepm.
4664: * If stepm is larger than one month (smallest stepm) and if the exact delay
4665: * (in months) between two waves is not a multiple of stepm, we rounded to
4666: * the nearest (and in case of equal distance, to the lowest) interval but now
4667: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4668: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4669: * probability in order to take into account the bias as a fraction of the way
4670: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4671: * -stepm/2 to stepm/2 .
4672: * For stepm=1 the results are the same as for previous versions of Imach.
4673: * For stepm > 1 the results are less biased than in previous versions.
4674: */
1.126 brouard 4675: s1=s[mw[mi][i]][i];
4676: s2=s[mw[mi+1][i]][i];
1.217 brouard 4677: /* if(s2==-1){ */
1.268 brouard 4678: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4679: /* /\* exit(1); *\/ */
4680: /* } */
1.126 brouard 4681: bbh=(double)bh[mi][i]/(double)stepm;
4682: /* bias is positive if real duration
4683: * is higher than the multiple of stepm and negative otherwise.
4684: */
4685: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4686: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4687: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4688: for (j=1,survp=0. ; j<=nlstate; j++)
4689: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4690: lli= log(survp);
1.126 brouard 4691: }else if (mle==1){
1.242 brouard 4692: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4693: } else if(mle==2){
1.242 brouard 4694: 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 4695: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4696: 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 4697: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4698: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4699: } else{ /* mle=0 back to 1 */
1.242 brouard 4700: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4701: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4702: } /* End of if */
4703: ipmx +=1;
4704: sw += weight[i];
4705: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4706: /* Printing covariates values for each contribution for checking */
1.343 brouard 4707: /* 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 4708: if(globpr){
1.246 brouard 4709: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4710: %11.6f %11.6f %11.6f ", \
1.242 brouard 4711: 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 4712: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4713: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4714: /* %11.6f %11.6f %11.6f ", \ */
4715: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4716: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4717: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4718: llt +=ll[k]*gipmx/gsw;
4719: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4720: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4721: }
1.343 brouard 4722: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4723: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4724: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4725: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4726: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4727: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4728: }
4729: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4730: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4731: if(ipos!=iposold){ /* Not a product or first of a product */
4732: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4733: /* printf(" %g",cov[ioffset+ipos]); */
4734: }else{
4735: fprintf(ficresilk,"*");
4736: /* printf("*"); */
1.342 brouard 4737: }
1.343 brouard 4738: iposold=ipos;
4739: }
1.349 brouard 4740: /* for (kk=1; kk<=cptcovage;kk++) { */
4741: /* if(!FixedV[Tvar[Tage[kk]]]){ */
4742: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
4743: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
4744: /* }else{ */
4745: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4746: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
4747: /* } */
4748: /* } */
4749: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4750: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4751: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4752: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4753: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4754: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4755: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4756: }else{ /* fixed covariate */
4757: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4758: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4759: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4760: }
4761: if(ipos!=iposold){ /* Not a product or first of a product */
4762: cotvarvold=cotvarv;
4763: }else{ /* A second product */
4764: /* printf("DEBUG * \n"); */
4765: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4766: }
1.349 brouard 4767: cotvarv=cotvarv*agexact;
4768: fprintf(ficresilk," %g*age",cotvarv);
4769: iposold=ipos;
4770: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4771: cov[ioffset+ipos]=cotvarv;
4772: /* For products */
1.343 brouard 4773: }
4774: /* printf("\n"); */
1.342 brouard 4775: /* } /\* End debugILK *\/ */
4776: fprintf(ficresilk,"\n");
4777: } /* End if globpr */
1.335 brouard 4778: } /* end of wave */
4779: } /* end of individual */
4780: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4781: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4782: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4783: if(globpr==0){ /* First time we count the contributions and weights */
4784: gipmx=ipmx;
4785: gsw=sw;
4786: }
1.343 brouard 4787: return -l;
1.126 brouard 4788: }
4789:
4790:
4791: /*************** function likelione ***********/
1.292 brouard 4792: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4793: {
4794: /* This routine should help understanding what is done with
4795: the selection of individuals/waves and
4796: to check the exact contribution to the likelihood.
4797: Plotting could be done.
1.342 brouard 4798: */
4799: void pstamp(FILE *ficres);
1.343 brouard 4800: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4801:
4802: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4803: strcpy(fileresilk,"ILK_");
1.202 brouard 4804: strcat(fileresilk,fileresu);
1.126 brouard 4805: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4806: printf("Problem with resultfile: %s\n", fileresilk);
4807: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4808: }
1.342 brouard 4809: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4810: 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");
4811: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4812: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4813: for(k=1; k<=nlstate; k++)
4814: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4815: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4816:
4817: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4818: for(kf=1;kf <= ncovf; kf++){
4819: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4820: /* printf("V%d",Tvar[TvarFind[kf]]); */
4821: }
4822: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4823: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4824: if(ipos!=iposold){ /* Not a product or first of a product */
4825: /* printf(" %d",ipos); */
4826: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4827: }else{
4828: /* printf("*"); */
4829: fprintf(ficresilk,"*");
1.343 brouard 4830: }
1.342 brouard 4831: iposold=ipos;
4832: }
4833: for (kk=1; kk<=cptcovage;kk++) {
4834: if(!FixedV[Tvar[Tage[kk]]]){
4835: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4836: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4837: }else{
4838: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4839: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4840: }
4841: }
4842: /* } /\* End if debugILK *\/ */
4843: /* printf("\n"); */
4844: fprintf(ficresilk,"\n");
4845: } /* End glogpri */
1.126 brouard 4846:
1.292 brouard 4847: *fretone=(*func)(p);
1.126 brouard 4848: if(*globpri !=0){
4849: fclose(ficresilk);
1.205 brouard 4850: if (mle ==0)
4851: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4852: else if(mle >=1)
4853: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4854: 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 4855: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4856:
1.207 brouard 4857: 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 4858: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4859: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4860: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4861:
4862: for (k=1; k<= nlstate ; k++) {
4863: 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 \
4864: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4865: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 4866: kvar=Tvar[TvarFind[kf]]; /* variable */
4867: 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]]);
4868: 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);
4869: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 4870: }
4871: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4872: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4873: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4874: /* 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]); */
4875: if(ipos!=iposold){ /* Not a product or first of a product */
4876: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4877: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4878: 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) */
4879: 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> \
4880: <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);
4881: } /* End only for dummies time varying (single?) */
4882: }else{ /* Useless product */
4883: /* printf("*"); */
4884: /* fprintf(ficresilk,"*"); */
4885: }
4886: iposold=ipos;
4887: } /* For each time varying covariate */
4888: } /* End loop on states */
4889:
4890: /* if(debugILK){ */
4891: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4892: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4893: /* for (k=1; k<= nlstate ; k++) { */
4894: /* 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> \ */
4895: /* <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]]); */
4896: /* } */
4897: /* } */
4898: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4899: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4900: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4901: /* /\* 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]); *\/ */
4902: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4903: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4904: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4905: /* 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) *\/ */
4906: /* for (k=1; k<= nlstate ; k++) { */
4907: /* 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> \ */
4908: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4909: /* } /\* End state *\/ */
4910: /* } /\* End only for dummies time varying (single?) *\/ */
4911: /* }else{ /\* Useless product *\/ */
4912: /* /\* printf("*"); *\/ */
4913: /* /\* fprintf(ficresilk,"*"); *\/ */
4914: /* } */
4915: /* iposold=ipos; */
4916: /* } /\* For each time varying covariate *\/ */
4917: /* }/\* End debugILK *\/ */
1.207 brouard 4918: fflush(fichtm);
1.343 brouard 4919: }/* End globpri */
1.126 brouard 4920: return;
4921: }
4922:
4923:
4924: /*********** Maximum Likelihood Estimation ***************/
4925:
4926: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4927: {
1.319 brouard 4928: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4929: double **xi;
4930: double fret;
4931: double fretone; /* Only one call to likelihood */
4932: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4933:
4934: #ifdef NLOPT
4935: int creturn;
4936: nlopt_opt opt;
4937: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4938: double *lb;
4939: double minf; /* the minimum objective value, upon return */
4940: double * p1; /* Shifted parameters from 0 instead of 1 */
4941: myfunc_data dinst, *d = &dinst;
4942: #endif
4943:
4944:
1.126 brouard 4945: xi=matrix(1,npar,1,npar);
4946: for (i=1;i<=npar;i++)
4947: for (j=1;j<=npar;j++)
4948: xi[i][j]=(i==j ? 1.0 : 0.0);
4949: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4950: strcpy(filerespow,"POW_");
1.126 brouard 4951: strcat(filerespow,fileres);
4952: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4953: printf("Problem with resultfile: %s\n", filerespow);
4954: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4955: }
4956: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4957: for (i=1;i<=nlstate;i++)
4958: for(j=1;j<=nlstate+ndeath;j++)
4959: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4960: fprintf(ficrespow,"\n");
1.162 brouard 4961: #ifdef POWELL
1.319 brouard 4962: #ifdef LINMINORIGINAL
4963: #else /* LINMINORIGINAL */
4964:
4965: flatdir=ivector(1,npar);
4966: for (j=1;j<=npar;j++) flatdir[j]=0;
4967: #endif /*LINMINORIGINAL */
4968:
4969: #ifdef FLATSUP
4970: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4971: /* reorganizing p by suppressing flat directions */
4972: for(i=1, jk=1; i <=nlstate; i++){
4973: for(k=1; k <=(nlstate+ndeath); k++){
4974: if (k != i) {
4975: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4976: if(flatdir[jk]==1){
4977: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4978: }
4979: for(j=1; j <=ncovmodel; j++){
4980: printf("%12.7f ",p[jk]);
4981: jk++;
4982: }
4983: printf("\n");
4984: }
4985: }
4986: }
4987: /* skipping */
4988: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4989: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4990: for(k=1; k <=(nlstate+ndeath); k++){
4991: if (k != i) {
4992: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4993: if(flatdir[jk]==1){
4994: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4995: for(j=1; j <=ncovmodel; jk++,j++){
4996: printf(" p[%d]=%12.7f",jk, p[jk]);
4997: /*q[jjk]=p[jk];*/
4998: }
4999: }else{
5000: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
5001: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
5002: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
5003: /*q[jjk]=p[jk];*/
5004: }
5005: }
5006: printf("\n");
5007: }
5008: fflush(stdout);
5009: }
5010: }
5011: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5012: #else /* FLATSUP */
1.126 brouard 5013: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 5014: #endif /* FLATSUP */
5015:
5016: #ifdef LINMINORIGINAL
5017: #else
5018: free_ivector(flatdir,1,npar);
5019: #endif /* LINMINORIGINAL*/
5020: #endif /* POWELL */
1.126 brouard 5021:
1.162 brouard 5022: #ifdef NLOPT
5023: #ifdef NEWUOA
5024: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
5025: #else
5026: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
5027: #endif
5028: lb=vector(0,npar-1);
5029: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
5030: nlopt_set_lower_bounds(opt, lb);
5031: nlopt_set_initial_step1(opt, 0.1);
5032:
5033: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5034: d->function = func;
5035: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5036: nlopt_set_min_objective(opt, myfunc, d);
5037: nlopt_set_xtol_rel(opt, ftol);
5038: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5039: printf("nlopt failed! %d\n",creturn);
5040: }
5041: else {
5042: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5043: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5044: iter=1; /* not equal */
5045: }
5046: nlopt_destroy(opt);
5047: #endif
1.319 brouard 5048: #ifdef FLATSUP
5049: /* npared = npar -flatd/ncovmodel; */
5050: /* xired= matrix(1,npared,1,npared); */
5051: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5052: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5053: /* free_matrix(xire,1,npared,1,npared); */
5054: #else /* FLATSUP */
5055: #endif /* FLATSUP */
1.126 brouard 5056: free_matrix(xi,1,npar,1,npar);
5057: fclose(ficrespow);
1.203 brouard 5058: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5059: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5060: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5061:
5062: }
5063:
5064: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5065: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5066: {
5067: double **a,**y,*x,pd;
1.203 brouard 5068: /* double **hess; */
1.164 brouard 5069: int i, j;
1.126 brouard 5070: int *indx;
5071:
5072: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5073: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5074: void lubksb(double **a, int npar, int *indx, double b[]) ;
5075: void ludcmp(double **a, int npar, int *indx, double *d) ;
5076: double gompertz(double p[]);
1.203 brouard 5077: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5078:
5079: printf("\nCalculation of the hessian matrix. Wait...\n");
5080: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5081: for (i=1;i<=npar;i++){
1.203 brouard 5082: printf("%d-",i);fflush(stdout);
5083: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5084:
5085: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5086:
5087: /* printf(" %f ",p[i]);
5088: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5089: }
5090:
5091: for (i=1;i<=npar;i++) {
5092: for (j=1;j<=npar;j++) {
5093: if (j>i) {
1.203 brouard 5094: printf(".%d-%d",i,j);fflush(stdout);
5095: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5096: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5097:
5098: hess[j][i]=hess[i][j];
5099: /*printf(" %lf ",hess[i][j]);*/
5100: }
5101: }
5102: }
5103: printf("\n");
5104: fprintf(ficlog,"\n");
5105:
5106: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5107: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5108:
5109: a=matrix(1,npar,1,npar);
5110: y=matrix(1,npar,1,npar);
5111: x=vector(1,npar);
5112: indx=ivector(1,npar);
5113: for (i=1;i<=npar;i++)
5114: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5115: ludcmp(a,npar,indx,&pd);
5116:
5117: for (j=1;j<=npar;j++) {
5118: for (i=1;i<=npar;i++) x[i]=0;
5119: x[j]=1;
5120: lubksb(a,npar,indx,x);
5121: for (i=1;i<=npar;i++){
5122: matcov[i][j]=x[i];
5123: }
5124: }
5125:
5126: printf("\n#Hessian matrix#\n");
5127: fprintf(ficlog,"\n#Hessian matrix#\n");
5128: for (i=1;i<=npar;i++) {
5129: for (j=1;j<=npar;j++) {
1.203 brouard 5130: printf("%.6e ",hess[i][j]);
5131: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5132: }
5133: printf("\n");
5134: fprintf(ficlog,"\n");
5135: }
5136:
1.203 brouard 5137: /* printf("\n#Covariance matrix#\n"); */
5138: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5139: /* for (i=1;i<=npar;i++) { */
5140: /* for (j=1;j<=npar;j++) { */
5141: /* printf("%.6e ",matcov[i][j]); */
5142: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5143: /* } */
5144: /* printf("\n"); */
5145: /* fprintf(ficlog,"\n"); */
5146: /* } */
5147:
1.126 brouard 5148: /* Recompute Inverse */
1.203 brouard 5149: /* for (i=1;i<=npar;i++) */
5150: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5151: /* ludcmp(a,npar,indx,&pd); */
5152:
5153: /* printf("\n#Hessian matrix recomputed#\n"); */
5154:
5155: /* for (j=1;j<=npar;j++) { */
5156: /* for (i=1;i<=npar;i++) x[i]=0; */
5157: /* x[j]=1; */
5158: /* lubksb(a,npar,indx,x); */
5159: /* for (i=1;i<=npar;i++){ */
5160: /* y[i][j]=x[i]; */
5161: /* printf("%.3e ",y[i][j]); */
5162: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5163: /* } */
5164: /* printf("\n"); */
5165: /* fprintf(ficlog,"\n"); */
5166: /* } */
5167:
5168: /* Verifying the inverse matrix */
5169: #ifdef DEBUGHESS
5170: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5171:
1.203 brouard 5172: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5173: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5174:
5175: for (j=1;j<=npar;j++) {
5176: for (i=1;i<=npar;i++){
1.203 brouard 5177: printf("%.2f ",y[i][j]);
5178: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5179: }
5180: printf("\n");
5181: fprintf(ficlog,"\n");
5182: }
1.203 brouard 5183: #endif
1.126 brouard 5184:
5185: free_matrix(a,1,npar,1,npar);
5186: free_matrix(y,1,npar,1,npar);
5187: free_vector(x,1,npar);
5188: free_ivector(indx,1,npar);
1.203 brouard 5189: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5190:
5191:
5192: }
5193:
5194: /*************** hessian matrix ****************/
5195: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5196: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5197: int i;
5198: int l=1, lmax=20;
1.203 brouard 5199: double k1,k2, res, fx;
1.132 brouard 5200: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5201: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5202: int k=0,kmax=10;
5203: double l1;
5204:
5205: fx=func(x);
5206: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5207: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5208: l1=pow(10,l);
5209: delts=delt;
5210: for(k=1 ; k <kmax; k=k+1){
5211: delt = delta*(l1*k);
5212: p2[theta]=x[theta] +delt;
1.145 brouard 5213: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5214: p2[theta]=x[theta]-delt;
5215: k2=func(p2)-fx;
5216: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5217: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5218:
1.203 brouard 5219: #ifdef DEBUGHESSII
1.126 brouard 5220: 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);
5221: 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);
5222: #endif
5223: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5224: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5225: k=kmax;
5226: }
5227: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5228: k=kmax; l=lmax*10;
1.126 brouard 5229: }
5230: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5231: delts=delt;
5232: }
1.203 brouard 5233: } /* End loop k */
1.126 brouard 5234: }
5235: delti[theta]=delts;
5236: return res;
5237:
5238: }
5239:
1.203 brouard 5240: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5241: {
5242: int i;
1.164 brouard 5243: int l=1, lmax=20;
1.126 brouard 5244: double k1,k2,k3,k4,res,fx;
1.132 brouard 5245: double p2[MAXPARM+1];
1.203 brouard 5246: int k, kmax=1;
5247: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5248:
5249: int firstime=0;
1.203 brouard 5250:
1.126 brouard 5251: fx=func(x);
1.203 brouard 5252: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5253: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5254: p2[thetai]=x[thetai]+delti[thetai]*k;
5255: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5256: k1=func(p2)-fx;
5257:
1.203 brouard 5258: p2[thetai]=x[thetai]+delti[thetai]*k;
5259: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5260: k2=func(p2)-fx;
5261:
1.203 brouard 5262: p2[thetai]=x[thetai]-delti[thetai]*k;
5263: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5264: k3=func(p2)-fx;
5265:
1.203 brouard 5266: p2[thetai]=x[thetai]-delti[thetai]*k;
5267: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5268: k4=func(p2)-fx;
1.203 brouard 5269: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5270: if(k1*k2*k3*k4 <0.){
1.208 brouard 5271: firstime=1;
1.203 brouard 5272: kmax=kmax+10;
1.208 brouard 5273: }
5274: if(kmax >=10 || firstime ==1){
1.246 brouard 5275: 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);
5276: 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 5277: 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);
5278: 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);
5279: }
5280: #ifdef DEBUGHESSIJ
5281: v1=hess[thetai][thetai];
5282: v2=hess[thetaj][thetaj];
5283: cv12=res;
5284: /* Computing eigen value of Hessian matrix */
5285: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5286: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5287: if ((lc2 <0) || (lc1 <0) ){
5288: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5289: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5290: 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);
5291: 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);
5292: }
1.126 brouard 5293: #endif
5294: }
5295: return res;
5296: }
5297:
1.203 brouard 5298: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5299: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5300: /* { */
5301: /* int i; */
5302: /* int l=1, lmax=20; */
5303: /* double k1,k2,k3,k4,res,fx; */
5304: /* double p2[MAXPARM+1]; */
5305: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5306: /* int k=0,kmax=10; */
5307: /* double l1; */
5308:
5309: /* fx=func(x); */
5310: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5311: /* l1=pow(10,l); */
5312: /* delts=delt; */
5313: /* for(k=1 ; k <kmax; k=k+1){ */
5314: /* delt = delti*(l1*k); */
5315: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5316: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5317: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5318: /* k1=func(p2)-fx; */
5319:
5320: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5321: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5322: /* k2=func(p2)-fx; */
5323:
5324: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5325: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5326: /* k3=func(p2)-fx; */
5327:
5328: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5329: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5330: /* k4=func(p2)-fx; */
5331: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5332: /* #ifdef DEBUGHESSIJ */
5333: /* 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); */
5334: /* 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); */
5335: /* #endif */
5336: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5337: /* k=kmax; */
5338: /* } */
5339: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5340: /* k=kmax; l=lmax*10; */
5341: /* } */
5342: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5343: /* delts=delt; */
5344: /* } */
5345: /* } /\* End loop k *\/ */
5346: /* } */
5347: /* delti[theta]=delts; */
5348: /* return res; */
5349: /* } */
5350:
5351:
1.126 brouard 5352: /************** Inverse of matrix **************/
5353: void ludcmp(double **a, int n, int *indx, double *d)
5354: {
5355: int i,imax,j,k;
5356: double big,dum,sum,temp;
5357: double *vv;
5358:
5359: vv=vector(1,n);
5360: *d=1.0;
5361: for (i=1;i<=n;i++) {
5362: big=0.0;
5363: for (j=1;j<=n;j++)
5364: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5365: if (big == 0.0){
5366: printf(" Singular Hessian matrix at row %d:\n",i);
5367: for (j=1;j<=n;j++) {
5368: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5369: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5370: }
5371: fflush(ficlog);
5372: fclose(ficlog);
5373: nrerror("Singular matrix in routine ludcmp");
5374: }
1.126 brouard 5375: vv[i]=1.0/big;
5376: }
5377: for (j=1;j<=n;j++) {
5378: for (i=1;i<j;i++) {
5379: sum=a[i][j];
5380: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5381: a[i][j]=sum;
5382: }
5383: big=0.0;
5384: for (i=j;i<=n;i++) {
5385: sum=a[i][j];
5386: for (k=1;k<j;k++)
5387: sum -= a[i][k]*a[k][j];
5388: a[i][j]=sum;
5389: if ( (dum=vv[i]*fabs(sum)) >= big) {
5390: big=dum;
5391: imax=i;
5392: }
5393: }
5394: if (j != imax) {
5395: for (k=1;k<=n;k++) {
5396: dum=a[imax][k];
5397: a[imax][k]=a[j][k];
5398: a[j][k]=dum;
5399: }
5400: *d = -(*d);
5401: vv[imax]=vv[j];
5402: }
5403: indx[j]=imax;
5404: if (a[j][j] == 0.0) a[j][j]=TINY;
5405: if (j != n) {
5406: dum=1.0/(a[j][j]);
5407: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5408: }
5409: }
5410: free_vector(vv,1,n); /* Doesn't work */
5411: ;
5412: }
5413:
5414: void lubksb(double **a, int n, int *indx, double b[])
5415: {
5416: int i,ii=0,ip,j;
5417: double sum;
5418:
5419: for (i=1;i<=n;i++) {
5420: ip=indx[i];
5421: sum=b[ip];
5422: b[ip]=b[i];
5423: if (ii)
5424: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5425: else if (sum) ii=i;
5426: b[i]=sum;
5427: }
5428: for (i=n;i>=1;i--) {
5429: sum=b[i];
5430: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5431: b[i]=sum/a[i][i];
5432: }
5433: }
5434:
5435: void pstamp(FILE *fichier)
5436: {
1.196 brouard 5437: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5438: }
5439:
1.297 brouard 5440: void date2dmy(double date,double *day, double *month, double *year){
5441: double yp=0., yp1=0., yp2=0.;
5442:
5443: yp1=modf(date,&yp);/* extracts integral of date in yp and
5444: fractional in yp1 */
5445: *year=yp;
5446: yp2=modf((yp1*12),&yp);
5447: *month=yp;
5448: yp1=modf((yp2*30.5),&yp);
5449: *day=yp;
5450: if(*day==0) *day=1;
5451: if(*month==0) *month=1;
5452: }
5453:
1.253 brouard 5454:
5455:
1.126 brouard 5456: /************ Frequencies ********************/
1.251 brouard 5457: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5458: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5459: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5460: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5461: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5462: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5463: int iind=0, iage=0;
5464: int mi; /* Effective wave */
5465: int first;
5466: double ***freq; /* Frequencies */
1.268 brouard 5467: 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 */
5468: 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 5469: double *meanq, *stdq, *idq;
1.226 brouard 5470: double **meanqt;
5471: double *pp, **prop, *posprop, *pospropt;
5472: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5473: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5474: double agebegin, ageend;
5475:
5476: pp=vector(1,nlstate);
1.251 brouard 5477: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5478: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5479: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5480: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5481: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5482: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5483: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5484: meanqt=matrix(1,lastpass,1,nqtveff);
5485: strcpy(fileresp,"P_");
5486: strcat(fileresp,fileresu);
5487: /*strcat(fileresphtm,fileresu);*/
5488: if((ficresp=fopen(fileresp,"w"))==NULL) {
5489: printf("Problem with prevalence resultfile: %s\n", fileresp);
5490: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5491: exit(0);
5492: }
1.240 brouard 5493:
1.226 brouard 5494: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5495: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5496: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5497: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5498: fflush(ficlog);
5499: exit(70);
5500: }
5501: else{
5502: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5503: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5504: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5505: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5506: }
1.319 brouard 5507: 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 5508:
1.226 brouard 5509: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5510: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5511: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5512: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5513: fflush(ficlog);
5514: exit(70);
1.240 brouard 5515: } else{
1.226 brouard 5516: 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 5517: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5518: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5519: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5520: }
1.319 brouard 5521: 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 5522:
1.253 brouard 5523: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5524: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5525: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5526: j1=0;
1.126 brouard 5527:
1.227 brouard 5528: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5529: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5530: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5531: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5532:
5533:
1.226 brouard 5534: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5535: reference=low_education V1=0,V2=0
5536: med_educ V1=1 V2=0,
5537: high_educ V1=0 V2=1
1.330 brouard 5538: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5539: */
1.249 brouard 5540: dateintsum=0;
5541: k2cpt=0;
5542:
1.253 brouard 5543: if(cptcoveff == 0 )
1.265 brouard 5544: nl=1; /* Constant and age model only */
1.253 brouard 5545: else
5546: nl=2;
1.265 brouard 5547:
5548: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5549: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5550: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5551: * freq[s1][s2][iage] =0.
5552: * Loop on iind
5553: * ++freq[s1][s2][iage] weighted
5554: * end iind
5555: * if covariate and j!0
5556: * headers Variable on one line
5557: * endif cov j!=0
5558: * header of frequency table by age
5559: * Loop on age
5560: * pp[s1]+=freq[s1][s2][iage] weighted
5561: * pos+=freq[s1][s2][iage] weighted
5562: * Loop on s1 initial state
5563: * fprintf(ficresp
5564: * end s1
5565: * end age
5566: * if j!=0 computes starting values
5567: * end compute starting values
5568: * end j1
5569: * end nl
5570: */
1.253 brouard 5571: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5572: if(nj==1)
5573: j=0; /* First pass for the constant */
1.265 brouard 5574: else{
1.335 brouard 5575: 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 5576: }
1.251 brouard 5577: first=1;
1.332 brouard 5578: 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 5579: posproptt=0.;
1.330 brouard 5580: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5581: scanf("%d", i);*/
5582: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5583: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5584: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5585: freq[i][s2][m]=0;
1.251 brouard 5586:
5587: for (i=1; i<=nlstate; i++) {
1.240 brouard 5588: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5589: prop[i][m]=0;
5590: posprop[i]=0;
5591: pospropt[i]=0;
5592: }
1.283 brouard 5593: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5594: idq[z1]=0.;
5595: meanq[z1]=0.;
5596: stdq[z1]=0.;
1.283 brouard 5597: }
5598: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5599: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5600: /* meanqt[m][z1]=0.; */
5601: /* } */
5602: /* } */
1.251 brouard 5603: /* dateintsum=0; */
5604: /* k2cpt=0; */
5605:
1.265 brouard 5606: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5607: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5608: bool=1;
5609: if(j !=0){
5610: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5611: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5612: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5613: /* if(Tvaraff[z1] ==-20){ */
5614: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5615: /* }else if(Tvaraff[z1] ==-10){ */
5616: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5617: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5618: /* 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); */
5619: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5620: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5621: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5622: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5623: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5624: /* 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", */
5625: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5626: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5627: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5628: } /* Onlyf fixed */
5629: } /* end z1 */
1.335 brouard 5630: } /* cptcoveff > 0 */
1.251 brouard 5631: } /* end any */
5632: }/* end j==0 */
1.265 brouard 5633: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5634: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5635: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5636: m=mw[mi][iind];
5637: if(j!=0){
5638: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5639: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5640: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5641: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5642: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5643: 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 5644: value is -1, we don't select. It differs from the
5645: constant and age model which counts them. */
5646: bool=0; /* not selected */
5647: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5648: /* i1=Tvaraff[z1]; */
5649: /* i2=TnsdVar[i1]; */
5650: /* i3=nbcode[i1][i2]; */
5651: /* i4=covar[i1][iind]; */
5652: /* if(i4 != i3){ */
5653: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5654: bool=0;
5655: }
5656: }
5657: }
5658: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5659: } /* end j==0 */
5660: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5661: if(bool==1){ /*Selected */
1.251 brouard 5662: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5663: and mw[mi+1][iind]. dh depends on stepm. */
5664: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5665: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5666: if(m >=firstpass && m <=lastpass){
5667: k2=anint[m][iind]+(mint[m][iind]/12.);
5668: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5669: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5670: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5671: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5672: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5673: if (m<lastpass) {
5674: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5675: /* 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]); */
5676: if(s[m][iind]==-1)
5677: 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.));
5678: 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 5679: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5680: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5681: idq[z1]=idq[z1]+weight[iind];
5682: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5683: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5684: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5685: }
1.284 brouard 5686: }
1.251 brouard 5687: /* if((int)agev[m][iind] == 55) */
5688: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5689: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5690: 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 5691: }
1.251 brouard 5692: } /* end if between passes */
5693: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5694: dateintsum=dateintsum+k2; /* on all covariates ?*/
5695: k2cpt++;
5696: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5697: }
1.251 brouard 5698: }else{
5699: bool=1;
5700: }/* end bool 2 */
5701: } /* end m */
1.284 brouard 5702: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5703: /* idq[z1]=idq[z1]+weight[iind]; */
5704: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5705: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5706: /* } */
1.251 brouard 5707: } /* end bool */
5708: } /* end iind = 1 to imx */
1.319 brouard 5709: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5710: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5711:
5712:
5713: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5714: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5715: pstamp(ficresp);
1.335 brouard 5716: if (cptcoveff>0 && j!=0){
1.265 brouard 5717: pstamp(ficresp);
1.251 brouard 5718: printf( "\n#********** Variable ");
5719: fprintf(ficresp, "\n#********** Variable ");
5720: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5721: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5722: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5723: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5724: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5725: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5726: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5727: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5728: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5729: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5730: }else{
1.330 brouard 5731: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5732: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5733: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5734: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5735: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5736: }
5737: }
5738: printf( "**********\n#");
5739: fprintf(ficresp, "**********\n#");
5740: fprintf(ficresphtm, "**********</h3>\n");
5741: fprintf(ficresphtmfr, "**********</h3>\n");
5742: fprintf(ficlog, "**********\n");
5743: }
1.284 brouard 5744: /*
5745: Printing means of quantitative variables if any
5746: */
5747: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5748: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5749: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5750: if(weightopt==1){
5751: printf(" Weighted mean and standard deviation of");
5752: fprintf(ficlog," Weighted mean and standard deviation of");
5753: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5754: }
1.311 brouard 5755: /* mu = \frac{w x}{\sum w}
5756: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5757: */
5758: 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]));
5759: 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]));
5760: 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 5761: }
5762: /* for (z1=1; z1<= nqtveff; z1++) { */
5763: /* for(m=1;m<=lastpass;m++){ */
5764: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5765: /* } */
5766: /* } */
1.283 brouard 5767:
1.251 brouard 5768: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5769: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5770: fprintf(ficresp, " Age");
1.335 brouard 5771: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5772: 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]]);
5773: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5774: }
1.251 brouard 5775: for(i=1; i<=nlstate;i++) {
1.335 brouard 5776: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5777: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5778: }
1.335 brouard 5779: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5780: fprintf(ficresphtm, "\n");
5781:
5782: /* Header of frequency table by age */
5783: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5784: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5785: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5786: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5787: if(s2!=0 && m!=0)
5788: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5789: }
1.226 brouard 5790: }
1.251 brouard 5791: fprintf(ficresphtmfr, "\n");
5792:
5793: /* For each age */
5794: for(iage=iagemin; iage <= iagemax+3; iage++){
5795: fprintf(ficresphtm,"<tr>");
5796: if(iage==iagemax+1){
5797: fprintf(ficlog,"1");
5798: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5799: }else if(iage==iagemax+2){
5800: fprintf(ficlog,"0");
5801: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5802: }else if(iage==iagemax+3){
5803: fprintf(ficlog,"Total");
5804: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5805: }else{
1.240 brouard 5806: if(first==1){
1.251 brouard 5807: first=0;
5808: printf("See log file for details...\n");
5809: }
5810: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5811: fprintf(ficlog,"Age %d", iage);
5812: }
1.265 brouard 5813: for(s1=1; s1 <=nlstate ; s1++){
5814: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5815: pp[s1] += freq[s1][m][iage];
1.251 brouard 5816: }
1.265 brouard 5817: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5818: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5819: pos += freq[s1][m][iage];
5820: if(pp[s1]>=1.e-10){
1.251 brouard 5821: if(first==1){
1.265 brouard 5822: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5823: }
1.265 brouard 5824: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5825: }else{
5826: if(first==1)
1.265 brouard 5827: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5828: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5829: }
5830: }
5831:
1.265 brouard 5832: for(s1=1; s1 <=nlstate ; s1++){
5833: /* posprop[s1]=0; */
5834: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5835: pp[s1] += freq[s1][m][iage];
5836: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5837:
5838: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5839: pos += pp[s1]; /* pos is the total number of transitions until this age */
5840: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5841: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5842: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5843: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5844: }
5845:
5846: /* Writing ficresp */
1.335 brouard 5847: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5848: if( iage <= iagemax){
5849: fprintf(ficresp," %d",iage);
5850: }
5851: }else if( nj==2){
5852: if( iage <= iagemax){
5853: fprintf(ficresp," %d",iage);
1.335 brouard 5854: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5855: }
1.240 brouard 5856: }
1.265 brouard 5857: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5858: if(pos>=1.e-5){
1.251 brouard 5859: if(first==1)
1.265 brouard 5860: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5861: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5862: }else{
5863: if(first==1)
1.265 brouard 5864: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5865: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5866: }
5867: if( iage <= iagemax){
5868: if(pos>=1.e-5){
1.335 brouard 5869: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5870: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5871: }else if( nj==2){
5872: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5873: }
5874: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5875: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5876: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5877: } else{
1.335 brouard 5878: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5879: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5880: }
1.240 brouard 5881: }
1.265 brouard 5882: pospropt[s1] +=posprop[s1];
5883: } /* end loop s1 */
1.251 brouard 5884: /* pospropt=0.; */
1.265 brouard 5885: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5886: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5887: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5888: if(first==1){
1.265 brouard 5889: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5890: }
1.265 brouard 5891: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5892: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5893: }
1.265 brouard 5894: if(s1!=0 && m!=0)
5895: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5896: }
1.265 brouard 5897: } /* end loop s1 */
1.251 brouard 5898: posproptt=0.;
1.265 brouard 5899: for(s1=1; s1 <=nlstate; s1++){
5900: posproptt += pospropt[s1];
1.251 brouard 5901: }
5902: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5903: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5904: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5905: if(iage <= iagemax)
5906: fprintf(ficresp,"\n");
1.240 brouard 5907: }
1.251 brouard 5908: if(first==1)
5909: printf("Others in log...\n");
5910: fprintf(ficlog,"\n");
5911: } /* end loop age iage */
1.265 brouard 5912:
1.251 brouard 5913: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5914: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5915: if(posproptt < 1.e-5){
1.265 brouard 5916: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5917: }else{
1.265 brouard 5918: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5919: }
1.226 brouard 5920: }
1.251 brouard 5921: fprintf(ficresphtm,"</tr>\n");
5922: fprintf(ficresphtm,"</table>\n");
5923: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5924: if(posproptt < 1.e-5){
1.251 brouard 5925: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5926: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5927: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5928: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5929: invalidvarcomb[j1]=1;
1.226 brouard 5930: }else{
1.338 brouard 5931: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5932: invalidvarcomb[j1]=0;
1.226 brouard 5933: }
1.251 brouard 5934: fprintf(ficresphtmfr,"</table>\n");
5935: fprintf(ficlog,"\n");
5936: if(j!=0){
5937: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5938: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5939: for(k=1; k <=(nlstate+ndeath); k++){
5940: if (k != i) {
1.265 brouard 5941: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5942: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5943: if(j1==1){ /* All dummy covariates to zero */
5944: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5945: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5946: printf("%d%d ",i,k);
5947: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5948: 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]));
5949: 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]));
5950: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5951: }
1.253 brouard 5952: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5953: for(iage=iagemin; iage <= iagemax+3; iage++){
5954: x[iage]= (double)iage;
5955: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5956: /* 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 5957: }
1.268 brouard 5958: /* Some are not finite, but linreg will ignore these ages */
5959: no=0;
1.253 brouard 5960: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5961: pstart[s1]=b;
5962: pstart[s1-1]=a;
1.252 brouard 5963: }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 */
5964: 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]);
5965: 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 5966: 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 5967: printf("%d%d ",i,k);
5968: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5969: 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 5970: }else{ /* Other cases, like quantitative fixed or varying covariates */
5971: ;
5972: }
5973: /* printf("%12.7f )", param[i][jj][k]); */
5974: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5975: s1++;
1.251 brouard 5976: } /* end jj */
5977: } /* end k!= i */
5978: } /* end k */
1.265 brouard 5979: } /* end i, s1 */
1.251 brouard 5980: } /* end j !=0 */
5981: } /* end selected combination of covariate j1 */
5982: if(j==0){ /* We can estimate starting values from the occurences in each case */
5983: printf("#Freqsummary: Starting values for the constants:\n");
5984: fprintf(ficlog,"\n");
1.265 brouard 5985: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5986: for(k=1; k <=(nlstate+ndeath); k++){
5987: if (k != i) {
5988: printf("%d%d ",i,k);
5989: fprintf(ficlog,"%d%d ",i,k);
5990: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5991: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5992: if(jj==1){ /* Age has to be done */
1.265 brouard 5993: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5994: 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]));
5995: 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 5996: }
5997: /* printf("%12.7f )", param[i][jj][k]); */
5998: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5999: s1++;
1.250 brouard 6000: }
1.251 brouard 6001: printf("\n");
6002: fprintf(ficlog,"\n");
1.250 brouard 6003: }
6004: }
1.284 brouard 6005: } /* end of state i */
1.251 brouard 6006: printf("#Freqsummary\n");
6007: fprintf(ficlog,"\n");
1.265 brouard 6008: for(s1=-1; s1 <=nlstate+ndeath; s1++){
6009: for(s2=-1; s2 <=nlstate+ndeath; s2++){
6010: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
6011: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6012: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6013: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
6014: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
6015: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 6016: /* } */
6017: }
1.265 brouard 6018: } /* end loop s1 */
1.251 brouard 6019:
6020: printf("\n");
6021: fprintf(ficlog,"\n");
6022: } /* end j=0 */
1.249 brouard 6023: } /* end j */
1.252 brouard 6024:
1.253 brouard 6025: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 6026: for(i=1, jk=1; i <=nlstate; i++){
6027: for(j=1; j <=nlstate+ndeath; j++){
6028: if(j!=i){
6029: /*ca[0]= k+'a'-1;ca[1]='\0';*/
6030: printf("%1d%1d",i,j);
6031: fprintf(ficparo,"%1d%1d",i,j);
6032: for(k=1; k<=ncovmodel;k++){
6033: /* printf(" %lf",param[i][j][k]); */
6034: /* fprintf(ficparo," %lf",param[i][j][k]); */
6035: p[jk]=pstart[jk];
6036: printf(" %f ",pstart[jk]);
6037: fprintf(ficparo," %f ",pstart[jk]);
6038: jk++;
6039: }
6040: printf("\n");
6041: fprintf(ficparo,"\n");
6042: }
6043: }
6044: }
6045: } /* end mle=-2 */
1.226 brouard 6046: dateintmean=dateintsum/k2cpt;
1.296 brouard 6047: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6048:
1.226 brouard 6049: fclose(ficresp);
6050: fclose(ficresphtm);
6051: fclose(ficresphtmfr);
1.283 brouard 6052: free_vector(idq,1,nqfveff);
1.226 brouard 6053: free_vector(meanq,1,nqfveff);
1.284 brouard 6054: free_vector(stdq,1,nqfveff);
1.226 brouard 6055: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6056: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6057: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6058: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6059: free_vector(pospropt,1,nlstate);
6060: free_vector(posprop,1,nlstate);
1.251 brouard 6061: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6062: free_vector(pp,1,nlstate);
6063: /* End of freqsummary */
6064: }
1.126 brouard 6065:
1.268 brouard 6066: /* Simple linear regression */
6067: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6068:
6069: /* y=a+bx regression */
6070: double sumx = 0.0; /* sum of x */
6071: double sumx2 = 0.0; /* sum of x**2 */
6072: double sumxy = 0.0; /* sum of x * y */
6073: double sumy = 0.0; /* sum of y */
6074: double sumy2 = 0.0; /* sum of y**2 */
6075: double sume2 = 0.0; /* sum of square or residuals */
6076: double yhat;
6077:
6078: double denom=0;
6079: int i;
6080: int ne=*no;
6081:
6082: for ( i=ifi, ne=0;i<=ila;i++) {
6083: if(!isfinite(x[i]) || !isfinite(y[i])){
6084: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6085: continue;
6086: }
6087: ne=ne+1;
6088: sumx += x[i];
6089: sumx2 += x[i]*x[i];
6090: sumxy += x[i] * y[i];
6091: sumy += y[i];
6092: sumy2 += y[i]*y[i];
6093: denom = (ne * sumx2 - sumx*sumx);
6094: /* 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); */
6095: }
6096:
6097: denom = (ne * sumx2 - sumx*sumx);
6098: if (denom == 0) {
6099: // vertical, slope m is infinity
6100: *b = INFINITY;
6101: *a = 0;
6102: if (r) *r = 0;
6103: return 1;
6104: }
6105:
6106: *b = (ne * sumxy - sumx * sumy) / denom;
6107: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6108: if (r!=NULL) {
6109: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6110: sqrt((sumx2 - sumx*sumx/ne) *
6111: (sumy2 - sumy*sumy/ne));
6112: }
6113: *no=ne;
6114: for ( i=ifi, ne=0;i<=ila;i++) {
6115: if(!isfinite(x[i]) || !isfinite(y[i])){
6116: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6117: continue;
6118: }
6119: ne=ne+1;
6120: yhat = y[i] - *a -*b* x[i];
6121: sume2 += yhat * yhat ;
6122:
6123: denom = (ne * sumx2 - sumx*sumx);
6124: /* 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); */
6125: }
6126: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6127: *sa= *sb * sqrt(sumx2/ne);
6128:
6129: return 0;
6130: }
6131:
1.126 brouard 6132: /************ Prevalence ********************/
1.227 brouard 6133: 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)
6134: {
6135: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6136: in each health status at the date of interview (if between dateprev1 and dateprev2).
6137: We still use firstpass and lastpass as another selection.
6138: */
1.126 brouard 6139:
1.227 brouard 6140: int i, m, jk, j1, bool, z1,j, iv;
6141: int mi; /* Effective wave */
6142: int iage;
6143: double agebegin, ageend;
6144:
6145: double **prop;
6146: double posprop;
6147: double y2; /* in fractional years */
6148: int iagemin, iagemax;
6149: int first; /** to stop verbosity which is redirected to log file */
6150:
6151: iagemin= (int) agemin;
6152: iagemax= (int) agemax;
6153: /*pp=vector(1,nlstate);*/
1.251 brouard 6154: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6155: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6156: j1=0;
1.222 brouard 6157:
1.227 brouard 6158: /*j=cptcoveff;*/
6159: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6160:
1.288 brouard 6161: first=0;
1.335 brouard 6162: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6163: for (i=1; i<=nlstate; i++)
1.251 brouard 6164: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6165: prop[i][iage]=0.0;
6166: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6167: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6168: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6169:
6170: for (i=1; i<=imx; i++) { /* Each individual */
6171: bool=1;
6172: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6173: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6174: m=mw[mi][i];
6175: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6176: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6177: for (z1=1; z1<=cptcoveff; z1++){
6178: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6179: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6180: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6181: bool=0;
6182: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6183: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6184: bool=0;
6185: }
6186: }
6187: if(bool==1){ /* Otherwise we skip that wave/person */
6188: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6189: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6190: if(m >=firstpass && m <=lastpass){
6191: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6192: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6193: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6194: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6195: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6196: 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);
6197: exit(1);
6198: }
6199: if (s[m][i]>0 && s[m][i]<=nlstate) {
6200: /*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]]);*/
6201: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6202: prop[s[m][i]][iagemax+3] += weight[i];
6203: } /* end valid statuses */
6204: } /* end selection of dates */
6205: } /* end selection of waves */
6206: } /* end bool */
6207: } /* end wave */
6208: } /* end individual */
6209: for(i=iagemin; i <= iagemax+3; i++){
6210: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6211: posprop += prop[jk][i];
6212: }
6213:
6214: for(jk=1; jk <=nlstate ; jk++){
6215: if( i <= iagemax){
6216: if(posprop>=1.e-5){
6217: probs[i][jk][j1]= prop[jk][i]/posprop;
6218: } else{
1.288 brouard 6219: if(!first){
6220: first=1;
1.266 brouard 6221: 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]);
6222: }else{
1.288 brouard 6223: 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 6224: }
6225: }
6226: }
6227: }/* end jk */
6228: }/* end i */
1.222 brouard 6229: /*} *//* end i1 */
1.227 brouard 6230: } /* end j1 */
1.222 brouard 6231:
1.227 brouard 6232: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6233: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6234: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6235: } /* End of prevalence */
1.126 brouard 6236:
6237: /************* Waves Concatenation ***************/
6238:
6239: 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)
6240: {
1.298 brouard 6241: /* 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 6242: Death is a valid wave (if date is known).
6243: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6244: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6245: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6246: */
1.126 brouard 6247:
1.224 brouard 6248: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6249: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6250: double sum=0., jmean=0.;*/
1.224 brouard 6251: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6252: int j, k=0,jk, ju, jl;
6253: double sum=0.;
6254: first=0;
1.214 brouard 6255: firstwo=0;
1.217 brouard 6256: firsthree=0;
1.218 brouard 6257: firstfour=0;
1.164 brouard 6258: jmin=100000;
1.126 brouard 6259: jmax=-1;
6260: jmean=0.;
1.224 brouard 6261:
6262: /* Treating live states */
1.214 brouard 6263: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6264: mi=0; /* First valid wave */
1.227 brouard 6265: mli=0; /* Last valid wave */
1.309 brouard 6266: m=firstpass; /* Loop on waves */
6267: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6268: 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 */
6269: mli=m-1;/* mw[++mi][i]=m-1; */
6270: }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 6271: 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 6272: mli=m;
1.224 brouard 6273: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6274: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6275: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6276: }
1.309 brouard 6277: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6278: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6279: break;
1.224 brouard 6280: #else
1.317 brouard 6281: 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 6282: if(firsthree == 0){
1.302 brouard 6283: 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 6284: firsthree=1;
1.317 brouard 6285: }else if(firsthree >=1 && firsthree < 10){
6286: 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);
6287: firsthree++;
6288: }else if(firsthree == 10){
6289: printf("Information, too many Information flags: no more reported to log either\n");
6290: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6291: firsthree++;
6292: }else{
6293: firsthree++;
1.227 brouard 6294: }
1.309 brouard 6295: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6296: mli=m;
6297: }
6298: if(s[m][i]==-2){ /* Vital status is really unknown */
6299: nbwarn++;
1.309 brouard 6300: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6301: 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);
6302: 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);
6303: }
6304: break;
6305: }
6306: break;
1.224 brouard 6307: #endif
1.227 brouard 6308: }/* End m >= lastpass */
1.126 brouard 6309: }/* end while */
1.224 brouard 6310:
1.227 brouard 6311: /* 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 6312: /* After last pass */
1.224 brouard 6313: /* Treating death states */
1.214 brouard 6314: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6315: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6316: /* } */
1.126 brouard 6317: mi++; /* Death is another wave */
6318: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6319: /* Only death is a correct wave */
1.126 brouard 6320: mw[mi][i]=m;
1.257 brouard 6321: } /* else not in a death state */
1.224 brouard 6322: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6323: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6324: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6325: 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 6326: nbwarn++;
6327: if(firstfiv==0){
1.309 brouard 6328: 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 6329: firstfiv=1;
6330: }else{
1.309 brouard 6331: 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 6332: }
1.309 brouard 6333: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6334: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6335: nberr++;
6336: if(firstwo==0){
1.309 brouard 6337: 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 6338: firstwo=1;
6339: }
1.309 brouard 6340: 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 6341: }
1.257 brouard 6342: }else{ /* if date of interview is unknown */
1.227 brouard 6343: /* death is known but not confirmed by death status at any wave */
6344: if(firstfour==0){
1.309 brouard 6345: 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 6346: firstfour=1;
6347: }
1.309 brouard 6348: 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 6349: }
1.224 brouard 6350: } /* end if date of death is known */
6351: #endif
1.309 brouard 6352: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6353: /* wav[i]=mw[mi][i]; */
1.126 brouard 6354: if(mi==0){
6355: nbwarn++;
6356: if(first==0){
1.227 brouard 6357: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6358: first=1;
1.126 brouard 6359: }
6360: if(first==1){
1.227 brouard 6361: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6362: }
6363: } /* end mi==0 */
6364: } /* End individuals */
1.214 brouard 6365: /* wav and mw are no more changed */
1.223 brouard 6366:
1.317 brouard 6367: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6368: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6369:
6370:
1.126 brouard 6371: for(i=1; i<=imx; i++){
6372: for(mi=1; mi<wav[i];mi++){
6373: if (stepm <=0)
1.227 brouard 6374: dh[mi][i]=1;
1.126 brouard 6375: else{
1.260 brouard 6376: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6377: if (agedc[i] < 2*AGESUP) {
6378: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6379: if(j==0) j=1; /* Survives at least one month after exam */
6380: else if(j<0){
6381: nberr++;
6382: 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]);
6383: j=1; /* Temporary Dangerous patch */
6384: 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);
6385: 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]);
6386: 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);
6387: }
6388: k=k+1;
6389: if (j >= jmax){
6390: jmax=j;
6391: ijmax=i;
6392: }
6393: if (j <= jmin){
6394: jmin=j;
6395: ijmin=i;
6396: }
6397: sum=sum+j;
6398: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6399: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6400: }
6401: }
6402: else{
6403: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6404: /* 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 6405:
1.227 brouard 6406: k=k+1;
6407: if (j >= jmax) {
6408: jmax=j;
6409: ijmax=i;
6410: }
6411: else if (j <= jmin){
6412: jmin=j;
6413: ijmin=i;
6414: }
6415: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6416: /*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]);*/
6417: if(j<0){
6418: nberr++;
6419: 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]);
6420: 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]);
6421: }
6422: sum=sum+j;
6423: }
6424: jk= j/stepm;
6425: jl= j -jk*stepm;
6426: ju= j -(jk+1)*stepm;
6427: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6428: if(jl==0){
6429: dh[mi][i]=jk;
6430: bh[mi][i]=0;
6431: }else{ /* We want a negative bias in order to only have interpolation ie
6432: * to avoid the price of an extra matrix product in likelihood */
6433: dh[mi][i]=jk+1;
6434: bh[mi][i]=ju;
6435: }
6436: }else{
6437: if(jl <= -ju){
6438: dh[mi][i]=jk;
6439: bh[mi][i]=jl; /* bias is positive if real duration
6440: * is higher than the multiple of stepm and negative otherwise.
6441: */
6442: }
6443: else{
6444: dh[mi][i]=jk+1;
6445: bh[mi][i]=ju;
6446: }
6447: if(dh[mi][i]==0){
6448: dh[mi][i]=1; /* At least one step */
6449: bh[mi][i]=ju; /* At least one step */
6450: /* 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);*/
6451: }
6452: } /* end if mle */
1.126 brouard 6453: }
6454: } /* end wave */
6455: }
6456: jmean=sum/k;
6457: 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 6458: 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 6459: }
1.126 brouard 6460:
6461: /*********** Tricode ****************************/
1.220 brouard 6462: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6463: {
6464: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6465: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6466: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6467: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6468: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6469: */
1.130 brouard 6470:
1.242 brouard 6471: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6472: int modmaxcovj=0; /* Modality max of covariates j */
6473: int cptcode=0; /* Modality max of covariates j */
6474: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6475:
6476:
1.242 brouard 6477: /* cptcoveff=0; */
6478: /* *cptcov=0; */
1.126 brouard 6479:
1.242 brouard 6480: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6481: for (k=1; k <= maxncov; k++)
6482: for(j=1; j<=2; j++)
6483: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6484:
1.242 brouard 6485: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6486: 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 6487: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6488: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 6489: 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 6490: switch(Fixed[k]) {
6491: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6492: modmaxcovj=0;
6493: modmincovj=0;
1.242 brouard 6494: 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 6495: /* 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 6496: ij=(int)(covar[Tvar[k]][i]);
6497: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6498: * If product of Vn*Vm, still boolean *:
6499: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6500: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6501: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6502: modality of the nth covariate of individual i. */
6503: if (ij > modmaxcovj)
6504: modmaxcovj=ij;
6505: else if (ij < modmincovj)
6506: modmincovj=ij;
1.287 brouard 6507: if (ij <0 || ij >1 ){
1.311 brouard 6508: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6509: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6510: fflush(ficlog);
6511: exit(1);
1.287 brouard 6512: }
6513: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6514: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6515: exit(1);
6516: }else
6517: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6518: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6519: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6520: /* getting the maximum value of the modality of the covariate
6521: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6522: female ies 1, then modmaxcovj=1.
6523: */
6524: } /* end for loop on individuals i */
6525: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6526: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6527: cptcode=modmaxcovj;
6528: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6529: /*for (i=0; i<=cptcode; i++) {*/
6530: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6531: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6532: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6533: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6534: if( j != -1){
6535: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6536: covariate for which somebody answered excluding
6537: undefined. Usually 2: 0 and 1. */
6538: }
6539: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6540: covariate for which somebody answered including
6541: undefined. Usually 3: -1, 0 and 1. */
6542: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6543: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6544: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6545:
1.242 brouard 6546: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6547: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6548: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6549: /* modmincovj=3; modmaxcovj = 7; */
6550: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6551: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6552: /* defining two dummy variables: variables V1_1 and V1_2.*/
6553: /* nbcode[Tvar[j]][ij]=k; */
6554: /* nbcode[Tvar[j]][1]=0; */
6555: /* nbcode[Tvar[j]][2]=1; */
6556: /* nbcode[Tvar[j]][3]=2; */
6557: /* To be continued (not working yet). */
6558: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6559:
6560: /* 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*/
6561: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6562: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6563: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6564: /*, could be restored in the future */
6565: 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 6566: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6567: break;
6568: }
6569: ij++;
1.287 brouard 6570: 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 6571: cptcode = ij; /* New max modality for covar j */
6572: } /* end of loop on modality i=-1 to 1 or more */
6573: break;
6574: case 1: /* Testing on varying covariate, could be simple and
6575: * should look at waves or product of fixed *
6576: * varying. No time to test -1, assuming 0 and 1 only */
6577: ij=0;
6578: for(i=0; i<=1;i++){
6579: nbcode[Tvar[k]][++ij]=i;
6580: }
6581: break;
6582: default:
6583: break;
6584: } /* end switch */
6585: } /* end dummy test */
1.349 brouard 6586: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6587: 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 6588: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6589: printf("Error k=%d \n",k);
6590: exit(1);
6591: }
1.311 brouard 6592: if(isnan(covar[Tvar[k]][i])){
6593: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6594: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6595: fflush(ficlog);
6596: exit(1);
6597: }
6598: }
1.335 brouard 6599: } /* end Quanti */
1.287 brouard 6600: } /* 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 6601:
6602: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6603: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6604: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6605: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6606: 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 */
6607: 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 */
6608: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6609: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6610:
6611: ij=0;
6612: /* 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 6613: 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 */
6614: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6615: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6616: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6617: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6618: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6619: /* 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 6620: /* If product not in single variable we don't print results */
6621: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6622: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6623: /* k= 1 2 3 4 5 6 7 8 9 */
6624: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6625: /* ij 1 2 3 */
6626: /* Tvaraff[ij]= 4 3 1 */
6627: /* Tmodelind[ij]=2 3 9 */
6628: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6629: 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*/
6630: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6631: 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 */
6632: if(Fixed[k]!=0)
6633: anyvaryingduminmodel=1;
6634: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6635: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6636: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6637: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6638: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6639: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6640: }
6641: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6642: /* ij--; */
6643: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6644: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6645: * because they can be excluded from the model and real
6646: * if in the model but excluded because missing values, but how to get k from ij?*/
6647: for(j=ij+1; j<= cptcovt; j++){
6648: Tvaraff[j]=0;
6649: Tmodelind[j]=0;
6650: }
6651: for(j=ntveff+1; j<= cptcovt; j++){
6652: TmodelInvind[j]=0;
6653: }
6654: /* To be sorted */
6655: ;
6656: }
1.126 brouard 6657:
1.145 brouard 6658:
1.126 brouard 6659: /*********** Health Expectancies ****************/
6660:
1.235 brouard 6661: 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 6662:
6663: {
6664: /* Health expectancies, no variances */
1.329 brouard 6665: /* cij is the combination in the list of combination of dummy covariates */
6666: /* strstart is a string of time at start of computing */
1.164 brouard 6667: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6668: int nhstepma, nstepma; /* Decreasing with age */
6669: double age, agelim, hf;
6670: double ***p3mat;
6671: double eip;
6672:
1.238 brouard 6673: /* pstamp(ficreseij); */
1.126 brouard 6674: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6675: fprintf(ficreseij,"# Age");
6676: for(i=1; i<=nlstate;i++){
6677: for(j=1; j<=nlstate;j++){
6678: fprintf(ficreseij," e%1d%1d ",i,j);
6679: }
6680: fprintf(ficreseij," e%1d. ",i);
6681: }
6682: fprintf(ficreseij,"\n");
6683:
6684:
6685: if(estepm < stepm){
6686: printf ("Problem %d lower than %d\n",estepm, stepm);
6687: }
6688: else hstepm=estepm;
6689: /* We compute the life expectancy from trapezoids spaced every estepm months
6690: * This is mainly to measure the difference between two models: for example
6691: * if stepm=24 months pijx are given only every 2 years and by summing them
6692: * we are calculating an estimate of the Life Expectancy assuming a linear
6693: * progression in between and thus overestimating or underestimating according
6694: * to the curvature of the survival function. If, for the same date, we
6695: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6696: * to compare the new estimate of Life expectancy with the same linear
6697: * hypothesis. A more precise result, taking into account a more precise
6698: * curvature will be obtained if estepm is as small as stepm. */
6699:
6700: /* For example we decided to compute the life expectancy with the smallest unit */
6701: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6702: nhstepm is the number of hstepm from age to agelim
6703: nstepm is the number of stepm from age to agelin.
1.270 brouard 6704: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6705: and note for a fixed period like estepm months */
6706: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6707: survival function given by stepm (the optimization length). Unfortunately it
6708: means that if the survival funtion is printed only each two years of age and if
6709: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6710: results. So we changed our mind and took the option of the best precision.
6711: */
6712: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6713:
6714: agelim=AGESUP;
6715: /* If stepm=6 months */
6716: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6717: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6718:
6719: /* nhstepm age range expressed in number of stepm */
6720: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6721: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6722: /* if (stepm >= YEARM) hstepm=1;*/
6723: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6724: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6725:
6726: for (age=bage; age<=fage; age ++){
6727: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6728: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6729: /* if (stepm >= YEARM) hstepm=1;*/
6730: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6731:
6732: /* If stepm=6 months */
6733: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6734: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6735: /* 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 6736: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6737:
6738: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6739:
6740: printf("%d|",(int)age);fflush(stdout);
6741: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6742:
6743: /* Computing expectancies */
6744: for(i=1; i<=nlstate;i++)
6745: for(j=1; j<=nlstate;j++)
6746: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6747: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6748:
6749: /* 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]);*/
6750:
6751: }
6752:
6753: fprintf(ficreseij,"%3.0f",age );
6754: for(i=1; i<=nlstate;i++){
6755: eip=0;
6756: for(j=1; j<=nlstate;j++){
6757: eip +=eij[i][j][(int)age];
6758: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6759: }
6760: fprintf(ficreseij,"%9.4f", eip );
6761: }
6762: fprintf(ficreseij,"\n");
6763:
6764: }
6765: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6766: printf("\n");
6767: fprintf(ficlog,"\n");
6768:
6769: }
6770:
1.235 brouard 6771: 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 6772:
6773: {
6774: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6775: to initial status i, ei. .
1.126 brouard 6776: */
1.336 brouard 6777: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6778: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6779: int nhstepma, nstepma; /* Decreasing with age */
6780: double age, agelim, hf;
6781: double ***p3matp, ***p3matm, ***varhe;
6782: double **dnewm,**doldm;
6783: double *xp, *xm;
6784: double **gp, **gm;
6785: double ***gradg, ***trgradg;
6786: int theta;
6787:
6788: double eip, vip;
6789:
6790: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6791: xp=vector(1,npar);
6792: xm=vector(1,npar);
6793: dnewm=matrix(1,nlstate*nlstate,1,npar);
6794: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6795:
6796: pstamp(ficresstdeij);
6797: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6798: fprintf(ficresstdeij,"# Age");
6799: for(i=1; i<=nlstate;i++){
6800: for(j=1; j<=nlstate;j++)
6801: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6802: fprintf(ficresstdeij," e%1d. ",i);
6803: }
6804: fprintf(ficresstdeij,"\n");
6805:
6806: pstamp(ficrescveij);
6807: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6808: fprintf(ficrescveij,"# Age");
6809: for(i=1; i<=nlstate;i++)
6810: for(j=1; j<=nlstate;j++){
6811: cptj= (j-1)*nlstate+i;
6812: for(i2=1; i2<=nlstate;i2++)
6813: for(j2=1; j2<=nlstate;j2++){
6814: cptj2= (j2-1)*nlstate+i2;
6815: if(cptj2 <= cptj)
6816: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6817: }
6818: }
6819: fprintf(ficrescveij,"\n");
6820:
6821: if(estepm < stepm){
6822: printf ("Problem %d lower than %d\n",estepm, stepm);
6823: }
6824: else hstepm=estepm;
6825: /* We compute the life expectancy from trapezoids spaced every estepm months
6826: * This is mainly to measure the difference between two models: for example
6827: * if stepm=24 months pijx are given only every 2 years and by summing them
6828: * we are calculating an estimate of the Life Expectancy assuming a linear
6829: * progression in between and thus overestimating or underestimating according
6830: * to the curvature of the survival function. If, for the same date, we
6831: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6832: * to compare the new estimate of Life expectancy with the same linear
6833: * hypothesis. A more precise result, taking into account a more precise
6834: * curvature will be obtained if estepm is as small as stepm. */
6835:
6836: /* For example we decided to compute the life expectancy with the smallest unit */
6837: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6838: nhstepm is the number of hstepm from age to agelim
6839: nstepm is the number of stepm from age to agelin.
6840: Look at hpijx to understand the reason of that which relies in memory size
6841: and note for a fixed period like estepm months */
6842: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6843: survival function given by stepm (the optimization length). Unfortunately it
6844: means that if the survival funtion is printed only each two years of age and if
6845: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6846: results. So we changed our mind and took the option of the best precision.
6847: */
6848: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6849:
6850: /* If stepm=6 months */
6851: /* nhstepm age range expressed in number of stepm */
6852: agelim=AGESUP;
6853: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6854: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6855: /* if (stepm >= YEARM) hstepm=1;*/
6856: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6857:
6858: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6859: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6860: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6861: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6862: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6863: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6864:
6865: for (age=bage; age<=fage; age ++){
6866: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6867: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6868: /* if (stepm >= YEARM) hstepm=1;*/
6869: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6870:
1.126 brouard 6871: /* If stepm=6 months */
6872: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6873: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6874:
6875: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6876:
1.126 brouard 6877: /* Computing Variances of health expectancies */
6878: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6879: decrease memory allocation */
6880: for(theta=1; theta <=npar; theta++){
6881: for(i=1; i<=npar; i++){
1.222 brouard 6882: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6883: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6884: }
1.235 brouard 6885: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6886: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6887:
1.126 brouard 6888: for(j=1; j<= nlstate; j++){
1.222 brouard 6889: for(i=1; i<=nlstate; i++){
6890: for(h=0; h<=nhstepm-1; h++){
6891: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6892: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6893: }
6894: }
1.126 brouard 6895: }
1.218 brouard 6896:
1.126 brouard 6897: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6898: for(h=0; h<=nhstepm-1; h++){
6899: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6900: }
1.126 brouard 6901: }/* End theta */
6902:
6903:
6904: for(h=0; h<=nhstepm-1; h++)
6905: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6906: for(theta=1; theta <=npar; theta++)
6907: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6908:
1.218 brouard 6909:
1.222 brouard 6910: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6911: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6912: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6913:
1.222 brouard 6914: printf("%d|",(int)age);fflush(stdout);
6915: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6916: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6917: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6918: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6919: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6920: for(ij=1;ij<=nlstate*nlstate;ij++)
6921: for(ji=1;ji<=nlstate*nlstate;ji++)
6922: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6923: }
6924: }
1.320 brouard 6925: /* if((int)age ==50){ */
6926: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6927: /* } */
1.126 brouard 6928: /* Computing expectancies */
1.235 brouard 6929: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6930: for(i=1; i<=nlstate;i++)
6931: for(j=1; j<=nlstate;j++)
1.222 brouard 6932: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6933: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6934:
1.222 brouard 6935: /* 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 6936:
1.222 brouard 6937: }
1.269 brouard 6938:
6939: /* Standard deviation of expectancies ij */
1.126 brouard 6940: fprintf(ficresstdeij,"%3.0f",age );
6941: for(i=1; i<=nlstate;i++){
6942: eip=0.;
6943: vip=0.;
6944: for(j=1; j<=nlstate;j++){
1.222 brouard 6945: eip += eij[i][j][(int)age];
6946: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6947: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6948: 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 6949: }
6950: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6951: }
6952: fprintf(ficresstdeij,"\n");
1.218 brouard 6953:
1.269 brouard 6954: /* Variance of expectancies ij */
1.126 brouard 6955: fprintf(ficrescveij,"%3.0f",age );
6956: for(i=1; i<=nlstate;i++)
6957: for(j=1; j<=nlstate;j++){
1.222 brouard 6958: cptj= (j-1)*nlstate+i;
6959: for(i2=1; i2<=nlstate;i2++)
6960: for(j2=1; j2<=nlstate;j2++){
6961: cptj2= (j2-1)*nlstate+i2;
6962: if(cptj2 <= cptj)
6963: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6964: }
1.126 brouard 6965: }
6966: fprintf(ficrescveij,"\n");
1.218 brouard 6967:
1.126 brouard 6968: }
6969: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6970: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6971: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6972: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6973: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6974: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6975: printf("\n");
6976: fprintf(ficlog,"\n");
1.218 brouard 6977:
1.126 brouard 6978: free_vector(xm,1,npar);
6979: free_vector(xp,1,npar);
6980: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6981: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6982: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6983: }
1.218 brouard 6984:
1.126 brouard 6985: /************ Variance ******************/
1.235 brouard 6986: 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 6987: {
1.279 brouard 6988: /** Variance of health expectancies
6989: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6990: * double **newm;
6991: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6992: */
1.218 brouard 6993:
6994: /* int movingaverage(); */
6995: double **dnewm,**doldm;
6996: double **dnewmp,**doldmp;
6997: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6998: int first=0;
1.218 brouard 6999: int k;
7000: double *xp;
1.279 brouard 7001: double **gp, **gm; /**< for var eij */
7002: double ***gradg, ***trgradg; /**< for var eij */
7003: double **gradgp, **trgradgp; /**< for var p point j */
7004: double *gpp, *gmp; /**< for var p point j */
7005: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 7006: double ***p3mat;
7007: double age,agelim, hf;
7008: /* double ***mobaverage; */
7009: int theta;
7010: char digit[4];
7011: char digitp[25];
7012:
7013: char fileresprobmorprev[FILENAMELENGTH];
7014:
7015: if(popbased==1){
7016: if(mobilav!=0)
7017: strcpy(digitp,"-POPULBASED-MOBILAV_");
7018: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
7019: }
7020: else
7021: strcpy(digitp,"-STABLBASED_");
1.126 brouard 7022:
1.218 brouard 7023: /* if (mobilav!=0) { */
7024: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7025: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
7026: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
7027: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
7028: /* } */
7029: /* } */
7030:
7031: strcpy(fileresprobmorprev,"PRMORPREV-");
7032: sprintf(digit,"%-d",ij);
7033: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7034: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7035: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7036: strcat(fileresprobmorprev,fileresu);
7037: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7038: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7039: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7040: }
7041: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7042: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7043: pstamp(ficresprobmorprev);
7044: 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 7045: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7046:
7047: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7048: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7049: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7050: /* } */
7051: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7052: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7053: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7054: }
1.337 brouard 7055: /* for(j=1;j<=cptcoveff;j++) */
7056: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7057: fprintf(ficresprobmorprev,"\n");
7058:
1.218 brouard 7059: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7060: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7061: fprintf(ficresprobmorprev," p.%-d SE",j);
7062: for(i=1; i<=nlstate;i++)
7063: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7064: }
7065: fprintf(ficresprobmorprev,"\n");
7066:
7067: fprintf(ficgp,"\n# Routine varevsij");
7068: fprintf(ficgp,"\nunset title \n");
7069: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7070: 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");
7071: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7072:
1.218 brouard 7073: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7074: pstamp(ficresvij);
7075: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7076: if(popbased==1)
7077: 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);
7078: else
7079: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7080: fprintf(ficresvij,"# Age");
7081: for(i=1; i<=nlstate;i++)
7082: for(j=1; j<=nlstate;j++)
7083: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7084: fprintf(ficresvij,"\n");
7085:
7086: xp=vector(1,npar);
7087: dnewm=matrix(1,nlstate,1,npar);
7088: doldm=matrix(1,nlstate,1,nlstate);
7089: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7090: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7091:
7092: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7093: gpp=vector(nlstate+1,nlstate+ndeath);
7094: gmp=vector(nlstate+1,nlstate+ndeath);
7095: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7096:
1.218 brouard 7097: if(estepm < stepm){
7098: printf ("Problem %d lower than %d\n",estepm, stepm);
7099: }
7100: else hstepm=estepm;
7101: /* For example we decided to compute the life expectancy with the smallest unit */
7102: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7103: nhstepm is the number of hstepm from age to agelim
7104: nstepm is the number of stepm from age to agelim.
7105: Look at function hpijx to understand why because of memory size limitations,
7106: we decided (b) to get a life expectancy respecting the most precise curvature of the
7107: survival function given by stepm (the optimization length). Unfortunately it
7108: means that if the survival funtion is printed every two years of age and if
7109: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7110: results. So we changed our mind and took the option of the best precision.
7111: */
7112: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7113: agelim = AGESUP;
7114: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7115: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7116: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7117: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7118: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7119: gp=matrix(0,nhstepm,1,nlstate);
7120: gm=matrix(0,nhstepm,1,nlstate);
7121:
7122:
7123: for(theta=1; theta <=npar; theta++){
7124: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7125: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7126: }
1.279 brouard 7127: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7128: * returns into prlim .
1.288 brouard 7129: */
1.242 brouard 7130: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7131:
7132: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7133: if (popbased==1) {
7134: if(mobilav ==0){
7135: for(i=1; i<=nlstate;i++)
7136: prlim[i][i]=probs[(int)age][i][ij];
7137: }else{ /* mobilav */
7138: for(i=1; i<=nlstate;i++)
7139: prlim[i][i]=mobaverage[(int)age][i][ij];
7140: }
7141: }
1.295 brouard 7142: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7143: */
7144: 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 7145: /**< 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 7146: * at horizon h in state j including mortality.
7147: */
1.218 brouard 7148: for(j=1; j<= nlstate; j++){
7149: for(h=0; h<=nhstepm; h++){
7150: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7151: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7152: }
7153: }
1.279 brouard 7154: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7155: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7156: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7157: */
7158: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7159: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7160: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7161: }
7162:
7163: /* Again with minus shift */
1.218 brouard 7164:
7165: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7166: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7167:
1.242 brouard 7168: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7169:
7170: if (popbased==1) {
7171: if(mobilav ==0){
7172: for(i=1; i<=nlstate;i++)
7173: prlim[i][i]=probs[(int)age][i][ij];
7174: }else{ /* mobilav */
7175: for(i=1; i<=nlstate;i++)
7176: prlim[i][i]=mobaverage[(int)age][i][ij];
7177: }
7178: }
7179:
1.235 brouard 7180: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7181:
7182: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7183: for(h=0; h<=nhstepm; h++){
7184: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7185: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7186: }
7187: }
7188: /* This for computing probability of death (h=1 means
7189: computed over hstepm matrices product = hstepm*stepm months)
7190: as a weighted average of prlim.
7191: */
7192: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7193: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7194: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7195: }
1.279 brouard 7196: /* end shifting computations */
7197:
7198: /**< Computing gradient matrix at horizon h
7199: */
1.218 brouard 7200: for(j=1; j<= nlstate; j++) /* vareij */
7201: for(h=0; h<=nhstepm; h++){
7202: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7203: }
1.279 brouard 7204: /**< Gradient of overall mortality p.3 (or p.j)
7205: */
7206: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7207: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7208: }
7209:
7210: } /* End theta */
1.279 brouard 7211:
7212: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7213: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7214:
7215: for(h=0; h<=nhstepm; h++) /* veij */
7216: for(j=1; j<=nlstate;j++)
7217: for(theta=1; theta <=npar; theta++)
7218: trgradg[h][j][theta]=gradg[h][theta][j];
7219:
7220: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7221: for(theta=1; theta <=npar; theta++)
7222: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7223: /**< as well as its transposed matrix
7224: */
1.218 brouard 7225:
7226: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7227: for(i=1;i<=nlstate;i++)
7228: for(j=1;j<=nlstate;j++)
7229: vareij[i][j][(int)age] =0.;
1.279 brouard 7230:
7231: /* Computing trgradg by matcov by gradg at age and summing over h
7232: * and k (nhstepm) formula 15 of article
7233: * Lievre-Brouard-Heathcote
7234: */
7235:
1.218 brouard 7236: for(h=0;h<=nhstepm;h++){
7237: for(k=0;k<=nhstepm;k++){
7238: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7239: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7240: for(i=1;i<=nlstate;i++)
7241: for(j=1;j<=nlstate;j++)
7242: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7243: }
7244: }
7245:
1.279 brouard 7246: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7247: * p.j overall mortality formula 49 but computed directly because
7248: * we compute the grad (wix pijx) instead of grad (pijx),even if
7249: * wix is independent of theta.
7250: */
1.218 brouard 7251: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7252: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7253: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7254: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7255: varppt[j][i]=doldmp[j][i];
7256: /* end ppptj */
7257: /* x centered again */
7258:
1.242 brouard 7259: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7260:
7261: if (popbased==1) {
7262: if(mobilav ==0){
7263: for(i=1; i<=nlstate;i++)
7264: prlim[i][i]=probs[(int)age][i][ij];
7265: }else{ /* mobilav */
7266: for(i=1; i<=nlstate;i++)
7267: prlim[i][i]=mobaverage[(int)age][i][ij];
7268: }
7269: }
7270:
7271: /* This for computing probability of death (h=1 means
7272: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7273: as a weighted average of prlim.
7274: */
1.235 brouard 7275: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7276: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7277: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7278: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7279: }
7280: /* end probability of death */
7281:
7282: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7283: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7284: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7285: for(i=1; i<=nlstate;i++){
7286: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7287: }
7288: }
7289: fprintf(ficresprobmorprev,"\n");
7290:
7291: fprintf(ficresvij,"%.0f ",age );
7292: for(i=1; i<=nlstate;i++)
7293: for(j=1; j<=nlstate;j++){
7294: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7295: }
7296: fprintf(ficresvij,"\n");
7297: free_matrix(gp,0,nhstepm,1,nlstate);
7298: free_matrix(gm,0,nhstepm,1,nlstate);
7299: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7300: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7301: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7302: } /* End age */
7303: free_vector(gpp,nlstate+1,nlstate+ndeath);
7304: free_vector(gmp,nlstate+1,nlstate+ndeath);
7305: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7306: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7307: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7308: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7309: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7310: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7311: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7312: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7313: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7314: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7315: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7316: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7317: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7318: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7319: 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);
7320: /* 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 7321: */
1.218 brouard 7322: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7323: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7324:
1.218 brouard 7325: free_vector(xp,1,npar);
7326: free_matrix(doldm,1,nlstate,1,nlstate);
7327: free_matrix(dnewm,1,nlstate,1,npar);
7328: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7329: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7330: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7331: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7332: fclose(ficresprobmorprev);
7333: fflush(ficgp);
7334: fflush(fichtm);
7335: } /* end varevsij */
1.126 brouard 7336:
7337: /************ Variance of prevlim ******************/
1.269 brouard 7338: 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 7339: {
1.205 brouard 7340: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7341: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7342:
1.268 brouard 7343: double **dnewmpar,**doldm;
1.126 brouard 7344: int i, j, nhstepm, hstepm;
7345: double *xp;
7346: double *gp, *gm;
7347: double **gradg, **trgradg;
1.208 brouard 7348: double **mgm, **mgp;
1.126 brouard 7349: double age,agelim;
7350: int theta;
7351:
7352: pstamp(ficresvpl);
1.288 brouard 7353: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7354: fprintf(ficresvpl,"# Age ");
7355: if(nresult >=1)
7356: fprintf(ficresvpl," Result# ");
1.126 brouard 7357: for(i=1; i<=nlstate;i++)
7358: fprintf(ficresvpl," %1d-%1d",i,i);
7359: fprintf(ficresvpl,"\n");
7360:
7361: xp=vector(1,npar);
1.268 brouard 7362: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7363: doldm=matrix(1,nlstate,1,nlstate);
7364:
7365: hstepm=1*YEARM; /* Every year of age */
7366: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7367: agelim = AGESUP;
7368: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7369: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7370: if (stepm >= YEARM) hstepm=1;
7371: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7372: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7373: mgp=matrix(1,npar,1,nlstate);
7374: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7375: gp=vector(1,nlstate);
7376: gm=vector(1,nlstate);
7377:
7378: for(theta=1; theta <=npar; theta++){
7379: for(i=1; i<=npar; i++){ /* Computes gradient */
7380: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7381: }
1.288 brouard 7382: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7383: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7384: /* else */
7385: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7386: for(i=1;i<=nlstate;i++){
1.126 brouard 7387: gp[i] = prlim[i][i];
1.208 brouard 7388: mgp[theta][i] = prlim[i][i];
7389: }
1.126 brouard 7390: for(i=1; i<=npar; i++) /* Computes gradient */
7391: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7392: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7393: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7394: /* else */
7395: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7396: for(i=1;i<=nlstate;i++){
1.126 brouard 7397: gm[i] = prlim[i][i];
1.208 brouard 7398: mgm[theta][i] = prlim[i][i];
7399: }
1.126 brouard 7400: for(i=1;i<=nlstate;i++)
7401: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7402: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7403: } /* End theta */
7404:
7405: trgradg =matrix(1,nlstate,1,npar);
7406:
7407: for(j=1; j<=nlstate;j++)
7408: for(theta=1; theta <=npar; theta++)
7409: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7410: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7411: /* printf("\nmgm mgp %d ",(int)age); */
7412: /* for(j=1; j<=nlstate;j++){ */
7413: /* printf(" %d ",j); */
7414: /* for(theta=1; theta <=npar; theta++) */
7415: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7416: /* printf("\n "); */
7417: /* } */
7418: /* } */
7419: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7420: /* printf("\n gradg %d ",(int)age); */
7421: /* for(j=1; j<=nlstate;j++){ */
7422: /* printf("%d ",j); */
7423: /* for(theta=1; theta <=npar; theta++) */
7424: /* printf("%d %lf ",theta,gradg[theta][j]); */
7425: /* printf("\n "); */
7426: /* } */
7427: /* } */
1.126 brouard 7428:
7429: for(i=1;i<=nlstate;i++)
7430: varpl[i][(int)age] =0.;
1.209 brouard 7431: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7432: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7433: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7434: }else{
1.268 brouard 7435: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7436: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7437: }
1.126 brouard 7438: for(i=1;i<=nlstate;i++)
7439: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7440:
7441: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7442: if(nresult >=1)
7443: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7444: for(i=1; i<=nlstate;i++){
1.126 brouard 7445: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7446: /* for(j=1;j<=nlstate;j++) */
7447: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7448: }
1.126 brouard 7449: fprintf(ficresvpl,"\n");
7450: free_vector(gp,1,nlstate);
7451: free_vector(gm,1,nlstate);
1.208 brouard 7452: free_matrix(mgm,1,npar,1,nlstate);
7453: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7454: free_matrix(gradg,1,npar,1,nlstate);
7455: free_matrix(trgradg,1,nlstate,1,npar);
7456: } /* End age */
7457:
7458: free_vector(xp,1,npar);
7459: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7460: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7461:
7462: }
7463:
7464:
7465: /************ Variance of backprevalence limit ******************/
1.269 brouard 7466: 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 7467: {
7468: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7469: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7470:
7471: double **dnewmpar,**doldm;
7472: int i, j, nhstepm, hstepm;
7473: double *xp;
7474: double *gp, *gm;
7475: double **gradg, **trgradg;
7476: double **mgm, **mgp;
7477: double age,agelim;
7478: int theta;
7479:
7480: pstamp(ficresvbl);
7481: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7482: fprintf(ficresvbl,"# Age ");
7483: if(nresult >=1)
7484: fprintf(ficresvbl," Result# ");
7485: for(i=1; i<=nlstate;i++)
7486: fprintf(ficresvbl," %1d-%1d",i,i);
7487: fprintf(ficresvbl,"\n");
7488:
7489: xp=vector(1,npar);
7490: dnewmpar=matrix(1,nlstate,1,npar);
7491: doldm=matrix(1,nlstate,1,nlstate);
7492:
7493: hstepm=1*YEARM; /* Every year of age */
7494: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7495: agelim = AGEINF;
7496: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7497: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7498: if (stepm >= YEARM) hstepm=1;
7499: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7500: gradg=matrix(1,npar,1,nlstate);
7501: mgp=matrix(1,npar,1,nlstate);
7502: mgm=matrix(1,npar,1,nlstate);
7503: gp=vector(1,nlstate);
7504: gm=vector(1,nlstate);
7505:
7506: for(theta=1; theta <=npar; theta++){
7507: for(i=1; i<=npar; i++){ /* Computes gradient */
7508: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7509: }
7510: if(mobilavproj > 0 )
7511: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7512: else
7513: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7514: for(i=1;i<=nlstate;i++){
7515: gp[i] = bprlim[i][i];
7516: mgp[theta][i] = bprlim[i][i];
7517: }
7518: for(i=1; i<=npar; i++) /* Computes gradient */
7519: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7520: if(mobilavproj > 0 )
7521: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7522: else
7523: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7524: for(i=1;i<=nlstate;i++){
7525: gm[i] = bprlim[i][i];
7526: mgm[theta][i] = bprlim[i][i];
7527: }
7528: for(i=1;i<=nlstate;i++)
7529: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7530: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7531: } /* End theta */
7532:
7533: trgradg =matrix(1,nlstate,1,npar);
7534:
7535: for(j=1; j<=nlstate;j++)
7536: for(theta=1; theta <=npar; theta++)
7537: trgradg[j][theta]=gradg[theta][j];
7538: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7539: /* printf("\nmgm mgp %d ",(int)age); */
7540: /* for(j=1; j<=nlstate;j++){ */
7541: /* printf(" %d ",j); */
7542: /* for(theta=1; theta <=npar; theta++) */
7543: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7544: /* printf("\n "); */
7545: /* } */
7546: /* } */
7547: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7548: /* printf("\n gradg %d ",(int)age); */
7549: /* for(j=1; j<=nlstate;j++){ */
7550: /* printf("%d ",j); */
7551: /* for(theta=1; theta <=npar; theta++) */
7552: /* printf("%d %lf ",theta,gradg[theta][j]); */
7553: /* printf("\n "); */
7554: /* } */
7555: /* } */
7556:
7557: for(i=1;i<=nlstate;i++)
7558: varbpl[i][(int)age] =0.;
7559: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7560: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7561: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7562: }else{
7563: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7564: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7565: }
7566: for(i=1;i<=nlstate;i++)
7567: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7568:
7569: fprintf(ficresvbl,"%.0f ",age );
7570: if(nresult >=1)
7571: fprintf(ficresvbl,"%d ",nres );
7572: for(i=1; i<=nlstate;i++)
7573: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7574: fprintf(ficresvbl,"\n");
7575: free_vector(gp,1,nlstate);
7576: free_vector(gm,1,nlstate);
7577: free_matrix(mgm,1,npar,1,nlstate);
7578: free_matrix(mgp,1,npar,1,nlstate);
7579: free_matrix(gradg,1,npar,1,nlstate);
7580: free_matrix(trgradg,1,nlstate,1,npar);
7581: } /* End age */
7582:
7583: free_vector(xp,1,npar);
7584: free_matrix(doldm,1,nlstate,1,npar);
7585: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7586:
7587: }
7588:
7589: /************ Variance of one-step probabilities ******************/
7590: 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 7591: {
7592: int i, j=0, k1, l1, tj;
7593: int k2, l2, j1, z1;
7594: int k=0, l;
7595: int first=1, first1, first2;
1.326 brouard 7596: int nres=0; /* New */
1.222 brouard 7597: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7598: double **dnewm,**doldm;
7599: double *xp;
7600: double *gp, *gm;
7601: double **gradg, **trgradg;
7602: double **mu;
7603: double age, cov[NCOVMAX+1];
7604: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7605: int theta;
7606: char fileresprob[FILENAMELENGTH];
7607: char fileresprobcov[FILENAMELENGTH];
7608: char fileresprobcor[FILENAMELENGTH];
7609: double ***varpij;
7610:
7611: strcpy(fileresprob,"PROB_");
7612: strcat(fileresprob,fileres);
7613: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7614: printf("Problem with resultfile: %s\n", fileresprob);
7615: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7616: }
7617: strcpy(fileresprobcov,"PROBCOV_");
7618: strcat(fileresprobcov,fileresu);
7619: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7620: printf("Problem with resultfile: %s\n", fileresprobcov);
7621: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7622: }
7623: strcpy(fileresprobcor,"PROBCOR_");
7624: strcat(fileresprobcor,fileresu);
7625: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7626: printf("Problem with resultfile: %s\n", fileresprobcor);
7627: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7628: }
7629: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7630: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7631: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7632: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7633: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7634: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7635: pstamp(ficresprob);
7636: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7637: fprintf(ficresprob,"# Age");
7638: pstamp(ficresprobcov);
7639: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7640: fprintf(ficresprobcov,"# Age");
7641: pstamp(ficresprobcor);
7642: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7643: fprintf(ficresprobcor,"# Age");
1.126 brouard 7644:
7645:
1.222 brouard 7646: for(i=1; i<=nlstate;i++)
7647: for(j=1; j<=(nlstate+ndeath);j++){
7648: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7649: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7650: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7651: }
7652: /* fprintf(ficresprob,"\n");
7653: fprintf(ficresprobcov,"\n");
7654: fprintf(ficresprobcor,"\n");
7655: */
7656: xp=vector(1,npar);
7657: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7658: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7659: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7660: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7661: first=1;
7662: fprintf(ficgp,"\n# Routine varprob");
7663: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7664: fprintf(fichtm,"\n");
7665:
1.288 brouard 7666: 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 7667: 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);
7668: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7669: and drawn. It helps understanding how is the covariance between two incidences.\
7670: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7671: 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 7672: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7673: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7674: standard deviations wide on each axis. <br>\
7675: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7676: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7677: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7678:
1.222 brouard 7679: cov[1]=1;
7680: /* tj=cptcoveff; */
1.225 brouard 7681: tj = (int) pow(2,cptcoveff);
1.222 brouard 7682: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7683: j1=0;
1.332 brouard 7684:
7685: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7686: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7687: /* 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 7688: if(tj != 1 && TKresult[nres]!= j1)
7689: continue;
7690:
7691: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7692: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7693: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7694: if (cptcovn>0) {
1.334 brouard 7695: fprintf(ficresprob, "\n#********** Variable ");
7696: fprintf(ficresprobcov, "\n#********** Variable ");
7697: fprintf(ficgp, "\n#********** Variable ");
7698: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7699: fprintf(ficresprobcor, "\n#********** Variable ");
7700:
7701: /* Including quantitative variables of the resultline to be done */
7702: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7703: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7704: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7705: /* 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 7706: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7707: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7708: 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 */
7709: 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 */
7710: 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 */
7711: 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 */
7712: 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 */
7713: fprintf(ficresprob,"fixed ");
7714: fprintf(ficresprobcov,"fixed ");
7715: fprintf(ficgp,"fixed ");
7716: fprintf(fichtmcov,"fixed ");
7717: fprintf(ficresprobcor,"fixed ");
7718: }else{
7719: fprintf(ficresprob,"varyi ");
7720: fprintf(ficresprobcov,"varyi ");
7721: fprintf(ficgp,"varyi ");
7722: fprintf(fichtmcov,"varyi ");
7723: fprintf(ficresprobcor,"varyi ");
7724: }
7725: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7726: /* For each selected (single) quantitative value */
1.337 brouard 7727: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7728: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7729: fprintf(ficresprob,"fixed ");
7730: fprintf(ficresprobcov,"fixed ");
7731: fprintf(ficgp,"fixed ");
7732: fprintf(fichtmcov,"fixed ");
7733: fprintf(ficresprobcor,"fixed ");
7734: }else{
7735: fprintf(ficresprob,"varyi ");
7736: fprintf(ficresprobcov,"varyi ");
7737: fprintf(ficgp,"varyi ");
7738: fprintf(fichtmcov,"varyi ");
7739: fprintf(ficresprobcor,"varyi ");
7740: }
7741: }else{
7742: 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 */
7743: 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 */
7744: exit(1);
7745: }
7746: } /* End loop on variable of this resultline */
7747: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7748: fprintf(ficresprob, "**********\n#\n");
7749: fprintf(ficresprobcov, "**********\n#\n");
7750: fprintf(ficgp, "**********\n#\n");
7751: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7752: fprintf(ficresprobcor, "**********\n#");
7753: if(invalidvarcomb[j1]){
7754: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7755: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7756: continue;
7757: }
7758: }
7759: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7760: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7761: gp=vector(1,(nlstate)*(nlstate+ndeath));
7762: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7763: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7764: cov[2]=age;
7765: if(nagesqr==1)
7766: cov[3]= age*age;
1.334 brouard 7767: /* New code end of combination but for each resultline */
7768: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 7769: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7770: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7771: }else{
1.334 brouard 7772: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7773: }
1.334 brouard 7774: }/* End of loop on model equation */
7775: /* Old code */
7776: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7777: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7778: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7779: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7780: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7781: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7782: /* * 1 1 1 1 1 */
7783: /* * 2 2 1 1 1 */
7784: /* * 3 1 2 1 1 */
7785: /* *\/ */
7786: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7787: /* } */
7788: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7789: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7790: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7791: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7792: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7793: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7794: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7795: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7796: /* 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]); */
7797: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7798: /* /\* exit(1); *\/ */
7799: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7800: /* } */
7801: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7802: /* } */
7803: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7804: /* if(Dummy[Tvard[k][1]]==0){ */
7805: /* if(Dummy[Tvard[k][2]]==0){ */
7806: /* 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]])]; */
7807: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7808: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7809: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7810: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7811: /* } */
7812: /* }else{ */
7813: /* if(Dummy[Tvard[k][2]]==0){ */
7814: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7815: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7816: /* }else{ */
7817: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7818: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7819: /* } */
7820: /* } */
7821: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7822: /* } */
1.326 brouard 7823: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7824: for(theta=1; theta <=npar; theta++){
7825: for(i=1; i<=npar; i++)
7826: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7827:
1.222 brouard 7828: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7829:
1.222 brouard 7830: k=0;
7831: for(i=1; i<= (nlstate); i++){
7832: for(j=1; j<=(nlstate+ndeath);j++){
7833: k=k+1;
7834: gp[k]=pmmij[i][j];
7835: }
7836: }
1.220 brouard 7837:
1.222 brouard 7838: for(i=1; i<=npar; i++)
7839: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7840:
1.222 brouard 7841: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7842: k=0;
7843: for(i=1; i<=(nlstate); i++){
7844: for(j=1; j<=(nlstate+ndeath);j++){
7845: k=k+1;
7846: gm[k]=pmmij[i][j];
7847: }
7848: }
1.220 brouard 7849:
1.222 brouard 7850: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7851: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7852: }
1.126 brouard 7853:
1.222 brouard 7854: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7855: for(theta=1; theta <=npar; theta++)
7856: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7857:
1.222 brouard 7858: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7859: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7860:
1.222 brouard 7861: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7862:
1.222 brouard 7863: k=0;
7864: for(i=1; i<=(nlstate); i++){
7865: for(j=1; j<=(nlstate+ndeath);j++){
7866: k=k+1;
7867: mu[k][(int) age]=pmmij[i][j];
7868: }
7869: }
7870: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7871: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7872: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7873:
1.222 brouard 7874: /*printf("\n%d ",(int)age);
7875: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7876: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7877: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7878: }*/
1.220 brouard 7879:
1.222 brouard 7880: fprintf(ficresprob,"\n%d ",(int)age);
7881: fprintf(ficresprobcov,"\n%d ",(int)age);
7882: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7883:
1.222 brouard 7884: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7885: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7886: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7887: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7888: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7889: }
7890: i=0;
7891: for (k=1; k<=(nlstate);k++){
7892: for (l=1; l<=(nlstate+ndeath);l++){
7893: i++;
7894: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7895: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7896: for (j=1; j<=i;j++){
7897: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7898: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7899: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7900: }
7901: }
7902: }/* end of loop for state */
7903: } /* end of loop for age */
7904: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7905: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7906: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7907: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7908:
7909: /* Confidence intervalle of pij */
7910: /*
7911: fprintf(ficgp,"\nunset parametric;unset label");
7912: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7913: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7914: 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);
7915: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7916: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7917: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7918: */
7919:
7920: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7921: first1=1;first2=2;
7922: for (k2=1; k2<=(nlstate);k2++){
7923: for (l2=1; l2<=(nlstate+ndeath);l2++){
7924: if(l2==k2) continue;
7925: j=(k2-1)*(nlstate+ndeath)+l2;
7926: for (k1=1; k1<=(nlstate);k1++){
7927: for (l1=1; l1<=(nlstate+ndeath);l1++){
7928: if(l1==k1) continue;
7929: i=(k1-1)*(nlstate+ndeath)+l1;
7930: if(i<=j) continue;
7931: for (age=bage; age<=fage; age ++){
7932: if ((int)age %5==0){
7933: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7934: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7935: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7936: mu1=mu[i][(int) age]/stepm*YEARM ;
7937: mu2=mu[j][(int) age]/stepm*YEARM;
7938: c12=cv12/sqrt(v1*v2);
7939: /* Computing eigen value of matrix of covariance */
7940: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7941: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7942: if ((lc2 <0) || (lc1 <0) ){
7943: if(first2==1){
7944: first1=0;
7945: 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);
7946: }
7947: 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);
7948: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7949: /* lc2=fabs(lc2); */
7950: }
1.220 brouard 7951:
1.222 brouard 7952: /* Eigen vectors */
1.280 brouard 7953: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7954: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7955: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7956: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7957: }else
7958: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7959: /*v21=sqrt(1.-v11*v11); *//* error */
7960: v21=(lc1-v1)/cv12*v11;
7961: v12=-v21;
7962: v22=v11;
7963: tnalp=v21/v11;
7964: if(first1==1){
7965: first1=0;
7966: 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);
7967: }
7968: 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);
7969: /*printf(fignu*/
7970: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7971: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7972: if(first==1){
7973: first=0;
7974: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7975: fprintf(ficgp,"\nset parametric;unset label");
7976: 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);
7977: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7978: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7979: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7980: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7981: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7982: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7983: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7984: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7985: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7986: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7987: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7988: 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 7989: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7990: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7991: }else{
7992: first=0;
7993: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7994: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7995: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7996: 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 7997: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7998: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7999: }/* if first */
8000: } /* age mod 5 */
8001: } /* end loop age */
8002: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8003: first=1;
8004: } /*l12 */
8005: } /* k12 */
8006: } /*l1 */
8007: }/* k1 */
1.332 brouard 8008: } /* loop on combination of covariates j1 */
1.326 brouard 8009: } /* loop on nres */
1.222 brouard 8010: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
8011: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
8012: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
8013: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
8014: free_vector(xp,1,npar);
8015: fclose(ficresprob);
8016: fclose(ficresprobcov);
8017: fclose(ficresprobcor);
8018: fflush(ficgp);
8019: fflush(fichtmcov);
8020: }
1.126 brouard 8021:
8022:
8023: /******************* Printing html file ***********/
1.201 brouard 8024: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8025: int lastpass, int stepm, int weightopt, char model[],\
8026: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 8027: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
8028: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
8029: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 8030: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 8031: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8032: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8033: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8034: </ul>");
1.319 brouard 8035: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8036: /* </ul>", model); */
1.214 brouard 8037: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8038: 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",
8039: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8040: 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 8041: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8042: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8043: fprintf(fichtm,"\
8044: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8045: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8046: fprintf(fichtm,"\
1.217 brouard 8047: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8048: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8049: fprintf(fichtm,"\
1.288 brouard 8050: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8051: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8052: fprintf(fichtm,"\
1.288 brouard 8053: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8054: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8055: fprintf(fichtm,"\
1.211 brouard 8056: - (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 8057: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8058: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8059: if(prevfcast==1){
8060: fprintf(fichtm,"\
8061: - Prevalence projections by age and states: \
1.201 brouard 8062: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8063: }
1.126 brouard 8064:
8065:
1.225 brouard 8066: m=pow(2,cptcoveff);
1.222 brouard 8067: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8068:
1.317 brouard 8069: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8070:
8071: jj1=0;
8072:
8073: fprintf(fichtm," \n<ul>");
1.337 brouard 8074: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8075: /* k1=nres; */
1.338 brouard 8076: k1=TKresult[nres];
8077: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8078: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8079: /* if(m != 1 && TKresult[nres]!= k1) */
8080: /* continue; */
1.264 brouard 8081: jj1++;
8082: if (cptcovn > 0) {
8083: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8084: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8085: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8086: }
1.337 brouard 8087: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8088: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8089: /* } */
8090: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8091: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8092: /* } */
1.264 brouard 8093: fprintf(fichtm,"\">");
8094:
8095: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8096: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8097: for (cpt=1; cpt<=cptcovs;cpt++){
8098: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8099: }
1.337 brouard 8100: /* fprintf(fichtm,"************ Results for covariates"); */
8101: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8102: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8103: /* } */
8104: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8105: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8106: /* } */
1.264 brouard 8107: if(invalidvarcomb[k1]){
8108: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8109: continue;
8110: }
8111: fprintf(fichtm,"</a></li>");
8112: } /* cptcovn >0 */
8113: }
1.317 brouard 8114: fprintf(fichtm," \n</ul>");
1.264 brouard 8115:
1.222 brouard 8116: jj1=0;
1.237 brouard 8117:
1.337 brouard 8118: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8119: /* k1=nres; */
1.338 brouard 8120: k1=TKresult[nres];
8121: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8122: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8123: /* if(m != 1 && TKresult[nres]!= k1) */
8124: /* continue; */
1.220 brouard 8125:
1.222 brouard 8126: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8127: jj1++;
8128: if (cptcovn > 0) {
1.264 brouard 8129: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8130: for (cpt=1; cpt<=cptcovs;cpt++){
8131: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8132: }
1.337 brouard 8133: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8134: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8135: /* } */
1.264 brouard 8136: fprintf(fichtm,"\"</a>");
8137:
1.222 brouard 8138: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8139: for (cpt=1; cpt<=cptcovs;cpt++){
8140: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8141: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8142: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8143: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8144: }
1.230 brouard 8145: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8146: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8147: if(invalidvarcomb[k1]){
8148: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8149: printf("\nCombination (%d) ignored because no cases \n",k1);
8150: continue;
8151: }
8152: }
8153: /* aij, bij */
1.259 brouard 8154: 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 8155: <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 8156: /* Pij */
1.241 brouard 8157: 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> \
8158: <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 8159: /* Quasi-incidences */
8160: 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 8161: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8162: 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 8163: 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> \
8164: <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 8165: /* Survival functions (period) in state j */
8166: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8167: 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);
8168: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8169: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8170: }
8171: /* State specific survival functions (period) */
8172: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8173: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8174: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8175: <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);
8176: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8177: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8178: }
1.288 brouard 8179: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8180: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8181: 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 8182: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8183: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8184: }
1.296 brouard 8185: if(prevbcast==1){
1.288 brouard 8186: /* Backward prevalence in each health state */
1.222 brouard 8187: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8188: 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);
8189: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8190: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8191: }
1.217 brouard 8192: }
1.222 brouard 8193: if(prevfcast==1){
1.288 brouard 8194: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8195: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8196: 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);
8197: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8198: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8199: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8200: }
8201: }
1.296 brouard 8202: if(prevbcast==1){
1.268 brouard 8203: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8204: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8205: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8206: 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 \
8207: 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 8208: 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);
8209: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8210: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8211: }
8212: }
1.220 brouard 8213:
1.222 brouard 8214: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8215: 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);
8216: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8217: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8218: }
8219: /* } /\* end i1 *\/ */
1.337 brouard 8220: }/* End k1=nres */
1.222 brouard 8221: fprintf(fichtm,"</ul>");
1.126 brouard 8222:
1.222 brouard 8223: fprintf(fichtm,"\
1.126 brouard 8224: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8225: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8226: - 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 8227: But because parameters are usually highly correlated (a higher incidence of disability \
8228: and a higher incidence of recovery can give very close observed transition) it might \
8229: be very useful to look not only at linear confidence intervals estimated from the \
8230: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8231: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8232: covariance matrix of the one-step probabilities. \
8233: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8234:
1.222 brouard 8235: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8236: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8237: fprintf(fichtm,"\
1.126 brouard 8238: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8239: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8240:
1.222 brouard 8241: fprintf(fichtm,"\
1.126 brouard 8242: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8243: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8244: fprintf(fichtm,"\
1.126 brouard 8245: - 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): \
8246: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8247: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8248: fprintf(fichtm,"\
1.126 brouard 8249: - (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): \
8250: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8251: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8252: fprintf(fichtm,"\
1.288 brouard 8253: - 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 8254: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8255: fprintf(fichtm,"\
1.128 brouard 8256: - 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 8257: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8258: fprintf(fichtm,"\
1.288 brouard 8259: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8260: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8261:
8262: /* if(popforecast==1) fprintf(fichtm,"\n */
8263: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8264: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8265: /* <br>",fileres,fileres,fileres,fileres); */
8266: /* else */
1.338 brouard 8267: /* 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 8268: fflush(fichtm);
1.126 brouard 8269:
1.225 brouard 8270: m=pow(2,cptcoveff);
1.222 brouard 8271: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8272:
1.317 brouard 8273: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8274:
8275: jj1=0;
8276:
8277: fprintf(fichtm," \n<ul>");
1.337 brouard 8278: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8279: /* k1=nres; */
1.338 brouard 8280: k1=TKresult[nres];
1.337 brouard 8281: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8282: /* if(m != 1 && TKresult[nres]!= k1) */
8283: /* continue; */
1.317 brouard 8284: jj1++;
8285: if (cptcovn > 0) {
8286: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8287: for (cpt=1; cpt<=cptcovs;cpt++){
8288: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8289: }
8290: fprintf(fichtm,"\">");
8291:
8292: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8293: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8294: for (cpt=1; cpt<=cptcovs;cpt++){
8295: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8296: }
8297: if(invalidvarcomb[k1]){
8298: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8299: continue;
8300: }
8301: fprintf(fichtm,"</a></li>");
8302: } /* cptcovn >0 */
1.337 brouard 8303: } /* End nres */
1.317 brouard 8304: fprintf(fichtm," \n</ul>");
8305:
1.222 brouard 8306: jj1=0;
1.237 brouard 8307:
1.241 brouard 8308: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8309: /* k1=nres; */
1.338 brouard 8310: k1=TKresult[nres];
8311: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8312: /* for(k1=1; k1<=m;k1++){ */
8313: /* if(m != 1 && TKresult[nres]!= k1) */
8314: /* continue; */
1.222 brouard 8315: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8316: jj1++;
1.126 brouard 8317: if (cptcovn > 0) {
1.317 brouard 8318: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8319: for (cpt=1; cpt<=cptcovs;cpt++){
8320: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8321: }
8322: fprintf(fichtm,"\"</a>");
8323:
1.126 brouard 8324: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8325: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8326: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8327: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8328: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8329: }
1.237 brouard 8330:
1.338 brouard 8331: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8332:
1.222 brouard 8333: if(invalidvarcomb[k1]){
8334: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8335: continue;
8336: }
1.337 brouard 8337: } /* If cptcovn >0 */
1.126 brouard 8338: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8339: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8340: 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);
8341: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8342: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8343: }
8344: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8345: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8346: true period expectancies (those weighted with period prevalences are also\
8347: drawn in addition to the population based expectancies computed using\
1.314 brouard 8348: 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);
8349: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8350: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8351: /* } /\* end i1 *\/ */
1.241 brouard 8352: }/* End nres */
1.222 brouard 8353: fprintf(fichtm,"</ul>");
8354: fflush(fichtm);
1.126 brouard 8355: }
8356:
8357: /******************* Gnuplot file **************/
1.296 brouard 8358: 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 8359:
8360: char dirfileres[132],optfileres[132];
1.264 brouard 8361: char gplotcondition[132], gplotlabel[132];
1.343 brouard 8362: 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 8363: int lv=0, vlv=0, kl=0;
1.130 brouard 8364: int ng=0;
1.201 brouard 8365: int vpopbased;
1.223 brouard 8366: int ioffset; /* variable offset for columns */
1.270 brouard 8367: int iyearc=1; /* variable column for year of projection */
8368: int iagec=1; /* variable column for age of projection */
1.235 brouard 8369: int nres=0; /* Index of resultline */
1.266 brouard 8370: int istart=1; /* For starting graphs in projections */
1.219 brouard 8371:
1.126 brouard 8372: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8373: /* printf("Problem with file %s",optionfilegnuplot); */
8374: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8375: /* } */
8376:
8377: /*#ifdef windows */
8378: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8379: /*#endif */
1.225 brouard 8380: m=pow(2,cptcoveff);
1.126 brouard 8381:
1.274 brouard 8382: /* diagram of the model */
8383: fprintf(ficgp,"\n#Diagram of the model \n");
8384: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8385: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8386: 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);
8387:
1.343 brouard 8388: 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 8389: fprintf(ficgp,"\n#show arrow\nunset label\n");
8390: 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);
8391: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8392: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8393: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8394: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8395:
1.202 brouard 8396: /* Contribution to likelihood */
8397: /* Plot the probability implied in the likelihood */
1.223 brouard 8398: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8399: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8400: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8401: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8402: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8403: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8404: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8405: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8406: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8407: 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));
8408: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8409: 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));
8410: for (i=1; i<= nlstate ; i ++) {
8411: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8412: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8413: 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);
8414: for (j=2; j<= nlstate+ndeath ; j ++) {
8415: 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);
8416: }
8417: fprintf(ficgp,";\nset out; unset ylabel;\n");
8418: }
8419: /* 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 */
8420: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8421: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8422: fprintf(ficgp,"\nset out;unset log\n");
8423: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8424:
1.343 brouard 8425: /* Plot the probability implied in the likelihood by covariate value */
8426: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8427: /* if(debugILK==1){ */
8428: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8429: kvar=Tvar[TvarFind[kf]]; /* variable name */
8430: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 8431: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
8432: k=19+kf;/*offset because there are 19 columns in the ILK_ file */
1.343 brouard 8433: for (i=1; i<= nlstate ; i ++) {
8434: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8435: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8436: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8437: 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);
8438: for (j=2; j<= nlstate+ndeath ; j ++) {
8439: 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);
8440: }
8441: }else{
8442: 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);
8443: for (j=2; j<= nlstate+ndeath ; j ++) {
8444: 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);
8445: }
1.343 brouard 8446: }
8447: fprintf(ficgp,";\nset out; unset ylabel;\n");
8448: }
8449: } /* End of each covariate dummy */
8450: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8451: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8452: * kmodel = 1 2 3 4 5 6 7 8 9
8453: * varying 1 2 3 4 5
8454: * ncovv 1 2 3 4 5 6 7 8
8455: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8456: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8457: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8458: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8459: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8460: */
8461: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8462: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8463: /* 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]); */
8464: if(ipos!=iposold){ /* Not a product or first of a product */
8465: /* printf(" %d",ipos); */
8466: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8467: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8468: kk++; /* Position of the ncovv column in ILK_ */
8469: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8470: 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) */
8471: for (i=1; i<= nlstate ; i ++) {
8472: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8473: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8474:
1.348 brouard 8475: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8476: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8477: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8478: 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);
8479: for (j=2; j<= nlstate+ndeath ; j ++) {
8480: 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);
8481: }
8482: }else{
8483: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8484: 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);
8485: for (j=2; j<= nlstate+ndeath ; j ++) {
8486: 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);
8487: }
8488: }
8489: fprintf(ficgp,";\nset out; unset ylabel;\n");
8490: }
8491: }/* End if dummy varying */
8492: }else{ /*Product */
8493: /* printf("*"); */
8494: /* fprintf(ficresilk,"*"); */
8495: }
8496: iposold=ipos;
8497: } /* For each time varying covariate */
8498: /* } /\* debugILK==1 *\/ */
8499: /* 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 */
8500: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8501: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8502: fprintf(ficgp,"\nset out;unset log\n");
8503: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8504:
8505:
8506:
1.126 brouard 8507: strcpy(dirfileres,optionfilefiname);
8508: strcpy(optfileres,"vpl");
1.223 brouard 8509: /* 1eme*/
1.238 brouard 8510: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8511: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8512: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8513: k1=TKresult[nres];
1.338 brouard 8514: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8515: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8516: /* if(m != 1 && TKresult[nres]!= k1) */
8517: /* continue; */
1.238 brouard 8518: /* We are interested in selected combination by the resultline */
1.246 brouard 8519: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8520: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8521: strcpy(gplotlabel,"(");
1.337 brouard 8522: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8523: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8524: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8525:
8526: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8527: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8528: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8529: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8530: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8531: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8532: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8533: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8534: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8535: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8536: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8537: /* } */
8538: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8539: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8540: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8541: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8542: }
8543: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8544: /* printf("\n#\n"); */
1.238 brouard 8545: fprintf(ficgp,"\n#\n");
8546: if(invalidvarcomb[k1]){
1.260 brouard 8547: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8548: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8549: continue;
8550: }
1.235 brouard 8551:
1.241 brouard 8552: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8553: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8554: /* 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 8555: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8556: 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);
8557: /* 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); */
8558: /* k1-1 error should be nres-1*/
1.238 brouard 8559: for (i=1; i<= nlstate ; i ++) {
8560: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8561: else fprintf(ficgp," %%*lf (%%*lf)");
8562: }
1.288 brouard 8563: 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 8564: for (i=1; i<= nlstate ; i ++) {
8565: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8566: else fprintf(ficgp," %%*lf (%%*lf)");
8567: }
1.260 brouard 8568: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8569: for (i=1; i<= nlstate ; i ++) {
8570: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8571: else fprintf(ficgp," %%*lf (%%*lf)");
8572: }
1.265 brouard 8573: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8574:
8575: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8576: if(cptcoveff ==0){
1.271 brouard 8577: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8578: }else{
8579: kl=0;
8580: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8581: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8582: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8583: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8584: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8585: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8586: vlv= nbcode[Tvaraff[k]][lv];
8587: kl++;
8588: /* 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 *\/ */
8589: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8590: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8591: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8592: if(k==cptcoveff){
8593: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8594: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8595: }else{
8596: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8597: kl++;
8598: }
8599: } /* end covariate */
8600: } /* end if no covariate */
8601:
1.296 brouard 8602: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8603: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8604: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8605: if(cptcoveff ==0){
1.245 brouard 8606: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8607: }else{
8608: kl=0;
8609: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8610: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8611: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8612: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8613: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8614: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8615: /* vlv= nbcode[Tvaraff[k]][lv]; */
8616: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8617: kl++;
1.238 brouard 8618: /* 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 *\/ */
8619: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8620: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8621: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8622: if(k==cptcoveff){
1.245 brouard 8623: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8624: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8625: }else{
1.332 brouard 8626: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8627: kl++;
8628: }
8629: } /* end covariate */
8630: } /* end if no covariate */
1.296 brouard 8631: if(prevbcast == 1){
1.268 brouard 8632: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8633: /* k1-1 error should be nres-1*/
8634: for (i=1; i<= nlstate ; i ++) {
8635: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8636: else fprintf(ficgp," %%*lf (%%*lf)");
8637: }
1.271 brouard 8638: 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 8639: for (i=1; i<= nlstate ; i ++) {
8640: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8641: else fprintf(ficgp," %%*lf (%%*lf)");
8642: }
1.276 brouard 8643: 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 8644: for (i=1; i<= nlstate ; i ++) {
8645: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8646: else fprintf(ficgp," %%*lf (%%*lf)");
8647: }
1.274 brouard 8648: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8649: } /* end if backprojcast */
1.296 brouard 8650: } /* end if prevbcast */
1.276 brouard 8651: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8652: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8653: } /* nres */
1.337 brouard 8654: /* } /\* k1 *\/ */
1.201 brouard 8655: } /* cpt */
1.235 brouard 8656:
8657:
1.126 brouard 8658: /*2 eme*/
1.337 brouard 8659: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8660: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8661: k1=TKresult[nres];
1.338 brouard 8662: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8663: /* if(m != 1 && TKresult[nres]!= k1) */
8664: /* continue; */
1.238 brouard 8665: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8666: strcpy(gplotlabel,"(");
1.337 brouard 8667: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8668: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8669: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8670: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8671: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8672: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8673: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8674: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8675: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8676: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8677: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8678: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8679: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8680: /* } */
8681: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8682: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8683: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8684: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8685: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8686: }
1.264 brouard 8687: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8688: fprintf(ficgp,"\n#\n");
1.223 brouard 8689: if(invalidvarcomb[k1]){
8690: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8691: continue;
8692: }
1.219 brouard 8693:
1.241 brouard 8694: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8695: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8696: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8697: if(vpopbased==0){
1.238 brouard 8698: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8699: }else
1.238 brouard 8700: fprintf(ficgp,"\nreplot ");
8701: for (i=1; i<= nlstate+1 ; i ++) {
8702: k=2*i;
1.261 brouard 8703: 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 8704: for (j=1; j<= nlstate+1 ; j ++) {
8705: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8706: else fprintf(ficgp," %%*lf (%%*lf)");
8707: }
8708: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8709: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8710: 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 8711: for (j=1; j<= nlstate+1 ; j ++) {
8712: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8713: else fprintf(ficgp," %%*lf (%%*lf)");
8714: }
8715: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8716: 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 8717: for (j=1; j<= nlstate+1 ; j ++) {
8718: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8719: else fprintf(ficgp," %%*lf (%%*lf)");
8720: }
8721: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8722: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8723: } /* state */
8724: } /* vpopbased */
1.264 brouard 8725: 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 8726: } /* end nres */
1.337 brouard 8727: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8728:
8729:
8730: /*3eme*/
1.337 brouard 8731: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8732: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8733: k1=TKresult[nres];
1.338 brouard 8734: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8735: /* if(m != 1 && TKresult[nres]!= k1) */
8736: /* continue; */
1.238 brouard 8737:
1.332 brouard 8738: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8739: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8740: strcpy(gplotlabel,"(");
1.337 brouard 8741: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8742: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8743: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8744: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8745: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8746: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8747: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8748: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8749: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8750: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8751: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8752: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8753: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8754: /* } */
8755: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8756: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8757: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8758: }
1.264 brouard 8759: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8760: fprintf(ficgp,"\n#\n");
8761: if(invalidvarcomb[k1]){
8762: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8763: continue;
8764: }
8765:
8766: /* k=2+nlstate*(2*cpt-2); */
8767: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8768: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8769: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8770: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8771: 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 8772: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8773: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8774: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8775: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8776: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8777: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8778:
1.238 brouard 8779: */
8780: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8781: 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 8782: /* 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 8783:
1.238 brouard 8784: }
1.261 brouard 8785: 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 8786: }
1.264 brouard 8787: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8788: } /* end nres */
1.337 brouard 8789: /* } /\* end kl 3eme *\/ */
1.126 brouard 8790:
1.223 brouard 8791: /* 4eme */
1.201 brouard 8792: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8793: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8794: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8795: k1=TKresult[nres];
1.338 brouard 8796: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8797: /* if(m != 1 && TKresult[nres]!= k1) */
8798: /* continue; */
1.238 brouard 8799: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8800: strcpy(gplotlabel,"(");
1.337 brouard 8801: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8802: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8803: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8804: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8805: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8806: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8807: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8808: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8809: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8810: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8811: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8812: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8813: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8814: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8815: /* } */
8816: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8817: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8818: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8819: }
1.264 brouard 8820: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8821: fprintf(ficgp,"\n#\n");
8822: if(invalidvarcomb[k1]){
8823: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8824: continue;
1.223 brouard 8825: }
1.238 brouard 8826:
1.241 brouard 8827: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8828: 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 8829: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8830: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8831: k=3;
8832: for (i=1; i<= nlstate ; i ++){
8833: if(i==1){
8834: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8835: }else{
8836: fprintf(ficgp,", '' ");
8837: }
8838: l=(nlstate+ndeath)*(i-1)+1;
8839: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8840: for (j=2; j<= nlstate+ndeath ; j ++)
8841: fprintf(ficgp,"+$%d",k+l+j-1);
8842: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8843: } /* nlstate */
1.264 brouard 8844: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8845: } /* end cpt state*/
8846: } /* end nres */
1.337 brouard 8847: /* } /\* end covariate k1 *\/ */
1.238 brouard 8848:
1.220 brouard 8849: /* 5eme */
1.201 brouard 8850: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8851: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8852: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8853: k1=TKresult[nres];
1.338 brouard 8854: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8855: /* if(m != 1 && TKresult[nres]!= k1) */
8856: /* continue; */
1.238 brouard 8857: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8858: strcpy(gplotlabel,"(");
1.238 brouard 8859: 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 8860: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8861: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8862: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8863: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8864: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8865: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8866: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8867: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8868: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8869: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8870: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8871: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8872: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8873: /* } */
8874: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8875: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8876: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8877: }
1.264 brouard 8878: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8879: fprintf(ficgp,"\n#\n");
8880: if(invalidvarcomb[k1]){
8881: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8882: continue;
8883: }
1.227 brouard 8884:
1.241 brouard 8885: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8886: 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 8887: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8888: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8889: k=3;
8890: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8891: if(j==1)
8892: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8893: else
8894: fprintf(ficgp,", '' ");
8895: l=(nlstate+ndeath)*(cpt-1) +j;
8896: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8897: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8898: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8899: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8900: } /* nlstate */
8901: fprintf(ficgp,", '' ");
8902: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8903: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8904: l=(nlstate+ndeath)*(cpt-1) +j;
8905: if(j < nlstate)
8906: fprintf(ficgp,"$%d +",k+l);
8907: else
8908: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8909: }
1.264 brouard 8910: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8911: } /* end cpt state*/
1.337 brouard 8912: /* } /\* end covariate *\/ */
1.238 brouard 8913: } /* end nres */
1.227 brouard 8914:
1.220 brouard 8915: /* 6eme */
1.202 brouard 8916: /* CV preval stable (period) for each covariate */
1.337 brouard 8917: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8918: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8919: k1=TKresult[nres];
1.338 brouard 8920: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8921: /* if(m != 1 && TKresult[nres]!= k1) */
8922: /* continue; */
1.255 brouard 8923: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8924: strcpy(gplotlabel,"(");
1.288 brouard 8925: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8926: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8927: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8928: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8929: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8930: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8931: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8932: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8933: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8934: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8935: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8936: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8937: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8938: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8939: /* } */
8940: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8941: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8942: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8943: }
1.264 brouard 8944: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8945: fprintf(ficgp,"\n#\n");
1.223 brouard 8946: if(invalidvarcomb[k1]){
1.227 brouard 8947: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8948: continue;
1.223 brouard 8949: }
1.227 brouard 8950:
1.241 brouard 8951: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8952: 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 8953: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8954: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8955: k=3; /* Offset */
1.255 brouard 8956: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8957: if(i==1)
8958: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8959: else
8960: fprintf(ficgp,", '' ");
1.255 brouard 8961: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8962: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8963: for (j=2; j<= nlstate ; j ++)
8964: fprintf(ficgp,"+$%d",k+l+j-1);
8965: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8966: } /* nlstate */
1.264 brouard 8967: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8968: } /* end cpt state*/
8969: } /* end covariate */
1.227 brouard 8970:
8971:
1.220 brouard 8972: /* 7eme */
1.296 brouard 8973: if(prevbcast == 1){
1.288 brouard 8974: /* CV backward prevalence for each covariate */
1.337 brouard 8975: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8976: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8977: k1=TKresult[nres];
1.338 brouard 8978: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8979: /* if(m != 1 && TKresult[nres]!= k1) */
8980: /* continue; */
1.268 brouard 8981: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8982: strcpy(gplotlabel,"(");
1.288 brouard 8983: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8984: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8985: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8986: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8987: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8988: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8989: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8990: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8991: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8992: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8993: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8994: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8995: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8996: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8997: /* } */
8998: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8999: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9000: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9001: }
1.264 brouard 9002: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9003: fprintf(ficgp,"\n#\n");
9004: if(invalidvarcomb[k1]){
9005: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9006: continue;
9007: }
9008:
1.241 brouard 9009: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 9010: 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 9011: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 9012: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 9013: k=3; /* Offset */
1.268 brouard 9014: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 9015: if(i==1)
9016: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
9017: else
9018: fprintf(ficgp,", '' ");
9019: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 9020: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 9021: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
9022: /* 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 9023: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 9024: /* for (j=2; j<= nlstate ; j ++) */
9025: /* fprintf(ficgp,"+$%d",k+l+j-1); */
9026: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 9027: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 9028: } /* nlstate */
1.264 brouard 9029: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 9030: } /* end cpt state*/
9031: } /* end covariate */
1.296 brouard 9032: } /* End if prevbcast */
1.218 brouard 9033:
1.223 brouard 9034: /* 8eme */
1.218 brouard 9035: if(prevfcast==1){
1.288 brouard 9036: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9037:
1.337 brouard 9038: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9039: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9040: k1=TKresult[nres];
1.338 brouard 9041: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9042: /* if(m != 1 && TKresult[nres]!= k1) */
9043: /* continue; */
1.211 brouard 9044: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9045: strcpy(gplotlabel,"(");
1.288 brouard 9046: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9047: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9048: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9049: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9050: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9051: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9052: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9053: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9054: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9055: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9056: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9057: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9058: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9059: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9060: /* } */
9061: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9062: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9063: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9064: }
1.264 brouard 9065: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9066: fprintf(ficgp,"\n#\n");
9067: if(invalidvarcomb[k1]){
9068: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9069: continue;
9070: }
9071:
9072: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9073: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9074: 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 9075: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9076: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9077:
9078: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9079: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9080: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9081: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9082: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9083: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9084: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9085: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9086: if(i==istart){
1.227 brouard 9087: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9088: }else{
9089: fprintf(ficgp,",\\\n '' ");
9090: }
9091: if(cptcoveff ==0){ /* No covariate */
9092: ioffset=2; /* Age is in 2 */
9093: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9094: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9095: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9096: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9097: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9098: if(i==nlstate+1){
1.270 brouard 9099: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9100: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9101: fprintf(ficgp,",\\\n '' ");
9102: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9103: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9104: offyear, \
1.268 brouard 9105: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9106: }else
1.227 brouard 9107: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9108: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9109: }else{ /* more than 2 covariates */
1.270 brouard 9110: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9111: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9112: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9113: iyearc=ioffset-1;
9114: iagec=ioffset;
1.227 brouard 9115: fprintf(ficgp," u %d:(",ioffset);
9116: kl=0;
9117: strcpy(gplotcondition,"(");
1.351 brouard 9118: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 9119: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 9120: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9121: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9122: lv=Tvresult[nres][k];
9123: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 9124: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9125: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9126: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9127: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 9128: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 9129: kl++;
1.351 brouard 9130: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9131: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 9132: kl++;
1.351 brouard 9133: if(k <cptcovs && cptcovs>1)
1.227 brouard 9134: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9135: }
9136: strcpy(gplotcondition+strlen(gplotcondition),")");
9137: /* 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 *\/ */
9138: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9139: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9140: /* '' 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*/
9141: if(i==nlstate+1){
1.270 brouard 9142: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9143: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9144: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9145: fprintf(ficgp," u %d:(",iagec);
9146: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9147: iyearc, iagec, offyear, \
9148: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9149: /* '' 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 9150: }else{
9151: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9152: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9153: }
9154: } /* end if covariate */
9155: } /* nlstate */
1.264 brouard 9156: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9157: } /* end cpt state*/
9158: } /* end covariate */
9159: } /* End if prevfcast */
1.227 brouard 9160:
1.296 brouard 9161: if(prevbcast==1){
1.268 brouard 9162: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9163:
1.337 brouard 9164: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9165: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9166: k1=TKresult[nres];
1.338 brouard 9167: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9168: /* if(m != 1 && TKresult[nres]!= k1) */
9169: /* continue; */
1.268 brouard 9170: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9171: strcpy(gplotlabel,"(");
9172: 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 9173: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9174: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9175: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9176: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9177: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9178: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9179: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9180: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9181: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9182: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9183: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9184: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9185: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9186: /* } */
9187: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9188: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9189: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9190: }
9191: strcpy(gplotlabel+strlen(gplotlabel),")");
9192: fprintf(ficgp,"\n#\n");
9193: if(invalidvarcomb[k1]){
9194: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9195: continue;
9196: }
9197:
9198: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9199: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9200: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9201: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9202: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9203:
9204: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9205: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9206: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9207: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9208: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9209: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9210: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9211: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9212: if(i==istart){
9213: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9214: }else{
9215: fprintf(ficgp,",\\\n '' ");
9216: }
1.351 brouard 9217: /* if(cptcoveff ==0){ /\* No covariate *\/ */
9218: if(cptcovs ==0){ /* No covariate */
1.268 brouard 9219: ioffset=2; /* Age is in 2 */
9220: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9221: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9222: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9223: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9224: fprintf(ficgp," u %d:(", ioffset);
9225: if(i==nlstate+1){
1.270 brouard 9226: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9227: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9228: fprintf(ficgp,",\\\n '' ");
9229: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9230: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9231: offbyear, \
9232: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9233: }else
9234: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9235: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9236: }else{ /* more than 2 covariates */
1.270 brouard 9237: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9238: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9239: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9240: iyearc=ioffset-1;
9241: iagec=ioffset;
1.268 brouard 9242: fprintf(ficgp," u %d:(",ioffset);
9243: kl=0;
9244: strcpy(gplotcondition,"(");
1.337 brouard 9245: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9246: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9247: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9248: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9249: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9250: lv=Tvresult[nres][k];
9251: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9252: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9253: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9254: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9255: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9256: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9257: kl++;
9258: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9259: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9260: kl++;
1.338 brouard 9261: if(k <cptcovs && cptcovs>1)
1.337 brouard 9262: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9263: }
1.268 brouard 9264: }
9265: strcpy(gplotcondition+strlen(gplotcondition),")");
9266: /* 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 *\/ */
9267: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9268: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9269: /* '' 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*/
9270: if(i==nlstate+1){
1.270 brouard 9271: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9272: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9273: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9274: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9275: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9276: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9277: iyearc,iagec,offbyear, \
9278: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9279: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9280: }else{
9281: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9282: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9283: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9284: }
9285: } /* end if covariate */
9286: } /* nlstate */
9287: fprintf(ficgp,"\nset out; unset label;\n");
9288: } /* end cpt state*/
9289: } /* end covariate */
1.296 brouard 9290: } /* End if prevbcast */
1.268 brouard 9291:
1.227 brouard 9292:
1.238 brouard 9293: /* 9eme writing MLE parameters */
9294: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9295: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9296: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9297: for(k=1; k <=(nlstate+ndeath); k++){
9298: if (k != i) {
1.227 brouard 9299: fprintf(ficgp,"# current state %d\n",k);
9300: for(j=1; j <=ncovmodel; j++){
9301: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9302: jk++;
9303: }
9304: fprintf(ficgp,"\n");
1.126 brouard 9305: }
9306: }
1.223 brouard 9307: }
1.187 brouard 9308: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9309:
1.145 brouard 9310: /*goto avoid;*/
1.238 brouard 9311: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9312: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9313: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9314: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9315: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9316: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9317: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9318: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9319: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9320: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9321: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9322: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9323: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9324: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9325: fprintf(ficgp,"#\n");
1.223 brouard 9326: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9327: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9328: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9329: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 9330: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
9331: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 9332: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9333: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9334: /* k1=nres; */
1.338 brouard 9335: k1=TKresult[nres];
9336: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9337: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9338: strcpy(gplotlabel,"(");
1.276 brouard 9339: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9340: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9341: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9342: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9343: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9344: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9345: }
9346: /* if(m != 1 && TKresult[nres]!= k1) */
9347: /* continue; */
9348: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9349: /* strcpy(gplotlabel,"("); */
9350: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9351: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9352: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9353: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9354: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9355: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9356: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9357: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9358: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9359: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9360: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9361: /* } */
9362: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9363: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9364: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9365: /* } */
1.264 brouard 9366: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9367: fprintf(ficgp,"\n#\n");
1.264 brouard 9368: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9369: fprintf(ficgp,"\nset key outside ");
9370: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9371: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9372: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9373: if (ng==1){
9374: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9375: fprintf(ficgp,"\nunset log y");
9376: }else if (ng==2){
9377: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9378: fprintf(ficgp,"\nset log y");
9379: }else if (ng==3){
9380: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9381: fprintf(ficgp,"\nset log y");
9382: }else
9383: fprintf(ficgp,"\nunset title ");
9384: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9385: i=1;
9386: for(k2=1; k2<=nlstate; k2++) {
9387: k3=i;
9388: for(k=1; k<=(nlstate+ndeath); k++) {
9389: if (k != k2){
9390: switch( ng) {
9391: case 1:
9392: if(nagesqr==0)
9393: fprintf(ficgp," p%d+p%d*x",i,i+1);
9394: else /* nagesqr =1 */
9395: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9396: break;
9397: case 2: /* ng=2 */
9398: if(nagesqr==0)
9399: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9400: else /* nagesqr =1 */
9401: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9402: break;
9403: case 3:
9404: if(nagesqr==0)
9405: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9406: else /* nagesqr =1 */
9407: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9408: break;
9409: }
9410: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9411: ijp=1; /* product no age */
9412: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9413: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9414: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9415: switch(Typevar[j]){
9416: case 1:
9417: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9418: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9419: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9420: if(DummyV[j]==0){/* Bug valgrind */
9421: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9422: }else{ /* quantitative */
9423: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9424: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9425: }
9426: ij++;
1.268 brouard 9427: }
1.237 brouard 9428: }
1.329 brouard 9429: }
9430: break;
9431: case 2:
9432: if(cptcovprod >0){
9433: if(j==Tprod[ijp]) { /* */
9434: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9435: if(ijp <=cptcovprod) { /* Product */
9436: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9437: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9438: /* 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)]); */
9439: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9440: }else{ /* Vn is dummy and Vm is quanti */
9441: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9442: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9443: }
9444: }else{ /* Vn*Vm Vn is quanti */
9445: if(DummyV[Tvard[ijp][2]]==0){
9446: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9447: }else{ /* Both quanti */
9448: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9449: }
1.268 brouard 9450: }
1.329 brouard 9451: ijp++;
1.237 brouard 9452: }
1.329 brouard 9453: } /* end Tprod */
9454: }
9455: break;
1.349 brouard 9456: case 3:
9457: if(cptcovdageprod >0){
9458: /* if(j==Tprod[ijp]) { */ /* not necessary */
9459: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 9460: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
9461: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9462: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9463: /* 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)]); */
9464: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9465: }else{ /* Vn is dummy and Vm is quanti */
9466: /* 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 9467: 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 9468: }
1.350 brouard 9469: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 9470: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 9471: 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 9472: }else{ /* Both quanti */
1.350 brouard 9473: 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 9474: }
9475: }
9476: ijp++;
9477: }
9478: /* } */ /* end Tprod */
9479: }
9480: break;
1.329 brouard 9481: case 0:
9482: /* simple covariate */
1.264 brouard 9483: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9484: if(Dummy[j]==0){
9485: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9486: }else{ /* quantitative */
9487: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9488: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9489: }
1.329 brouard 9490: /* end simple */
9491: break;
9492: default:
9493: break;
9494: } /* end switch */
1.237 brouard 9495: } /* end j */
1.329 brouard 9496: }else{ /* k=k2 */
9497: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9498: fprintf(ficgp," (1.");i=i-ncovmodel;
9499: }else
9500: i=i-ncovmodel;
1.223 brouard 9501: }
1.227 brouard 9502:
1.223 brouard 9503: if(ng != 1){
9504: fprintf(ficgp,")/(1");
1.227 brouard 9505:
1.264 brouard 9506: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9507: if(nagesqr==0)
1.264 brouard 9508: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9509: else /* nagesqr =1 */
1.264 brouard 9510: 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 9511:
1.223 brouard 9512: ij=1;
1.329 brouard 9513: ijp=1;
9514: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9515: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9516: switch(Typevar[j]){
9517: case 1:
9518: if(cptcovage >0){
9519: if(j==Tage[ij]) { /* Bug valgrind */
9520: if(ij <=cptcovage) { /* Bug valgrind */
9521: if(DummyV[j]==0){/* Bug valgrind */
9522: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9523: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9524: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9525: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9526: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9527: }else{ /* quantitative */
9528: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9529: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9530: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9531: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9532: }
9533: ij++;
9534: }
9535: }
9536: }
9537: break;
9538: case 2:
9539: if(cptcovprod >0){
9540: if(j==Tprod[ijp]) { /* */
9541: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9542: if(ijp <=cptcovprod) { /* Product */
9543: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9544: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9545: /* 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)]); */
9546: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9547: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9548: }else{ /* Vn is dummy and Vm is quanti */
9549: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9550: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9551: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9552: }
9553: }else{ /* Vn*Vm Vn is quanti */
9554: if(DummyV[Tvard[ijp][2]]==0){
9555: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9556: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9557: }else{ /* Both quanti */
9558: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9559: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9560: }
9561: }
9562: ijp++;
9563: }
9564: } /* end Tprod */
9565: } /* end if */
9566: break;
1.349 brouard 9567: case 3:
9568: if(cptcovdageprod >0){
9569: /* if(j==Tprod[ijp]) { /\* *\/ */
9570: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9571: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 9572: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9573: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9574: /* 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 9575: 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 9576: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9577: }else{ /* Vn is dummy and Vm is quanti */
9578: /* 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 9579: 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 9580: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9581: }
9582: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 9583: if(DummyV[Tvardk[ijp][2]]==0){
9584: 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 9585: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9586: }else{ /* Both quanti */
1.350 brouard 9587: 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 9588: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9589: }
9590: }
9591: ijp++;
9592: }
9593: /* } /\* end Tprod *\/ */
9594: } /* end if */
9595: break;
1.329 brouard 9596: case 0:
9597: /* simple covariate */
9598: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9599: if(Dummy[j]==0){
9600: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9601: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9602: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9603: }else{ /* quantitative */
9604: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9605: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9606: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9607: }
9608: /* end simple */
9609: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9610: break;
9611: default:
9612: break;
9613: } /* end switch */
1.223 brouard 9614: }
9615: fprintf(ficgp,")");
9616: }
9617: fprintf(ficgp,")");
9618: if(ng ==2)
1.276 brouard 9619: 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 9620: else /* ng= 3 */
1.276 brouard 9621: 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 9622: }else{ /* end ng <> 1 */
1.223 brouard 9623: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9624: 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 9625: }
9626: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9627: fprintf(ficgp,",");
9628: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9629: fprintf(ficgp,",");
9630: i=i+ncovmodel;
9631: } /* end k */
9632: } /* end k2 */
1.276 brouard 9633: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9634: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9635: } /* end resultline */
1.223 brouard 9636: } /* end ng */
9637: /* avoid: */
9638: fflush(ficgp);
1.126 brouard 9639: } /* end gnuplot */
9640:
9641:
9642: /*************** Moving average **************/
1.219 brouard 9643: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9644: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9645:
1.222 brouard 9646: int i, cpt, cptcod;
9647: int modcovmax =1;
9648: int mobilavrange, mob;
9649: int iage=0;
1.288 brouard 9650: int firstA1=0, firstA2=0;
1.222 brouard 9651:
1.266 brouard 9652: double sum=0., sumr=0.;
1.222 brouard 9653: double age;
1.266 brouard 9654: double *sumnewp, *sumnewm, *sumnewmr;
9655: double *agemingood, *agemaxgood;
9656: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9657:
9658:
1.278 brouard 9659: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9660: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9661:
9662: sumnewp = vector(1,ncovcombmax);
9663: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9664: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9665: agemingood = vector(1,ncovcombmax);
1.266 brouard 9666: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9667: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9668: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9669:
9670: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9671: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9672: sumnewp[cptcod]=0.;
1.266 brouard 9673: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9674: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9675: }
9676: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9677:
1.266 brouard 9678: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9679: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9680: else mobilavrange=mobilav;
9681: for (age=bage; age<=fage; age++)
9682: for (i=1; i<=nlstate;i++)
9683: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9684: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9685: /* We keep the original values on the extreme ages bage, fage and for
9686: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9687: we use a 5 terms etc. until the borders are no more concerned.
9688: */
9689: for (mob=3;mob <=mobilavrange;mob=mob+2){
9690: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9691: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9692: sumnewm[cptcod]=0.;
9693: for (i=1; i<=nlstate;i++){
1.222 brouard 9694: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9695: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9696: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9697: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9698: }
9699: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9700: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9701: } /* end i */
9702: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9703: } /* end cptcod */
1.222 brouard 9704: }/* end age */
9705: }/* end mob */
1.266 brouard 9706: }else{
9707: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9708: return -1;
1.266 brouard 9709: }
9710:
9711: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9712: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9713: if(invalidvarcomb[cptcod]){
9714: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9715: continue;
9716: }
1.219 brouard 9717:
1.266 brouard 9718: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9719: sumnewm[cptcod]=0.;
9720: sumnewmr[cptcod]=0.;
9721: for (i=1; i<=nlstate;i++){
9722: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9723: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9724: }
9725: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9726: agemingoodr[cptcod]=age;
9727: }
9728: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9729: agemingood[cptcod]=age;
9730: }
9731: } /* age */
9732: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9733: sumnewm[cptcod]=0.;
1.266 brouard 9734: sumnewmr[cptcod]=0.;
1.222 brouard 9735: for (i=1; i<=nlstate;i++){
9736: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9737: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9738: }
9739: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9740: agemaxgoodr[cptcod]=age;
1.222 brouard 9741: }
9742: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9743: agemaxgood[cptcod]=age;
9744: }
9745: } /* age */
9746: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9747: /* but they will change */
1.288 brouard 9748: firstA1=0;firstA2=0;
1.266 brouard 9749: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9750: sumnewm[cptcod]=0.;
9751: sumnewmr[cptcod]=0.;
9752: for (i=1; i<=nlstate;i++){
9753: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9754: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9755: }
9756: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9757: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9758: agemaxgoodr[cptcod]=age; /* age min */
9759: for (i=1; i<=nlstate;i++)
9760: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9761: }else{ /* bad we change the value with the values of good ages */
9762: for (i=1; i<=nlstate;i++){
9763: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9764: } /* i */
9765: } /* end bad */
9766: }else{
9767: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9768: agemaxgood[cptcod]=age;
9769: }else{ /* bad we change the value with the values of good ages */
9770: for (i=1; i<=nlstate;i++){
9771: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9772: } /* i */
9773: } /* end bad */
9774: }/* end else */
9775: sum=0.;sumr=0.;
9776: for (i=1; i<=nlstate;i++){
9777: sum+=mobaverage[(int)age][i][cptcod];
9778: sumr+=probs[(int)age][i][cptcod];
9779: }
9780: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9781: if(!firstA1){
9782: firstA1=1;
9783: 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);
9784: }
9785: 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 9786: } /* end bad */
9787: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9788: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9789: if(!firstA2){
9790: firstA2=1;
9791: 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);
9792: }
9793: 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 9794: } /* end bad */
9795: }/* age */
1.266 brouard 9796:
9797: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9798: sumnewm[cptcod]=0.;
1.266 brouard 9799: sumnewmr[cptcod]=0.;
1.222 brouard 9800: for (i=1; i<=nlstate;i++){
9801: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9802: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9803: }
9804: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9805: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9806: agemingoodr[cptcod]=age;
9807: for (i=1; i<=nlstate;i++)
9808: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9809: }else{ /* bad we change the value with the values of good ages */
9810: for (i=1; i<=nlstate;i++){
9811: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9812: } /* i */
9813: } /* end bad */
9814: }else{
9815: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9816: agemingood[cptcod]=age;
9817: }else{ /* bad */
9818: for (i=1; i<=nlstate;i++){
9819: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9820: } /* i */
9821: } /* end bad */
9822: }/* end else */
9823: sum=0.;sumr=0.;
9824: for (i=1; i<=nlstate;i++){
9825: sum+=mobaverage[(int)age][i][cptcod];
9826: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9827: }
1.266 brouard 9828: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9829: 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 9830: } /* end bad */
9831: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9832: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9833: 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 9834: } /* end bad */
9835: }/* age */
1.266 brouard 9836:
1.222 brouard 9837:
9838: for (age=bage; age<=fage; age++){
1.235 brouard 9839: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9840: sumnewp[cptcod]=0.;
9841: sumnewm[cptcod]=0.;
9842: for (i=1; i<=nlstate;i++){
9843: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9844: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9845: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9846: }
9847: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9848: }
9849: /* printf("\n"); */
9850: /* } */
1.266 brouard 9851:
1.222 brouard 9852: /* brutal averaging */
1.266 brouard 9853: /* for (i=1; i<=nlstate;i++){ */
9854: /* for (age=1; age<=bage; age++){ */
9855: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9856: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9857: /* } */
9858: /* for (age=fage; age<=AGESUP; age++){ */
9859: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9860: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9861: /* } */
9862: /* } /\* end i status *\/ */
9863: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9864: /* for (age=1; age<=AGESUP; age++){ */
9865: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9866: /* mobaverage[(int)age][i][cptcod]=0.; */
9867: /* } */
9868: /* } */
1.222 brouard 9869: }/* end cptcod */
1.266 brouard 9870: free_vector(agemaxgoodr,1, ncovcombmax);
9871: free_vector(agemaxgood,1, ncovcombmax);
9872: free_vector(agemingood,1, ncovcombmax);
9873: free_vector(agemingoodr,1, ncovcombmax);
9874: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9875: free_vector(sumnewm,1, ncovcombmax);
9876: free_vector(sumnewp,1, ncovcombmax);
9877: return 0;
9878: }/* End movingaverage */
1.218 brouard 9879:
1.126 brouard 9880:
1.296 brouard 9881:
1.126 brouard 9882: /************** Forecasting ******************/
1.296 brouard 9883: /* 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)*/
9884: 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){
9885: /* dateintemean, mean date of interviews
9886: dateprojd, year, month, day of starting projection
9887: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9888: agemin, agemax range of age
9889: dateprev1 dateprev2 range of dates during which prevalence is computed
9890: */
1.296 brouard 9891: /* double anprojd, mprojd, jprojd; */
9892: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9893: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9894: double agec; /* generic age */
1.296 brouard 9895: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9896: double *popeffectif,*popcount;
9897: double ***p3mat;
1.218 brouard 9898: /* double ***mobaverage; */
1.126 brouard 9899: char fileresf[FILENAMELENGTH];
9900:
9901: agelim=AGESUP;
1.211 brouard 9902: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9903: in each health status at the date of interview (if between dateprev1 and dateprev2).
9904: We still use firstpass and lastpass as another selection.
9905: */
1.214 brouard 9906: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9907: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9908:
1.201 brouard 9909: strcpy(fileresf,"F_");
9910: strcat(fileresf,fileresu);
1.126 brouard 9911: if((ficresf=fopen(fileresf,"w"))==NULL) {
9912: printf("Problem with forecast resultfile: %s\n", fileresf);
9913: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9914: }
1.235 brouard 9915: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9916: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9917:
1.225 brouard 9918: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9919:
9920:
9921: stepsize=(int) (stepm+YEARM-1)/YEARM;
9922: if (stepm<=12) stepsize=1;
9923: if(estepm < stepm){
9924: printf ("Problem %d lower than %d\n",estepm, stepm);
9925: }
1.270 brouard 9926: else{
9927: hstepm=estepm;
9928: }
9929: if(estepm > stepm){ /* Yes every two year */
9930: stepsize=2;
9931: }
1.296 brouard 9932: hstepm=hstepm/stepm;
1.126 brouard 9933:
1.296 brouard 9934:
9935: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9936: /* fractional in yp1 *\/ */
9937: /* aintmean=yp; */
9938: /* yp2=modf((yp1*12),&yp); */
9939: /* mintmean=yp; */
9940: /* yp1=modf((yp2*30.5),&yp); */
9941: /* jintmean=yp; */
9942: /* if(jintmean==0) jintmean=1; */
9943: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9944:
1.296 brouard 9945:
9946: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9947: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9948: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 9949: /* i1=pow(2,cptcoveff); */
9950: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 9951:
1.296 brouard 9952: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9953:
9954: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9955:
1.126 brouard 9956: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 9957: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9958: k=TKresult[nres];
9959: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
9960: /* 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) *\/ */
9961: /* if(i1 != 1 && TKresult[nres]!= k) */
9962: /* continue; */
9963: /* if(invalidvarcomb[k]){ */
9964: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
9965: /* continue; */
9966: /* } */
1.227 brouard 9967: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 9968: for(j=1;j<=cptcovs;j++){
9969: /* for(j=1;j<=cptcoveff;j++) { */
9970: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
9971: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9972: /* } */
9973: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9974: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9975: /* } */
9976: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 9977: }
1.351 brouard 9978:
1.227 brouard 9979: fprintf(ficresf," yearproj age");
9980: for(j=1; j<=nlstate+ndeath;j++){
9981: for(i=1; i<=nlstate;i++)
9982: fprintf(ficresf," p%d%d",i,j);
9983: fprintf(ficresf," wp.%d",j);
9984: }
1.296 brouard 9985: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9986: fprintf(ficresf,"\n");
1.296 brouard 9987: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9988: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9989: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9990: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9991: nhstepm = nhstepm/hstepm;
9992: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9993: oldm=oldms;savm=savms;
1.268 brouard 9994: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9995: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9996: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9997: for (h=0; h<=nhstepm; h++){
9998: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9999: break;
10000: }
10001: }
10002: fprintf(ficresf,"\n");
1.351 brouard 10003: /* for(j=1;j<=cptcoveff;j++) */
10004: for(j=1;j<=cptcovs;j++)
10005: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 10006: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 10007: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 10008: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 10009:
10010: for(j=1; j<=nlstate+ndeath;j++) {
10011: ppij=0.;
10012: for(i=1; i<=nlstate;i++) {
1.278 brouard 10013: if (mobilav>=1)
10014: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
10015: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
10016: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
10017: }
1.268 brouard 10018: fprintf(ficresf," %.3f", p3mat[i][j][h]);
10019: } /* end i */
10020: fprintf(ficresf," %.3f", ppij);
10021: }/* end j */
1.227 brouard 10022: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10023: } /* end agec */
1.266 brouard 10024: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
10025: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 10026: } /* end yearp */
10027: } /* end k */
1.219 brouard 10028:
1.126 brouard 10029: fclose(ficresf);
1.215 brouard 10030: printf("End of Computing forecasting \n");
10031: fprintf(ficlog,"End of Computing forecasting\n");
10032:
1.126 brouard 10033: }
10034:
1.269 brouard 10035: /************** Back Forecasting ******************/
1.296 brouard 10036: /* 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){ */
10037: 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){
10038: /* back1, year, month, day of starting backprojection
1.267 brouard 10039: agemin, agemax range of age
10040: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 10041: anback2 year of end of backprojection (same day and month as back1).
10042: prevacurrent and prev are prevalences.
1.267 brouard 10043: */
10044: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
10045: double agec; /* generic age */
1.302 brouard 10046: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10047: double *popeffectif,*popcount;
10048: double ***p3mat;
10049: /* double ***mobaverage; */
10050: char fileresfb[FILENAMELENGTH];
10051:
1.268 brouard 10052: agelim=AGEINF;
1.267 brouard 10053: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10054: in each health status at the date of interview (if between dateprev1 and dateprev2).
10055: We still use firstpass and lastpass as another selection.
10056: */
10057: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10058: /* firstpass, lastpass, stepm, weightopt, model); */
10059:
10060: /*Do we need to compute prevalence again?*/
10061:
10062: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10063:
10064: strcpy(fileresfb,"FB_");
10065: strcat(fileresfb,fileresu);
10066: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10067: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10068: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10069: }
10070: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10071: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10072:
10073: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10074:
10075:
10076: stepsize=(int) (stepm+YEARM-1)/YEARM;
10077: if (stepm<=12) stepsize=1;
10078: if(estepm < stepm){
10079: printf ("Problem %d lower than %d\n",estepm, stepm);
10080: }
1.270 brouard 10081: else{
10082: hstepm=estepm;
10083: }
10084: if(estepm >= stepm){ /* Yes every two year */
10085: stepsize=2;
10086: }
1.267 brouard 10087:
10088: hstepm=hstepm/stepm;
1.296 brouard 10089: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10090: /* fractional in yp1 *\/ */
10091: /* aintmean=yp; */
10092: /* yp2=modf((yp1*12),&yp); */
10093: /* mintmean=yp; */
10094: /* yp1=modf((yp2*30.5),&yp); */
10095: /* jintmean=yp; */
10096: /* if(jintmean==0) jintmean=1; */
10097: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10098:
1.351 brouard 10099: /* i1=pow(2,cptcoveff); */
10100: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 10101:
1.296 brouard 10102: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10103: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10104:
10105: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10106:
1.351 brouard 10107: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10108: k=TKresult[nres];
10109: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
10110: /* for(k=1; k<=i1;k++){ */
10111: /* if(i1 != 1 && TKresult[nres]!= k) */
10112: /* continue; */
10113: /* if(invalidvarcomb[k]){ */
10114: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
10115: /* continue; */
10116: /* } */
1.268 brouard 10117: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 10118: for(j=1;j<=cptcovs;j++){
10119: /* for(j=1;j<=cptcoveff;j++) { */
10120: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10121: /* } */
10122: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 10123: }
1.351 brouard 10124: /* fprintf(ficrespij,"******\n"); */
10125: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10126: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10127: /* } */
1.267 brouard 10128: fprintf(ficresfb," yearbproj age");
10129: for(j=1; j<=nlstate+ndeath;j++){
10130: for(i=1; i<=nlstate;i++)
1.268 brouard 10131: fprintf(ficresfb," b%d%d",i,j);
10132: fprintf(ficresfb," b.%d",j);
1.267 brouard 10133: }
1.296 brouard 10134: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10135: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10136: fprintf(ficresfb,"\n");
1.296 brouard 10137: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10138: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10139: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10140: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10141: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10142: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10143: nhstepm = nhstepm/hstepm;
10144: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10145: oldm=oldms;savm=savms;
1.268 brouard 10146: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10147: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10148: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10149: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10150: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10151: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10152: for (h=0; h<=nhstepm; h++){
1.268 brouard 10153: if (h*hstepm/YEARM*stepm ==-yearp) {
10154: break;
10155: }
10156: }
10157: fprintf(ficresfb,"\n");
1.351 brouard 10158: /* for(j=1;j<=cptcoveff;j++) */
10159: for(j=1;j<=cptcovs;j++)
10160: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10161: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 10162: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10163: for(i=1; i<=nlstate+ndeath;i++) {
10164: ppij=0.;ppi=0.;
10165: for(j=1; j<=nlstate;j++) {
10166: /* if (mobilav==1) */
1.269 brouard 10167: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10168: ppi=ppi+prevacurrent[(int)agec][j][k];
10169: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10170: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10171: /* else { */
10172: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10173: /* } */
1.268 brouard 10174: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10175: } /* end j */
10176: if(ppi <0.99){
10177: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10178: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10179: }
10180: fprintf(ficresfb," %.3f", ppij);
10181: }/* end j */
1.267 brouard 10182: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10183: } /* end agec */
10184: } /* end yearp */
10185: } /* end k */
1.217 brouard 10186:
1.267 brouard 10187: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10188:
1.267 brouard 10189: fclose(ficresfb);
10190: printf("End of Computing Back forecasting \n");
10191: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10192:
1.267 brouard 10193: }
1.217 brouard 10194:
1.269 brouard 10195: /* Variance of prevalence limit: varprlim */
10196: 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 10197: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10198:
10199: char fileresvpl[FILENAMELENGTH];
10200: FILE *ficresvpl;
10201: double **oldm, **savm;
10202: double **varpl; /* Variances of prevalence limits by age */
10203: int i1, k, nres, j ;
10204:
10205: strcpy(fileresvpl,"VPL_");
10206: strcat(fileresvpl,fileresu);
10207: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10208: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10209: exit(0);
10210: }
1.288 brouard 10211: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10212: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10213:
10214: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10215: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10216:
10217: i1=pow(2,cptcoveff);
10218: if (cptcovn < 1){i1=1;}
10219:
1.337 brouard 10220: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10221: k=TKresult[nres];
1.338 brouard 10222: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10223: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10224: if(i1 != 1 && TKresult[nres]!= k)
10225: continue;
10226: fprintf(ficresvpl,"\n#****** ");
10227: printf("\n#****** ");
10228: fprintf(ficlog,"\n#****** ");
1.337 brouard 10229: for(j=1;j<=cptcovs;j++) {
10230: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10231: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10232: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10233: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10234: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10235: }
1.337 brouard 10236: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10237: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10238: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10239: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10240: /* } */
1.269 brouard 10241: fprintf(ficresvpl,"******\n");
10242: printf("******\n");
10243: fprintf(ficlog,"******\n");
10244:
10245: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10246: oldm=oldms;savm=savms;
10247: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10248: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10249: /*}*/
10250: }
10251:
10252: fclose(ficresvpl);
1.288 brouard 10253: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10254: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10255:
10256: }
10257: /* Variance of back prevalence: varbprlim */
10258: 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){
10259: /*------- Variance of back (stable) prevalence------*/
10260:
10261: char fileresvbl[FILENAMELENGTH];
10262: FILE *ficresvbl;
10263:
10264: double **oldm, **savm;
10265: double **varbpl; /* Variances of back prevalence limits by age */
10266: int i1, k, nres, j ;
10267:
10268: strcpy(fileresvbl,"VBL_");
10269: strcat(fileresvbl,fileresu);
10270: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10271: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10272: exit(0);
10273: }
10274: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10275: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10276:
10277:
10278: i1=pow(2,cptcoveff);
10279: if (cptcovn < 1){i1=1;}
10280:
1.337 brouard 10281: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10282: k=TKresult[nres];
1.338 brouard 10283: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10284: /* for(k=1; k<=i1;k++){ */
10285: /* if(i1 != 1 && TKresult[nres]!= k) */
10286: /* continue; */
1.269 brouard 10287: fprintf(ficresvbl,"\n#****** ");
10288: printf("\n#****** ");
10289: fprintf(ficlog,"\n#****** ");
1.337 brouard 10290: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10291: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10292: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10293: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10294: /* for(j=1;j<=cptcoveff;j++) { */
10295: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10296: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10297: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10298: /* } */
10299: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10300: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10301: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10302: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10303: }
10304: fprintf(ficresvbl,"******\n");
10305: printf("******\n");
10306: fprintf(ficlog,"******\n");
10307:
10308: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10309: oldm=oldms;savm=savms;
10310:
10311: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10312: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10313: /*}*/
10314: }
10315:
10316: fclose(ficresvbl);
10317: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10318: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10319:
10320: } /* End of varbprlim */
10321:
1.126 brouard 10322: /************** Forecasting *****not tested NB*************/
1.227 brouard 10323: /* 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 10324:
1.227 brouard 10325: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10326: /* int *popage; */
10327: /* double calagedatem, agelim, kk1, kk2; */
10328: /* double *popeffectif,*popcount; */
10329: /* double ***p3mat,***tabpop,***tabpopprev; */
10330: /* /\* double ***mobaverage; *\/ */
10331: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10332:
1.227 brouard 10333: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10334: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10335: /* agelim=AGESUP; */
10336: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10337:
1.227 brouard 10338: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10339:
10340:
1.227 brouard 10341: /* strcpy(filerespop,"POP_"); */
10342: /* strcat(filerespop,fileresu); */
10343: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10344: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10345: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10346: /* } */
10347: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10348: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10349:
1.227 brouard 10350: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10351:
1.227 brouard 10352: /* /\* if (mobilav!=0) { *\/ */
10353: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10354: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10355: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10356: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10357: /* /\* } *\/ */
10358: /* /\* } *\/ */
1.126 brouard 10359:
1.227 brouard 10360: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10361: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10362:
1.227 brouard 10363: /* agelim=AGESUP; */
1.126 brouard 10364:
1.227 brouard 10365: /* hstepm=1; */
10366: /* hstepm=hstepm/stepm; */
1.218 brouard 10367:
1.227 brouard 10368: /* if (popforecast==1) { */
10369: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10370: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10371: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10372: /* } */
10373: /* popage=ivector(0,AGESUP); */
10374: /* popeffectif=vector(0,AGESUP); */
10375: /* popcount=vector(0,AGESUP); */
1.126 brouard 10376:
1.227 brouard 10377: /* i=1; */
10378: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10379:
1.227 brouard 10380: /* imx=i; */
10381: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10382: /* } */
1.218 brouard 10383:
1.227 brouard 10384: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10385: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10386: /* k=k+1; */
10387: /* fprintf(ficrespop,"\n#******"); */
10388: /* for(j=1;j<=cptcoveff;j++) { */
10389: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10390: /* } */
10391: /* fprintf(ficrespop,"******\n"); */
10392: /* fprintf(ficrespop,"# Age"); */
10393: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10394: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10395:
1.227 brouard 10396: /* for (cpt=0; cpt<=0;cpt++) { */
10397: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10398:
1.227 brouard 10399: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10400: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10401: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10402:
1.227 brouard 10403: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10404: /* oldm=oldms;savm=savms; */
10405: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10406:
1.227 brouard 10407: /* for (h=0; h<=nhstepm; h++){ */
10408: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10409: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10410: /* } */
10411: /* for(j=1; j<=nlstate+ndeath;j++) { */
10412: /* kk1=0.;kk2=0; */
10413: /* for(i=1; i<=nlstate;i++) { */
10414: /* if (mobilav==1) */
10415: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10416: /* else { */
10417: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10418: /* } */
10419: /* } */
10420: /* if (h==(int)(calagedatem+12*cpt)){ */
10421: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10422: /* /\*fprintf(ficrespop," %.3f", kk1); */
10423: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10424: /* } */
10425: /* } */
10426: /* for(i=1; i<=nlstate;i++){ */
10427: /* kk1=0.; */
10428: /* for(j=1; j<=nlstate;j++){ */
10429: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10430: /* } */
10431: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10432: /* } */
1.218 brouard 10433:
1.227 brouard 10434: /* if (h==(int)(calagedatem+12*cpt)) */
10435: /* for(j=1; j<=nlstate;j++) */
10436: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10437: /* } */
10438: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10439: /* } */
10440: /* } */
1.218 brouard 10441:
1.227 brouard 10442: /* /\******\/ */
1.218 brouard 10443:
1.227 brouard 10444: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10445: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10446: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10447: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10448: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10449:
1.227 brouard 10450: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10451: /* oldm=oldms;savm=savms; */
10452: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10453: /* for (h=0; h<=nhstepm; h++){ */
10454: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10455: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10456: /* } */
10457: /* for(j=1; j<=nlstate+ndeath;j++) { */
10458: /* kk1=0.;kk2=0; */
10459: /* for(i=1; i<=nlstate;i++) { */
10460: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10461: /* } */
10462: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10463: /* } */
10464: /* } */
10465: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10466: /* } */
10467: /* } */
10468: /* } */
10469: /* } */
1.218 brouard 10470:
1.227 brouard 10471: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10472:
1.227 brouard 10473: /* if (popforecast==1) { */
10474: /* free_ivector(popage,0,AGESUP); */
10475: /* free_vector(popeffectif,0,AGESUP); */
10476: /* free_vector(popcount,0,AGESUP); */
10477: /* } */
10478: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10479: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10480: /* fclose(ficrespop); */
10481: /* } /\* End of popforecast *\/ */
1.218 brouard 10482:
1.126 brouard 10483: int fileappend(FILE *fichier, char *optionfich)
10484: {
10485: if((fichier=fopen(optionfich,"a"))==NULL) {
10486: printf("Problem with file: %s\n", optionfich);
10487: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10488: return (0);
10489: }
10490: fflush(fichier);
10491: return (1);
10492: }
10493:
10494:
10495: /**************** function prwizard **********************/
10496: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10497: {
10498:
10499: /* Wizard to print covariance matrix template */
10500:
1.164 brouard 10501: char ca[32], cb[32];
10502: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10503: int numlinepar;
10504:
10505: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10506: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10507: for(i=1; i <=nlstate; i++){
10508: jj=0;
10509: for(j=1; j <=nlstate+ndeath; j++){
10510: if(j==i) continue;
10511: jj++;
10512: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10513: printf("%1d%1d",i,j);
10514: fprintf(ficparo,"%1d%1d",i,j);
10515: for(k=1; k<=ncovmodel;k++){
10516: /* printf(" %lf",param[i][j][k]); */
10517: /* fprintf(ficparo," %lf",param[i][j][k]); */
10518: printf(" 0.");
10519: fprintf(ficparo," 0.");
10520: }
10521: printf("\n");
10522: fprintf(ficparo,"\n");
10523: }
10524: }
10525: printf("# Scales (for hessian or gradient estimation)\n");
10526: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10527: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
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: fprintf(ficparo,"%1d%1d",i,j);
10534: printf("%1d%1d",i,j);
10535: fflush(stdout);
10536: for(k=1; k<=ncovmodel;k++){
10537: /* printf(" %le",delti3[i][j][k]); */
10538: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10539: printf(" 0.");
10540: fprintf(ficparo," 0.");
10541: }
10542: numlinepar++;
10543: printf("\n");
10544: fprintf(ficparo,"\n");
10545: }
10546: }
10547: printf("# Covariance matrix\n");
10548: /* # 121 Var(a12)\n\ */
10549: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10550: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10551: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10552: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10553: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10554: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10555: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10556: fflush(stdout);
10557: fprintf(ficparo,"# Covariance matrix\n");
10558: /* # 121 Var(a12)\n\ */
10559: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10560: /* # ...\n\ */
10561: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10562:
10563: for(itimes=1;itimes<=2;itimes++){
10564: jj=0;
10565: for(i=1; i <=nlstate; i++){
10566: for(j=1; j <=nlstate+ndeath; j++){
10567: if(j==i) continue;
10568: for(k=1; k<=ncovmodel;k++){
10569: jj++;
10570: ca[0]= k+'a'-1;ca[1]='\0';
10571: if(itimes==1){
10572: printf("#%1d%1d%d",i,j,k);
10573: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10574: }else{
10575: printf("%1d%1d%d",i,j,k);
10576: fprintf(ficparo,"%1d%1d%d",i,j,k);
10577: /* printf(" %.5le",matcov[i][j]); */
10578: }
10579: ll=0;
10580: for(li=1;li <=nlstate; li++){
10581: for(lj=1;lj <=nlstate+ndeath; lj++){
10582: if(lj==li) continue;
10583: for(lk=1;lk<=ncovmodel;lk++){
10584: ll++;
10585: if(ll<=jj){
10586: cb[0]= lk +'a'-1;cb[1]='\0';
10587: if(ll<jj){
10588: if(itimes==1){
10589: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10590: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10591: }else{
10592: printf(" 0.");
10593: fprintf(ficparo," 0.");
10594: }
10595: }else{
10596: if(itimes==1){
10597: printf(" Var(%s%1d%1d)",ca,i,j);
10598: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10599: }else{
10600: printf(" 0.");
10601: fprintf(ficparo," 0.");
10602: }
10603: }
10604: }
10605: } /* end lk */
10606: } /* end lj */
10607: } /* end li */
10608: printf("\n");
10609: fprintf(ficparo,"\n");
10610: numlinepar++;
10611: } /* end k*/
10612: } /*end j */
10613: } /* end i */
10614: } /* end itimes */
10615:
10616: } /* end of prwizard */
10617: /******************* Gompertz Likelihood ******************************/
10618: double gompertz(double x[])
10619: {
1.302 brouard 10620: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10621: int i,n=0; /* n is the size of the sample */
10622:
1.220 brouard 10623: for (i=1;i<=imx ; i++) {
1.126 brouard 10624: sump=sump+weight[i];
10625: /* sump=sump+1;*/
10626: num=num+1;
10627: }
1.302 brouard 10628: L=0.0;
10629: /* agegomp=AGEGOMP; */
1.126 brouard 10630: /* for (i=0; i<=imx; i++)
10631: 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]);*/
10632:
1.302 brouard 10633: for (i=1;i<=imx ; i++) {
10634: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10635: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10636: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10637: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10638: * +
10639: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10640: */
10641: if (wav[i] > 1 || agedc[i] < AGESUP) {
10642: if (cens[i] == 1){
10643: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10644: } else if (cens[i] == 0){
1.126 brouard 10645: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10646: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10647: } else
10648: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10649: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10650: L=L+A*weight[i];
1.126 brouard 10651: /* 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 10652: }
10653: }
1.126 brouard 10654:
1.302 brouard 10655: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10656:
10657: return -2*L*num/sump;
10658: }
10659:
1.136 brouard 10660: #ifdef GSL
10661: /******************* Gompertz_f Likelihood ******************************/
10662: double gompertz_f(const gsl_vector *v, void *params)
10663: {
1.302 brouard 10664: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10665: double *x= (double *) v->data;
10666: int i,n=0; /* n is the size of the sample */
10667:
10668: for (i=0;i<=imx-1 ; i++) {
10669: sump=sump+weight[i];
10670: /* sump=sump+1;*/
10671: num=num+1;
10672: }
10673:
10674:
10675: /* for (i=0; i<=imx; i++)
10676: 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]);*/
10677: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10678: for (i=1;i<=imx ; i++)
10679: {
10680: if (cens[i] == 1 && wav[i]>1)
10681: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10682:
10683: if (cens[i] == 0 && wav[i]>1)
10684: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10685: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10686:
10687: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10688: if (wav[i] > 1 ) { /* ??? */
10689: LL=LL+A*weight[i];
10690: /* 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]);*/
10691: }
10692: }
10693:
10694: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10695: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10696:
10697: return -2*LL*num/sump;
10698: }
10699: #endif
10700:
1.126 brouard 10701: /******************* Printing html file ***********/
1.201 brouard 10702: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10703: int lastpass, int stepm, int weightopt, char model[],\
10704: int imx, double p[],double **matcov,double agemortsup){
10705: int i,k;
10706:
10707: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10708: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10709: for (i=1;i<=2;i++)
10710: 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 10711: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10712: fprintf(fichtm,"</ul>");
10713:
10714: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10715:
10716: 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>");
10717:
10718: for (k=agegomp;k<(agemortsup-2);k++)
10719: 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]);
10720:
10721:
10722: fflush(fichtm);
10723: }
10724:
10725: /******************* Gnuplot file **************/
1.201 brouard 10726: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10727:
10728: char dirfileres[132],optfileres[132];
1.164 brouard 10729:
1.126 brouard 10730: int ng;
10731:
10732:
10733: /*#ifdef windows */
10734: fprintf(ficgp,"cd \"%s\" \n",pathc);
10735: /*#endif */
10736:
10737:
10738: strcpy(dirfileres,optionfilefiname);
10739: strcpy(optfileres,"vpl");
1.199 brouard 10740: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10741: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10742: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10743: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10744: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10745:
10746: }
10747:
1.136 brouard 10748: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10749: {
1.126 brouard 10750:
1.136 brouard 10751: /*-------- data file ----------*/
10752: FILE *fic;
10753: char dummy[]=" ";
1.240 brouard 10754: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10755: int lstra;
1.136 brouard 10756: int linei, month, year,iout;
1.302 brouard 10757: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10758: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10759: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10760: char *stratrunc;
1.223 brouard 10761:
1.349 brouard 10762: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
10763: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10764:
10765: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10766:
1.136 brouard 10767: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10768: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10769: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10770: }
1.126 brouard 10771:
1.302 brouard 10772: /* Is it a BOM UTF-8 Windows file? */
10773: /* First data line */
10774: linei=0;
10775: while(fgets(line, MAXLINE, fic)) {
10776: noffset=0;
10777: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10778: {
10779: noffset=noffset+3;
10780: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10781: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10782: fflush(ficlog); return 1;
10783: }
10784: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10785: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10786: {
10787: noffset=noffset+2;
1.304 brouard 10788: 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);
10789: 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 10790: fflush(ficlog); return 1;
10791: }
10792: else if( line[0] == 0 && line[1] == 0)
10793: {
10794: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10795: noffset=noffset+4;
1.304 brouard 10796: 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);
10797: 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 10798: fflush(ficlog); return 1;
10799: }
10800: } else{
10801: ;/*printf(" Not a BOM file\n");*/
10802: }
10803: /* If line starts with a # it is a comment */
10804: if (line[noffset] == '#') {
10805: linei=linei+1;
10806: break;
10807: }else{
10808: break;
10809: }
10810: }
10811: fclose(fic);
10812: if((fic=fopen(datafile,"r"))==NULL) {
10813: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10814: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10815: }
10816: /* Not a Bom file */
10817:
1.136 brouard 10818: i=1;
10819: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10820: linei=linei+1;
10821: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10822: if(line[j] == '\t')
10823: line[j] = ' ';
10824: }
10825: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10826: ;
10827: };
10828: line[j+1]=0; /* Trims blanks at end of line */
10829: if(line[0]=='#'){
10830: fprintf(ficlog,"Comment line\n%s\n",line);
10831: printf("Comment line\n%s\n",line);
10832: continue;
10833: }
10834: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10835: strcpy(line, linetmp);
1.223 brouard 10836:
10837: /* Loops on waves */
10838: for (j=maxwav;j>=1;j--){
10839: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10840: cutv(stra, strb, line, ' ');
10841: if(strb[0]=='.') { /* Missing value */
10842: lval=-1;
10843: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10844: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10845: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10846: 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);
10847: 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);
10848: return 1;
10849: }
10850: }else{
10851: errno=0;
10852: /* what_kind_of_number(strb); */
10853: dval=strtod(strb,&endptr);
10854: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10855: /* if(strb != endptr && *endptr == '\0') */
10856: /* dval=dlval; */
10857: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10858: if( strb[0]=='\0' || (*endptr != '\0')){
10859: 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);
10860: 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);
10861: return 1;
10862: }
10863: cotqvar[j][iv][i]=dval;
1.341 brouard 10864: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10865: }
10866: strcpy(line,stra);
1.223 brouard 10867: }/* end loop ntqv */
1.225 brouard 10868:
1.223 brouard 10869: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10870: cutv(stra, strb, line, ' ');
10871: if(strb[0]=='.') { /* Missing value */
10872: lval=-1;
10873: }else{
10874: errno=0;
10875: lval=strtol(strb,&endptr,10);
10876: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10877: if( strb[0]=='\0' || (*endptr != '\0')){
10878: 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);
10879: 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);
10880: return 1;
10881: }
10882: }
10883: if(lval <-1 || lval >1){
10884: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10885: 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 10886: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10887: For example, for multinomial values like 1, 2 and 3,\n \
10888: build V1=0 V2=0 for the reference value (1),\n \
10889: V1=1 V2=0 for (2) \n \
1.223 brouard 10890: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10891: output of IMaCh is often meaningless.\n \
1.319 brouard 10892: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10893: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10894: 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 10895: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10896: For example, for multinomial values like 1, 2 and 3,\n \
10897: build V1=0 V2=0 for the reference value (1),\n \
10898: V1=1 V2=0 for (2) \n \
1.223 brouard 10899: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10900: output of IMaCh is often meaningless.\n \
1.319 brouard 10901: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10902: return 1;
10903: }
1.341 brouard 10904: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10905: strcpy(line,stra);
1.223 brouard 10906: }/* end loop ntv */
1.225 brouard 10907:
1.223 brouard 10908: /* Statuses at wave */
1.137 brouard 10909: cutv(stra, strb, line, ' ');
1.223 brouard 10910: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10911: lval=-1;
1.136 brouard 10912: }else{
1.238 brouard 10913: errno=0;
10914: lval=strtol(strb,&endptr,10);
10915: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10916: if( strb[0]=='\0' || (*endptr != '\0' )){
10917: 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);
10918: 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);
10919: return 1;
10920: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10921: 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);
10922: 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 10923: return 1;
10924: }
1.136 brouard 10925: }
1.225 brouard 10926:
1.136 brouard 10927: s[j][i]=lval;
1.225 brouard 10928:
1.223 brouard 10929: /* Date of Interview */
1.136 brouard 10930: strcpy(line,stra);
10931: cutv(stra, strb,line,' ');
1.169 brouard 10932: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10933: }
1.169 brouard 10934: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10935: month=99;
10936: year=9999;
1.136 brouard 10937: }else{
1.225 brouard 10938: 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);
10939: 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);
10940: return 1;
1.136 brouard 10941: }
10942: anint[j][i]= (double) year;
1.302 brouard 10943: mint[j][i]= (double)month;
10944: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10945: /* 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]); */
10946: /* 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]); */
10947: /* } */
1.136 brouard 10948: strcpy(line,stra);
1.223 brouard 10949: } /* End loop on waves */
1.225 brouard 10950:
1.223 brouard 10951: /* Date of death */
1.136 brouard 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){
1.136 brouard 10956: month=99;
10957: year=9999;
10958: }else{
1.141 brouard 10959: 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 10960: 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);
10961: return 1;
1.136 brouard 10962: }
10963: andc[i]=(double) year;
10964: moisdc[i]=(double) month;
10965: strcpy(line,stra);
10966:
1.223 brouard 10967: /* Date of birth */
1.136 brouard 10968: cutv(stra, strb,line,' ');
1.169 brouard 10969: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10970: }
1.169 brouard 10971: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10972: month=99;
10973: year=9999;
10974: }else{
1.141 brouard 10975: 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);
10976: 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 10977: return 1;
1.136 brouard 10978: }
10979: if (year==9999) {
1.141 brouard 10980: 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);
10981: 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 10982: return 1;
10983:
1.136 brouard 10984: }
10985: annais[i]=(double)(year);
1.302 brouard 10986: moisnais[i]=(double)(month);
10987: for (j=1;j<=maxwav;j++){
10988: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10989: 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]);
10990: 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]);
10991: }
10992: }
10993:
1.136 brouard 10994: strcpy(line,stra);
1.225 brouard 10995:
1.223 brouard 10996: /* Sample weight */
1.136 brouard 10997: cutv(stra, strb,line,' ');
10998: errno=0;
10999: dval=strtod(strb,&endptr);
11000: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 11001: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
11002: 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 11003: fflush(ficlog);
11004: return 1;
11005: }
11006: weight[i]=dval;
11007: strcpy(line,stra);
1.225 brouard 11008:
1.223 brouard 11009: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
11010: cutv(stra, strb, line, ' ');
11011: if(strb[0]=='.') { /* Missing value */
1.225 brouard 11012: lval=-1;
1.311 brouard 11013: coqvar[iv][i]=NAN;
11014: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 11015: }else{
1.225 brouard 11016: errno=0;
11017: /* what_kind_of_number(strb); */
11018: dval=strtod(strb,&endptr);
11019: /* if(strb != endptr && *endptr == '\0') */
11020: /* dval=dlval; */
11021: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
11022: if( strb[0]=='\0' || (*endptr != '\0')){
11023: 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);
11024: 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);
11025: return 1;
11026: }
11027: coqvar[iv][i]=dval;
1.226 brouard 11028: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 11029: }
11030: strcpy(line,stra);
11031: }/* end loop nqv */
1.136 brouard 11032:
1.223 brouard 11033: /* Covariate values */
1.136 brouard 11034: for (j=ncovcol;j>=1;j--){
11035: cutv(stra, strb,line,' ');
1.223 brouard 11036: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 11037: lval=-1;
1.136 brouard 11038: }else{
1.225 brouard 11039: errno=0;
11040: lval=strtol(strb,&endptr,10);
11041: if( strb[0]=='\0' || (*endptr != '\0')){
11042: 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);
11043: 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);
11044: return 1;
11045: }
1.136 brouard 11046: }
11047: if(lval <-1 || lval >1){
1.225 brouard 11048: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11049: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11050: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11051: For example, for multinomial values like 1, 2 and 3,\n \
11052: build V1=0 V2=0 for the reference value (1),\n \
11053: V1=1 V2=0 for (2) \n \
1.136 brouard 11054: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11055: output of IMaCh is often meaningless.\n \
1.136 brouard 11056: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11057: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11058: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11059: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11060: For example, for multinomial values like 1, 2 and 3,\n \
11061: build V1=0 V2=0 for the reference value (1),\n \
11062: V1=1 V2=0 for (2) \n \
1.136 brouard 11063: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11064: output of IMaCh is often meaningless.\n \
1.136 brouard 11065: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11066: return 1;
1.136 brouard 11067: }
11068: covar[j][i]=(double)(lval);
11069: strcpy(line,stra);
11070: }
11071: lstra=strlen(stra);
1.225 brouard 11072:
1.136 brouard 11073: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11074: stratrunc = &(stra[lstra-9]);
11075: num[i]=atol(stratrunc);
11076: }
11077: else
11078: num[i]=atol(stra);
11079: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11080: 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;}*/
11081:
11082: i=i+1;
11083: } /* End loop reading data */
1.225 brouard 11084:
1.136 brouard 11085: *imax=i-1; /* Number of individuals */
11086: fclose(fic);
1.225 brouard 11087:
1.136 brouard 11088: return (0);
1.164 brouard 11089: /* endread: */
1.225 brouard 11090: printf("Exiting readdata: ");
11091: fclose(fic);
11092: return (1);
1.223 brouard 11093: }
1.126 brouard 11094:
1.234 brouard 11095: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11096: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11097: while (*p2 == ' ')
1.234 brouard 11098: p2++;
11099: /* while ((*p1++ = *p2++) !=0) */
11100: /* ; */
11101: /* do */
11102: /* while (*p2 == ' ') */
11103: /* p2++; */
11104: /* while (*p1++ == *p2++); */
11105: *stri=p2;
1.145 brouard 11106: }
11107:
1.330 brouard 11108: int decoderesult( char resultline[], int nres)
1.230 brouard 11109: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11110: {
1.235 brouard 11111: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11112: char resultsav[MAXLINE];
1.330 brouard 11113: /* int resultmodel[MAXLINE]; */
1.334 brouard 11114: /* int modelresult[MAXLINE]; */
1.230 brouard 11115: char stra[80], strb[80], strc[80], strd[80],stre[80];
11116:
1.234 brouard 11117: removefirstspace(&resultline);
1.332 brouard 11118: printf("decoderesult:%s\n",resultline);
1.230 brouard 11119:
1.332 brouard 11120: strcpy(resultsav,resultline);
1.342 brouard 11121: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11122: if (strlen(resultsav) >1){
1.334 brouard 11123: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11124: }
1.353 ! brouard 11125: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 11126: TKresult[nres]=0; /* Combination for the nresult and the model */
11127: return (0);
11128: }
1.234 brouard 11129: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 ! brouard 11130: 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);
! 11131: 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);
! 11132: if(j==0)
! 11133: return 1;
1.234 brouard 11134: }
1.334 brouard 11135: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11136: if(nbocc(resultsav,'=') >1){
1.318 brouard 11137: 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 11138: /* 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 11139: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11140: /* If a blank, then strc="V4=" and strd='\0' */
11141: if(strc[0]=='\0'){
11142: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11143: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11144: return 1;
11145: }
1.234 brouard 11146: }else
11147: cutl(strc,strd,resultsav,'=');
1.318 brouard 11148: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11149:
1.230 brouard 11150: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11151: 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 11152: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11153: /* cptcovsel++; */
11154: if (nbocc(stra,'=') >0)
11155: strcpy(resultsav,stra); /* and analyzes it */
11156: }
1.235 brouard 11157: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11158: /* 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 11159: 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 11160: if(Typevar[k1]==0){ /* Single covariate in model */
11161: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11162: match=0;
1.318 brouard 11163: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11164: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11165: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11166: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11167: break;
11168: }
11169: }
11170: if(match == 0){
1.338 brouard 11171: 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]);
11172: 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 11173: return 1;
1.234 brouard 11174: }
1.332 brouard 11175: }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*/
11176: /* We feed resultmodel[k1]=k2; */
11177: match=0;
11178: 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 */
11179: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11180: 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 11181: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11182: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11183: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11184: break;
11185: }
11186: }
11187: if(match == 0){
1.338 brouard 11188: 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]);
11189: 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 11190: return 1;
11191: }
1.349 brouard 11192: }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 11193: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11194: match=0;
1.342 brouard 11195: /* 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 11196: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11197: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11198: /* modelresult[k2]=k1; */
1.342 brouard 11199: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11200: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11201: }
11202: }
11203: if(match == 0){
1.349 brouard 11204: 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);
11205: 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 11206: return 1;
11207: }
11208: match=0;
11209: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11210: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11211: /* modelresult[k2]=k1;*/
1.342 brouard 11212: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11213: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11214: break;
11215: }
11216: }
11217: if(match == 0){
1.349 brouard 11218: 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);
11219: 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 11220: return 1;
11221: }
11222: }/* End of testing */
1.333 brouard 11223: }/* End loop cptcovt */
1.235 brouard 11224: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11225: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11226: 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)
11227: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11228: match=0;
1.318 brouard 11229: 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 11230: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 11231: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11232: 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 11233: 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 11234: ++match;
11235: }
11236: }
11237: }
11238: if(match == 0){
1.338 brouard 11239: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11240: 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 11241: return 1;
1.234 brouard 11242: }else if(match > 1){
1.338 brouard 11243: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11244: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11245: return 1;
1.234 brouard 11246: }
11247: }
1.334 brouard 11248: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11249: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11250: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11251: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11252: /* 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*/
11253: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11254: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11255: /* 1 0 0 0 */
11256: /* 2 1 0 0 */
11257: /* 3 0 1 0 */
1.330 brouard 11258: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11259: /* 5 0 0 1 */
1.330 brouard 11260: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11261: /* 7 0 1 1 */
11262: /* 8 1 1 1 */
1.237 brouard 11263: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11264: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11265: /* V5*age V5 known which value for nres? */
11266: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11267: 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.
11268: * loop on position k1 in the MODEL LINE */
1.331 brouard 11269: /* k counting number of combination of single dummies in the equation model */
11270: /* k4 counting single dummies in the equation model */
11271: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11272: 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 11273: /* 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 11274: /* 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 11275: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11276: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11277: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11278: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11279: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11280: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11281: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11282: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11283: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11284: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11285: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11286: 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 11287: 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 11288: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11289: /* Tinvresult[nres][4]=1 */
1.334 brouard 11290: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11291: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11292: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11293: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11294: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11295: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11296: /* 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 11297: k4++;;
1.331 brouard 11298: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11299: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11300: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11301: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11302: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11303: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11304: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11305: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11306: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11307: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11308: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11309: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11310: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11311: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11312: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11313: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11314: /* 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 11315: k4q++;;
1.350 brouard 11316: }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"*/
11317: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 11318: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 11319: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11320: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11321: /* 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]]); */
11322: }else{
11323: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11324: 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)*/
11325: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
11326: precov[nres][k1]=Tvalsel[k3];
11327: }
1.342 brouard 11328: /* 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 11329: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 11330: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11331: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11332: /* 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]]); */
11333: }else{
11334: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
11335: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
11336: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
11337: precov[nres][k1]=Tvalsel[k3q];
11338: }
1.342 brouard 11339: /* 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 11340: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11341: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 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]]); */
1.330 brouard 11343: }else{
1.332 brouard 11344: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11345: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11346: }
11347: }
1.234 brouard 11348:
1.334 brouard 11349: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11350: return (0);
11351: }
1.235 brouard 11352:
1.230 brouard 11353: int decodemodel( char model[], int lastobs)
11354: /**< This routine decodes the model and returns:
1.224 brouard 11355: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11356: * - nagesqr = 1 if age*age in the model, otherwise 0.
11357: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11358: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11359: * - cptcovage number of covariates with age*products =2
11360: * - cptcovs number of simple covariates
1.339 brouard 11361: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11362: * - 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 11363: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11364: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11365: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11366: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11367: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11368: */
1.319 brouard 11369: /* 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 11370: {
1.238 brouard 11371: int i, j, k, ks, v;
1.349 brouard 11372: int n,m;
11373: int j1, k1, k11, k12, k2, k3, k4;
11374: char modelsav[300];
11375: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11376: char *strpt;
1.349 brouard 11377: int **existcomb;
11378:
11379: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
11380: for(i=1;i<=NCOVMAX;i++)
11381: for(j=1;j<=NCOVMAX;j++)
11382: existcomb[i][j]=0;
11383:
1.145 brouard 11384: /*removespace(model);*/
1.136 brouard 11385: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 11386: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11387: if (strstr(model,"AGE") !=0){
1.192 brouard 11388: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11389: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11390: return 1;
11391: }
1.141 brouard 11392: if (strstr(model,"v") !=0){
1.338 brouard 11393: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11394: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11395: return 1;
11396: }
1.187 brouard 11397: strcpy(modelsav,model);
11398: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11399: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11400: if(strpt != model){
1.338 brouard 11401: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11402: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11403: corresponding column of parameters.\n",model);
1.338 brouard 11404: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11405: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11406: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11407: return 1;
1.225 brouard 11408: }
1.187 brouard 11409: nagesqr=1;
11410: if (strstr(model,"+age*age") !=0)
1.234 brouard 11411: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11412: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11413: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11414: else
1.234 brouard 11415: substrchaine(modelsav, model, "age*age");
1.187 brouard 11416: }else
11417: nagesqr=0;
1.349 brouard 11418: 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 11419: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11420: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 11421: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 11422: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11423: * cst, age and age*age
11424: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11425: /* including age products which are counted in cptcovage.
11426: * but the covariates which are products must be treated
11427: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 11428: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
11429: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11430: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 11431: cptcovprodage=0;
11432: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11433:
1.187 brouard 11434: /* Design
11435: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11436: * < ncovcol=8 >
11437: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11438: * k= 1 2 3 4 5 6 7 8
11439: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11440: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11441: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11442: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11443: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11444: * Tage[++cptcovage]=k
1.345 brouard 11445: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11446: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11447: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11448: * 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
11449: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11450: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11451: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11452: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11453: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11454: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11455: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11456: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11457: * p Tprod[1]@2={ 6, 5}
11458: *p Tvard[1][1]@4= {7, 8, 5, 6}
11459: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11460: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11461: *How to reorganize? Tvars(orted)
1.187 brouard 11462: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11463: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11464: * {2, 1, 4, 8, 5, 6, 3, 7}
11465: * Struct []
11466: */
1.225 brouard 11467:
1.187 brouard 11468: /* This loop fills the array Tvar from the string 'model'.*/
11469: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11470: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11471: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11472: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11473: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11474: /* k=1 Tvar[1]=2 (from V2) */
11475: /* k=5 Tvar[5] */
11476: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11477: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11478: /* } */
1.198 brouard 11479: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11480: /*
11481: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11482: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11483: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11484: }
1.187 brouard 11485: cptcovage=0;
1.351 brouard 11486:
11487: /* First loop in order to calculate */
11488: /* for age*VN*Vm
11489: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
11490: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
11491: */
11492: /* Needs FixedV[Tvardk[k][1]] */
11493: /* For others:
11494: * Sets Typevar[k];
11495: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11496: * Tposprod[k]=k11;
11497: * Tprod[k11]=k;
11498: * Tvardk[k][1] =m;
11499: * Needs FixedV[Tvardk[k][1]] == 0
11500: */
11501:
1.319 brouard 11502: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11503: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11504: 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" */
11505: if (nbocc(modelsav,'+')==0)
11506: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11507: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11508: /*scanf("%d",i);*/
1.349 brouard 11509: 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 */
11510: 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 */
11511: 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 */
11512: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
11513: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
11514: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
11515: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
11516: /* We want strb=Vn*Vm */
11517: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
11518: strcpy(strb,strd);
11519: strcat(strb,"*");
11520: strcat(strb,stre);
11521: }else{ /* strf=Vm If strf=V6 then stre=V2 */
11522: strcpy(strb,strf);
11523: strcat(strb,"*");
11524: strcat(strb,stre);
11525: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
11526: }
1.351 brouard 11527: /* 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]]]); */
11528: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 11529: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
11530: strcpy(stre,strb); /* save full b in stre */
11531: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
11532: strcpy(strf,strc); /* save short c in new short f */
11533: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
11534: /* strcpy(strc,stre);*/ /* save full e in c for future */
11535: }
11536: cptcovdageprod++; /* double product with age Which product is it? */
11537: /* 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 *\/ */
11538: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11539: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 11540: n=atoi(stre);
1.234 brouard 11541: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 11542: m=atoi(strc);
11543: cptcovage++; /* Counts the number of covariates which include age as a product */
11544: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
11545: if(existcomb[n][m] == 0){
11546: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
11547: 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);
11548: 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);
11549: fflush(ficlog);
11550: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
11551: k12++;
11552: existcomb[n][m]=k1;
11553: existcomb[m][n]=k1;
11554: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
11555: 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*/
11556: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
11557: Tvard[k1][1] =m; /* m 1 for V1*/
11558: Tvardk[k][1] =m; /* m 1 for V1*/
11559: Tvard[k1][2] =n; /* n 4 for V4*/
11560: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 11561: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 11562: 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 */
11563: for (i=1; i<=lastobs;i++){/* For fixed product */
11564: /* Computes the new covariate which is a product of
11565: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11566: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11567: }
11568: cptcovprodage++; /* Counting the number of fixed covariate with age */
11569: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11570: k12++;
11571: FixedV[ncovcolt+k12]=0;
11572: }else{ /*End of FixedV */
11573: cptcovprodvage++; /* Counting the number of varying covariate with age */
11574: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11575: k12++;
11576: FixedV[ncovcolt+k12]=1;
11577: }
11578: }else{ /* k1 Vn*Vm already exists */
11579: k11=existcomb[n][m];
11580: Tposprod[k]=k11; /* OK */
11581: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
11582: Tvardk[k][1]=m;
11583: Tvardk[k][2]=n;
11584: 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 */
11585: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11586: cptcovprodage++; /* Counting the number of fixed covariate with age */
11587: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11588: Tvar[Tage[cptcovage]]=k1;
11589: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11590: k12++;
11591: FixedV[ncovcolt+k12]=0;
11592: }else{ /* Already exists but time varying (and age) */
11593: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11594: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11595: /* Tvar[Tage[cptcovage]]=k1; */
11596: cptcovprodvage++;
11597: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11598: k12++;
11599: FixedV[ncovcolt+k12]=1;
11600: }
11601: }
11602: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
11603: /* Tvar[k]=k11; /\* HERY *\/ */
11604: } 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 */
11605: cptcovprod++;
11606: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
11607: /* covar is not filled and then is empty */
11608: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
11609: 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 */
11610: Typevar[k]=1; /* 1 for age product */
11611: cptcovage++; /* Counts the number of covariates which include age as a product */
11612: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
11613: if( FixedV[Tvar[k]] == 0){
11614: cptcovprodage++; /* Counting the number of fixed covariate with age */
11615: }else{
11616: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
11617: }
11618: /*printf("stre=%s ", stre);*/
11619: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
11620: cutl(stre,strb,strc,'V');
11621: Tvar[k]=atoi(stre);
11622: Typevar[k]=1; /* 1 for age product */
11623: cptcovage++;
11624: Tage[cptcovage]=k;
11625: if( FixedV[Tvar[k]] == 0){
11626: cptcovprodage++; /* Counting the number of fixed covariate with age */
11627: }else{
11628: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11629: }
1.349 brouard 11630: }else{ /* for product Vn*Vm */
11631: Typevar[k]=2; /* 2 for product Vn*Vm */
11632: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
11633: n=atoi(stre);
11634: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11635: m=atoi(strc);
11636: k1++;
11637: cptcovprodnoage++;
11638: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
11639: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11640: 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]);
11641: fflush(ficlog);
11642: k11=existcomb[n][m];
11643: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11644: Tposprod[k]=k11;
11645: Tprod[k11]=k;
11646: Tvardk[k][1] =m; /* m 1 for V1*/
11647: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
11648: Tvardk[k][2] =n; /* n 4 for V4*/
11649: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
11650: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
11651: existcomb[n][m]=k1;
11652: existcomb[m][n]=k1;
11653: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
11654: because this model-covariate is a construction we invent a new column
11655: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
11656: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
11657: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
11658: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
11659: /* Please remark that the new variables are model dependent */
11660: /* If we have 4 variable but the model uses only 3, like in
11661: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11662: * k= 1 2 3 4 5 6 7 8
11663: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11664: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11665: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11666: */
11667: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
11668: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
11669: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
11670: Tvard[k1][1] =m; /* m 1 for V1*/
11671: Tvardk[k][1] =m; /* m 1 for V1*/
11672: Tvard[k1][2] =n; /* n 4 for V4*/
11673: Tvardk[k][2] =n; /* n 4 for V4*/
11674: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11675: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11676: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
11677: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
11678: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
11679: 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 */
11680: for (i=1; i<=lastobs;i++){/* For fixed product */
11681: /* Computes the new covariate which is a product of
11682: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11683: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11684: }
11685: /* TvarVV[k2]=n; */
11686: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11687: /* TvarVV[k2+1]=m; */
11688: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11689: }else{ /* not FixedV */
11690: /* TvarVV[k2]=n; */
11691: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11692: /* TvarVV[k2+1]=m; */
11693: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11694: }
11695: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
11696: } /* End of product Vn*Vm */
11697: } /* End of age*double product or simple product */
11698: }else { /* not a product */
1.234 brouard 11699: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11700: /* scanf("%d",i);*/
11701: cutl(strd,strc,strb,'V');
11702: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11703: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11704: Tvar[k]=atoi(strd);
11705: Typevar[k]=0; /* 0 for simple covariates */
11706: }
11707: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11708: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11709: scanf("%d",i);*/
1.187 brouard 11710: } /* end of loop + on total covariates */
1.351 brouard 11711:
11712:
1.187 brouard 11713: } /* end if strlen(modelsave == 0) age*age might exist */
11714: } /* end if strlen(model == 0) */
1.349 brouard 11715: 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 */
11716:
1.136 brouard 11717: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11718: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11719:
1.136 brouard 11720: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11721: printf("cptcovprod=%d ", cptcovprod);
11722: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11723: scanf("%d ",i);*/
11724:
11725:
1.230 brouard 11726: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11727: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11728: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11729: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11730: k = 1 2 3 4 5 6 7 8 9
11731: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11732: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11733: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11734: Dummy[k] 1 0 0 0 3 1 1 2 3
11735: Tmodelind[combination of covar]=k;
1.225 brouard 11736: */
11737: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11738: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11739: /* 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 11740: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11741: printf("Model=1+age+%s\n\
1.349 brouard 11742: 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 11743: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11744: 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 11745: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 11746: 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 11747: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11748: 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 11749: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11750: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 11751:
11752:
11753: /* Second loop for calculating Fixed[k], Dummy[k]*/
11754:
11755:
1.349 brouard 11756: 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 11757: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11758: Fixed[k]= 0;
11759: Dummy[k]= 0;
1.225 brouard 11760: ncoveff++;
1.232 brouard 11761: ncovf++;
1.234 brouard 11762: nsd++;
11763: modell[k].maintype= FTYPE;
11764: TvarsD[nsd]=Tvar[k];
11765: TvarsDind[nsd]=k;
1.330 brouard 11766: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11767: TvarF[ncovf]=Tvar[k];
11768: TvarFind[ncovf]=k;
11769: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11770: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11771: /* }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 11772: }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 11773: Fixed[k]= 0;
11774: Dummy[k]= 1;
1.230 brouard 11775: nqfveff++;
1.234 brouard 11776: modell[k].maintype= FTYPE;
11777: modell[k].subtype= FQ;
11778: nsq++;
1.334 brouard 11779: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11780: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11781: ncovf++;
1.234 brouard 11782: TvarF[ncovf]=Tvar[k];
11783: TvarFind[ncovf]=k;
1.231 brouard 11784: 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 11785: 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 11786: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11787: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11788: /* model V1+V3+age*V1+age*V3+V1*V3 */
11789: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11790: ncovvt++;
11791: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11792: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11793:
1.227 brouard 11794: Fixed[k]= 1;
11795: Dummy[k]= 0;
1.225 brouard 11796: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11797: modell[k].maintype= VTYPE;
11798: modell[k].subtype= VD;
11799: nsd++;
11800: TvarsD[nsd]=Tvar[k];
11801: TvarsDind[nsd]=k;
1.330 brouard 11802: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11803: ncovv++; /* Only simple time varying variables */
11804: TvarV[ncovv]=Tvar[k];
1.242 brouard 11805: 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 11806: 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 */
11807: 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 11808: 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);
11809: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11810: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11811: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11812: /* model V1+V3+age*V1+age*V3+V1*V3 */
11813: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11814: ncovvt++;
11815: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11816: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11817:
1.234 brouard 11818: Fixed[k]= 1;
11819: Dummy[k]= 1;
11820: nqtveff++;
11821: modell[k].maintype= VTYPE;
11822: modell[k].subtype= VQ;
11823: ncovv++; /* Only simple time varying variables */
11824: nsq++;
1.334 brouard 11825: 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) */
11826: 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 11827: TvarV[ncovv]=Tvar[k];
1.242 brouard 11828: 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 11829: 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 */
11830: 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 11831: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11832: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 11833: /* 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 11834: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11835: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11836: ncova++;
11837: TvarA[ncova]=Tvar[k];
11838: TvarAind[ncova]=k;
1.349 brouard 11839: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11840: /** 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 11841: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11842: Fixed[k]= 2;
11843: Dummy[k]= 2;
11844: modell[k].maintype= ATYPE;
11845: modell[k].subtype= APFD;
1.349 brouard 11846: ncovta++;
11847: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
11848: TvarAVVAind[ncovta]=k;
1.240 brouard 11849: /* ncoveff++; */
1.227 brouard 11850: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11851: Fixed[k]= 2;
11852: Dummy[k]= 3;
11853: modell[k].maintype= ATYPE;
11854: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 11855: ncovta++;
11856: TvarAVVA[ncovta]=Tvar[k]; /* */
11857: TvarAVVAind[ncovta]=k;
1.240 brouard 11858: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11859: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11860: Fixed[k]= 3;
11861: Dummy[k]= 2;
11862: modell[k].maintype= ATYPE;
11863: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 11864: ncovva++;
11865: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11866: TvarVVAind[ncovva]=k;
11867: ncovta++;
11868: TvarAVVA[ncovta]=Tvar[k]; /* */
11869: TvarAVVAind[ncovta]=k;
1.240 brouard 11870: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11871: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11872: Fixed[k]= 3;
11873: Dummy[k]= 3;
11874: modell[k].maintype= ATYPE;
11875: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 11876: ncovva++;
11877: TvarVVA[ncovva]=Tvar[k]; /* */
11878: TvarVVAind[ncovva]=k;
11879: ncovta++;
11880: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11881: TvarAVVAind[ncovta]=k;
1.240 brouard 11882: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11883: }
1.349 brouard 11884: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
11885: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
11886: 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 */
11887: 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]]);
11888: Fixed[k]= 0;
11889: Dummy[k]= 0;
11890: ncoveff++;
11891: ncovf++;
11892: /* ncovv++; */
11893: /* TvarVV[ncovv]=Tvardk[k][1]; */
11894: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11895: /* ncovv++; */
11896: /* TvarVV[ncovv]=Tvardk[k][2]; */
11897: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11898: modell[k].maintype= FTYPE;
11899: TvarF[ncovf]=Tvar[k];
11900: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
11901: TvarFind[ncovf]=k;
11902: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11903: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11904: }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 */
11905: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11906: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11907: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11908: 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 */
11909: ncovvt++;
11910: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11911: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11912: ncovvt++;
11913: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11914: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11915:
11916: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11917: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
11918:
11919: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11920: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
11921: Fixed[k]= 1;
11922: Dummy[k]= 0;
11923: modell[k].maintype= FTYPE;
11924: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11925: ncovf++; /* Fixed variables without age */
11926: TvarF[ncovf]=Tvar[k];
11927: TvarFind[ncovf]=k;
11928: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11929: Fixed[k]= 0; /* Fixed product */
11930: Dummy[k]= 1;
11931: modell[k].maintype= FTYPE;
11932: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11933: ncovf++; /* Varying variables without age */
11934: TvarF[ncovf]=Tvar[k];
11935: TvarFind[ncovf]=k;
11936: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
11937: Fixed[k]= 1;
11938: Dummy[k]= 0;
11939: modell[k].maintype= VTYPE;
11940: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11941: ncovv++; /* Varying variables without age */
11942: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11943: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11944: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
11945: Fixed[k]= 1;
11946: Dummy[k]= 1;
11947: modell[k].maintype= VTYPE;
11948: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11949: ncovv++; /* Varying variables without age */
11950: TvarV[ncovv]=Tvar[k];
11951: TvarVind[ncovv]=k;
11952: }
11953: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11954: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11955: Fixed[k]= 0; /* Fixed product */
11956: Dummy[k]= 1;
11957: modell[k].maintype= FTYPE;
11958: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11959: ncovf++; /* Fixed variables without age */
11960: TvarF[ncovf]=Tvar[k];
11961: TvarFind[ncovf]=k;
11962: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
11963: Fixed[k]= 1;
11964: Dummy[k]= 1;
11965: modell[k].maintype= VTYPE;
11966: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11967: ncovv++; /* Varying variables without age */
11968: TvarV[ncovv]=Tvar[k];
11969: TvarVind[ncovv]=k;
11970: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
11971: Fixed[k]= 1;
11972: Dummy[k]= 1;
11973: modell[k].maintype= VTYPE;
11974: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11975: ncovv++; /* Varying variables without age */
11976: TvarV[ncovv]=Tvar[k];
11977: TvarVind[ncovv]=k;
11978: ncovv++; /* Varying variables without age */
11979: TvarV[ncovv]=Tvar[k];
11980: TvarVind[ncovv]=k;
11981: }
11982: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
11983: if(Tvard[k1][2] <=ncovcol){
11984: Fixed[k]= 1;
11985: Dummy[k]= 1;
11986: modell[k].maintype= VTYPE;
11987: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11988: ncovv++; /* Varying variables without age */
11989: TvarV[ncovv]=Tvar[k];
11990: TvarVind[ncovv]=k;
11991: }else if(Tvard[k1][2] <=ncovcol+nqv){
11992: Fixed[k]= 1;
11993: Dummy[k]= 1;
11994: modell[k].maintype= VTYPE;
11995: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11996: ncovv++; /* Varying variables without age */
11997: TvarV[ncovv]=Tvar[k];
11998: TvarVind[ncovv]=k;
11999: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12000: Fixed[k]= 1;
12001: Dummy[k]= 0;
12002: modell[k].maintype= VTYPE;
12003: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
12004: ncovv++; /* Varying variables without age */
12005: TvarV[ncovv]=Tvar[k];
12006: TvarVind[ncovv]=k;
12007: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12008: Fixed[k]= 1;
12009: Dummy[k]= 1;
12010: modell[k].maintype= VTYPE;
12011: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
12012: ncovv++; /* Varying variables without age */
12013: TvarV[ncovv]=Tvar[k];
12014: TvarVind[ncovv]=k;
12015: }
12016: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
12017: if(Tvard[k1][2] <=ncovcol){
12018: Fixed[k]= 1;
12019: Dummy[k]= 1;
12020: modell[k].maintype= VTYPE;
12021: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
12022: ncovv++; /* Varying variables without age */
12023: TvarV[ncovv]=Tvar[k];
12024: TvarVind[ncovv]=k;
12025: }else if(Tvard[k1][2] <=ncovcol+nqv){
12026: Fixed[k]= 1;
12027: Dummy[k]= 1;
12028: modell[k].maintype= VTYPE;
12029: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
12030: ncovv++; /* Varying variables without age */
12031: TvarV[ncovv]=Tvar[k];
12032: TvarVind[ncovv]=k;
12033: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12034: Fixed[k]= 1;
12035: Dummy[k]= 1;
12036: modell[k].maintype= VTYPE;
12037: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
12038: ncovv++; /* Varying variables without age */
12039: TvarV[ncovv]=Tvar[k];
12040: TvarVind[ncovv]=k;
12041: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12042: Fixed[k]= 1;
12043: Dummy[k]= 1;
12044: modell[k].maintype= VTYPE;
12045: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
12046: ncovv++; /* Varying variables without age */
12047: TvarV[ncovv]=Tvar[k];
12048: TvarVind[ncovv]=k;
12049: }
12050: }else{
12051: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12052: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12053: } /*end k1*/
12054: }
12055: }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 12056: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 12057: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
12058: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
12059: 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 */
12060: ncova++;
12061: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
12062: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
12063: ncova++;
12064: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
12065: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 12066:
1.349 brouard 12067: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
12068: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
12069: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
12070: ncovta++;
12071: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12072: TvarAVVAind[ncovta]=k;
12073: ncovta++;
12074: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12075: TvarAVVAind[ncovta]=k;
12076: }else{
12077: ncovva++; /* HERY reached */
12078: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12079: TvarVVAind[ncovva]=k;
12080: ncovva++;
12081: TvarVVA[ncovva]=Tvard[k1][2]; /* */
12082: TvarVVAind[ncovva]=k;
12083: ncovta++;
12084: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12085: TvarAVVAind[ncovta]=k;
12086: ncovta++;
12087: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12088: TvarAVVAind[ncovta]=k;
12089: }
1.339 brouard 12090: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12091: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 12092: Fixed[k]= 2;
12093: Dummy[k]= 2;
1.240 brouard 12094: modell[k].maintype= FTYPE;
12095: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 12096: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
12097: /* TvarFind[ncova]=k; */
1.339 brouard 12098: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 12099: Fixed[k]= 2; /* Fixed product */
12100: Dummy[k]= 3;
1.240 brouard 12101: modell[k].maintype= FTYPE;
12102: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 12103: /* TvarF[ncova]=Tvar[k]; */
12104: /* TvarFind[ncova]=k; */
1.339 brouard 12105: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 12106: Fixed[k]= 3;
12107: Dummy[k]= 2;
1.240 brouard 12108: modell[k].maintype= VTYPE;
12109: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 12110: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
12111: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12112: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 12113: Fixed[k]= 3;
12114: Dummy[k]= 3;
1.240 brouard 12115: modell[k].maintype= VTYPE;
12116: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 12117: /* ncovv++; /\* Varying variables without age *\/ */
12118: /* TvarV[ncovv]=Tvar[k]; */
12119: /* TvarVind[ncovv]=k; */
1.240 brouard 12120: }
1.339 brouard 12121: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12122: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 12123: Fixed[k]= 2; /* Fixed product */
12124: Dummy[k]= 2;
1.240 brouard 12125: modell[k].maintype= FTYPE;
12126: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 12127: /* ncova++; /\* Fixed variables with age *\/ */
12128: /* TvarF[ncovf]=Tvar[k]; */
12129: /* TvarFind[ncovf]=k; */
1.339 brouard 12130: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 12131: Fixed[k]= 2;
12132: Dummy[k]= 3;
1.240 brouard 12133: modell[k].maintype= VTYPE;
12134: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 12135: /* ncova++; /\* Varying variables with age *\/ */
12136: /* TvarV[ncova]=Tvar[k]; */
12137: /* TvarVind[ncova]=k; */
1.339 brouard 12138: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 12139: Fixed[k]= 3;
12140: Dummy[k]= 2;
1.240 brouard 12141: modell[k].maintype= VTYPE;
12142: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 12143: ncova++; /* Varying variables without age */
12144: TvarV[ncova]=Tvar[k];
12145: TvarVind[ncova]=k;
12146: /* ncova++; /\* Varying variables without age *\/ */
12147: /* TvarV[ncova]=Tvar[k]; */
12148: /* TvarVind[ncova]=k; */
1.240 brouard 12149: }
1.339 brouard 12150: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12151: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12152: Fixed[k]= 2;
12153: Dummy[k]= 2;
1.240 brouard 12154: modell[k].maintype= VTYPE;
12155: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 12156: /* ncova++; /\* Varying variables with age *\/ */
12157: /* TvarV[ncova]=Tvar[k]; */
12158: /* TvarVind[ncova]=k; */
1.240 brouard 12159: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12160: Fixed[k]= 2;
12161: Dummy[k]= 3;
1.240 brouard 12162: modell[k].maintype= VTYPE;
12163: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 12164: /* ncova++; /\* Varying variables with age *\/ */
12165: /* TvarV[ncova]=Tvar[k]; */
12166: /* TvarVind[ncova]=k; */
1.240 brouard 12167: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12168: Fixed[k]= 3;
12169: Dummy[k]= 2;
1.240 brouard 12170: modell[k].maintype= VTYPE;
12171: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 12172: /* ncova++; /\* Varying variables with age *\/ */
12173: /* TvarV[ncova]=Tvar[k]; */
12174: /* TvarVind[ncova]=k; */
1.240 brouard 12175: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12176: Fixed[k]= 3;
12177: Dummy[k]= 3;
1.240 brouard 12178: modell[k].maintype= VTYPE;
12179: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 12180: /* ncova++; /\* Varying variables with age *\/ */
12181: /* TvarV[ncova]=Tvar[k]; */
12182: /* TvarVind[ncova]=k; */
1.240 brouard 12183: }
1.339 brouard 12184: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12185: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12186: Fixed[k]= 2;
12187: Dummy[k]= 2;
1.240 brouard 12188: modell[k].maintype= VTYPE;
12189: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 12190: /* ncova++; /\* Varying variables with age *\/ */
12191: /* TvarV[ncova]=Tvar[k]; */
12192: /* TvarVind[ncova]=k; */
1.240 brouard 12193: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12194: Fixed[k]= 2;
12195: Dummy[k]= 3;
1.240 brouard 12196: modell[k].maintype= VTYPE;
12197: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 12198: /* ncova++; /\* Varying variables with age *\/ */
12199: /* TvarV[ncova]=Tvar[k]; */
12200: /* TvarVind[ncova]=k; */
1.240 brouard 12201: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12202: Fixed[k]= 3;
12203: Dummy[k]= 2;
1.240 brouard 12204: modell[k].maintype= VTYPE;
12205: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 12206: /* ncova++; /\* Varying variables with age *\/ */
12207: /* TvarV[ncova]=Tvar[k]; */
12208: /* TvarVind[ncova]=k; */
1.240 brouard 12209: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12210: Fixed[k]= 3;
12211: Dummy[k]= 3;
1.240 brouard 12212: modell[k].maintype= VTYPE;
12213: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 12214: /* ncova++; /\* Varying variables with age *\/ */
12215: /* TvarV[ncova]=Tvar[k]; */
12216: /* TvarVind[ncova]=k; */
1.240 brouard 12217: }
1.227 brouard 12218: }else{
1.240 brouard 12219: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12220: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12221: } /*end k1*/
1.349 brouard 12222: } else{
1.226 brouard 12223: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12224: 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 12225: }
1.342 brouard 12226: /* 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]); */
12227: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12228: 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]);
12229: }
1.349 brouard 12230: ncovvta=ncovva;
1.227 brouard 12231: /* Searching for doublons in the model */
12232: for(k1=1; k1<= cptcovt;k1++){
12233: for(k2=1; k2 <k1;k2++){
1.285 brouard 12234: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12235: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12236: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12237: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12238: 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]);
12239: 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 12240: return(1);
12241: }
12242: }else if (Typevar[k1] ==2){
12243: k3=Tposprod[k1];
12244: k4=Tposprod[k2];
12245: 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 12246: 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]]);
12247: 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 12248: return(1);
12249: }
12250: }
1.227 brouard 12251: }
12252: }
1.225 brouard 12253: }
12254: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12255: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12256: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12257: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 12258:
12259: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12260: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12261: /*endread:*/
1.225 brouard 12262: printf("Exiting decodemodel: ");
12263: return (1);
1.136 brouard 12264: }
12265:
1.169 brouard 12266: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12267: {/* Check ages at death */
1.136 brouard 12268: int i, m;
1.218 brouard 12269: int firstone=0;
12270:
1.136 brouard 12271: for (i=1; i<=imx; i++) {
12272: for(m=2; (m<= maxwav); m++) {
12273: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12274: anint[m][i]=9999;
1.216 brouard 12275: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12276: s[m][i]=-1;
1.136 brouard 12277: }
12278: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12279: *nberr = *nberr + 1;
1.218 brouard 12280: if(firstone == 0){
12281: firstone=1;
1.260 brouard 12282: 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 12283: }
1.262 brouard 12284: 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 12285: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12286: }
12287: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12288: (*nberr)++;
1.259 brouard 12289: 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 12290: 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 12291: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12292: }
12293: }
12294: }
12295:
12296: for (i=1; i<=imx; i++) {
12297: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12298: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12299: 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 12300: if (s[m][i] >= nlstate+1) {
1.169 brouard 12301: if(agedc[i]>0){
12302: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12303: agev[m][i]=agedc[i];
1.214 brouard 12304: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12305: }else {
1.136 brouard 12306: if ((int)andc[i]!=9999){
12307: nbwarn++;
12308: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12309: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12310: agev[m][i]=-1;
12311: }
12312: }
1.169 brouard 12313: } /* agedc > 0 */
1.214 brouard 12314: } /* end if */
1.136 brouard 12315: else if(s[m][i] !=9){ /* Standard case, age in fractional
12316: years but with the precision of a month */
12317: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12318: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12319: agev[m][i]=1;
12320: else if(agev[m][i] < *agemin){
12321: *agemin=agev[m][i];
12322: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12323: }
12324: else if(agev[m][i] >*agemax){
12325: *agemax=agev[m][i];
1.156 brouard 12326: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12327: }
12328: /*agev[m][i]=anint[m][i]-annais[i];*/
12329: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12330: } /* en if 9*/
1.136 brouard 12331: else { /* =9 */
1.214 brouard 12332: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12333: agev[m][i]=1;
12334: s[m][i]=-1;
12335: }
12336: }
1.214 brouard 12337: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12338: agev[m][i]=1;
1.214 brouard 12339: else{
12340: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12341: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12342: agev[m][i]=0;
12343: }
12344: } /* End for lastpass */
12345: }
1.136 brouard 12346:
12347: for (i=1; i<=imx; i++) {
12348: for(m=firstpass; (m<=lastpass); m++){
12349: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12350: (*nberr)++;
1.136 brouard 12351: 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);
12352: 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);
12353: return 1;
12354: }
12355: }
12356: }
12357:
12358: /*for (i=1; i<=imx; i++){
12359: for (m=firstpass; (m<lastpass); m++){
12360: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12361: }
12362:
12363: }*/
12364:
12365:
1.139 brouard 12366: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12367: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12368:
12369: return (0);
1.164 brouard 12370: /* endread:*/
1.136 brouard 12371: printf("Exiting calandcheckages: ");
12372: return (1);
12373: }
12374:
1.172 brouard 12375: #if defined(_MSC_VER)
12376: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12377: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12378: //#include "stdafx.h"
12379: //#include <stdio.h>
12380: //#include <tchar.h>
12381: //#include <windows.h>
12382: //#include <iostream>
12383: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12384:
12385: LPFN_ISWOW64PROCESS fnIsWow64Process;
12386:
12387: BOOL IsWow64()
12388: {
12389: BOOL bIsWow64 = FALSE;
12390:
12391: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12392: // (HANDLE, PBOOL);
12393:
12394: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12395:
12396: HMODULE module = GetModuleHandle(_T("kernel32"));
12397: const char funcName[] = "IsWow64Process";
12398: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12399: GetProcAddress(module, funcName);
12400:
12401: if (NULL != fnIsWow64Process)
12402: {
12403: if (!fnIsWow64Process(GetCurrentProcess(),
12404: &bIsWow64))
12405: //throw std::exception("Unknown error");
12406: printf("Unknown error\n");
12407: }
12408: return bIsWow64 != FALSE;
12409: }
12410: #endif
1.177 brouard 12411:
1.191 brouard 12412: void syscompilerinfo(int logged)
1.292 brouard 12413: {
12414: #include <stdint.h>
12415:
12416: /* #include "syscompilerinfo.h"*/
1.185 brouard 12417: /* command line Intel compiler 32bit windows, XP compatible:*/
12418: /* /GS /W3 /Gy
12419: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12420: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12421: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12422: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12423: */
12424: /* 64 bits */
1.185 brouard 12425: /*
12426: /GS /W3 /Gy
12427: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12428: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12429: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12430: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12431: /* Optimization are useless and O3 is slower than O2 */
12432: /*
12433: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12434: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12435: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12436: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12437: */
1.186 brouard 12438: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12439: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12440: /PDB:"visual studio
12441: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12442: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12443: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12444: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12445: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12446: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12447: uiAccess='false'"
12448: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12449: /NOLOGO /TLBID:1
12450: */
1.292 brouard 12451:
12452:
1.177 brouard 12453: #if defined __INTEL_COMPILER
1.178 brouard 12454: #if defined(__GNUC__)
12455: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12456: #endif
1.177 brouard 12457: #elif defined(__GNUC__)
1.179 brouard 12458: #ifndef __APPLE__
1.174 brouard 12459: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12460: #endif
1.177 brouard 12461: struct utsname sysInfo;
1.178 brouard 12462: int cross = CROSS;
12463: if (cross){
12464: printf("Cross-");
1.191 brouard 12465: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12466: }
1.174 brouard 12467: #endif
12468:
1.191 brouard 12469: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12470: #if defined(__clang__)
1.191 brouard 12471: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12472: #endif
12473: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12474: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12475: #endif
12476: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12477: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12478: #endif
12479: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12480: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12481: #endif
12482: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12483: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12484: #endif
12485: #if defined(_MSC_VER)
1.191 brouard 12486: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12487: #endif
12488: #if defined(__PGI)
1.191 brouard 12489: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12490: #endif
12491: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12492: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12493: #endif
1.191 brouard 12494: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12495:
1.167 brouard 12496: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12497: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12498: // Windows (x64 and x86)
1.191 brouard 12499: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12500: #elif __unix__ // all unices, not all compilers
12501: // Unix
1.191 brouard 12502: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12503: #elif __linux__
12504: // linux
1.191 brouard 12505: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12506: #elif __APPLE__
1.174 brouard 12507: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12508: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12509: #endif
12510:
12511: /* __MINGW32__ */
12512: /* __CYGWIN__ */
12513: /* __MINGW64__ */
12514: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12515: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12516: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12517: /* _WIN64 // Defined for applications for Win64. */
12518: /* _M_X64 // Defined for compilations that target x64 processors. */
12519: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12520:
1.167 brouard 12521: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12522: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12523: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12524: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12525: #else
1.191 brouard 12526: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12527: #endif
12528:
1.169 brouard 12529: #if defined(__GNUC__)
12530: # if defined(__GNUC_PATCHLEVEL__)
12531: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12532: + __GNUC_MINOR__ * 100 \
12533: + __GNUC_PATCHLEVEL__)
12534: # else
12535: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12536: + __GNUC_MINOR__ * 100)
12537: # endif
1.174 brouard 12538: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12539: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12540:
12541: if (uname(&sysInfo) != -1) {
12542: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12543: 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 12544: }
12545: else
12546: perror("uname() error");
1.179 brouard 12547: //#ifndef __INTEL_COMPILER
12548: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12549: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12550: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12551: #endif
1.169 brouard 12552: #endif
1.172 brouard 12553:
1.286 brouard 12554: // void main ()
1.172 brouard 12555: // {
1.169 brouard 12556: #if defined(_MSC_VER)
1.174 brouard 12557: if (IsWow64()){
1.191 brouard 12558: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12559: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12560: }
12561: else{
1.191 brouard 12562: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12563: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12564: }
1.172 brouard 12565: // printf("\nPress Enter to continue...");
12566: // getchar();
12567: // }
12568:
1.169 brouard 12569: #endif
12570:
1.167 brouard 12571:
1.219 brouard 12572: }
1.136 brouard 12573:
1.219 brouard 12574: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12575: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12576: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12577: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12578: /* double ftolpl = 1.e-10; */
1.180 brouard 12579: double age, agebase, agelim;
1.203 brouard 12580: double tot;
1.180 brouard 12581:
1.202 brouard 12582: strcpy(filerespl,"PL_");
12583: strcat(filerespl,fileresu);
12584: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12585: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12586: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12587: }
1.288 brouard 12588: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12589: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12590: pstamp(ficrespl);
1.288 brouard 12591: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12592: fprintf(ficrespl,"#Age ");
12593: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12594: fprintf(ficrespl,"\n");
1.180 brouard 12595:
1.219 brouard 12596: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12597:
1.219 brouard 12598: agebase=ageminpar;
12599: agelim=agemaxpar;
1.180 brouard 12600:
1.227 brouard 12601: /* i1=pow(2,ncoveff); */
1.234 brouard 12602: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12603: if (cptcovn < 1){i1=1;}
1.180 brouard 12604:
1.337 brouard 12605: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12606: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12607: k=TKresult[nres];
1.338 brouard 12608: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12609: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12610: /* continue; */
1.235 brouard 12611:
1.238 brouard 12612: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12613: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12614: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12615: /* k=k+1; */
12616: /* to clean */
1.332 brouard 12617: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12618: fprintf(ficrespl,"#******");
12619: printf("#******");
12620: fprintf(ficlog,"#******");
1.337 brouard 12621: 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 12622: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12623: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12624: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12625: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12626: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12627: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12628: }
12629: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12630: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12631: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12632: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12633: /* } */
1.238 brouard 12634: fprintf(ficrespl,"******\n");
12635: printf("******\n");
12636: fprintf(ficlog,"******\n");
12637: if(invalidvarcomb[k]){
12638: printf("\nCombination (%d) ignored because no case \n",k);
12639: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12640: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12641: continue;
12642: }
1.219 brouard 12643:
1.238 brouard 12644: fprintf(ficrespl,"#Age ");
1.337 brouard 12645: /* for(j=1;j<=cptcoveff;j++) { */
12646: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12647: /* } */
12648: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12649: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12650: }
12651: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12652: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12653:
1.238 brouard 12654: for (age=agebase; age<=agelim; age++){
12655: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12656: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12657: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12658: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12659: /* for(j=1;j<=cptcoveff;j++) */
12660: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12661: for(j=1;j<=cptcovs;j++)
12662: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12663: tot=0.;
12664: for(i=1; i<=nlstate;i++){
12665: tot += prlim[i][i];
12666: fprintf(ficrespl," %.5f", prlim[i][i]);
12667: }
12668: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12669: } /* Age */
12670: /* was end of cptcod */
1.337 brouard 12671: } /* nres */
12672: /* } /\* for each combination *\/ */
1.219 brouard 12673: return 0;
1.180 brouard 12674: }
12675:
1.218 brouard 12676: 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 12677: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12678:
12679: /* Computes the back prevalence limit for any combination of covariate values
12680: * at any age between ageminpar and agemaxpar
12681: */
1.235 brouard 12682: int i, j, k, i1, nres=0 ;
1.217 brouard 12683: /* double ftolpl = 1.e-10; */
12684: double age, agebase, agelim;
12685: double tot;
1.218 brouard 12686: /* double ***mobaverage; */
12687: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12688:
12689: strcpy(fileresplb,"PLB_");
12690: strcat(fileresplb,fileresu);
12691: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12692: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12693: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12694: }
1.288 brouard 12695: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12696: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12697: pstamp(ficresplb);
1.288 brouard 12698: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12699: fprintf(ficresplb,"#Age ");
12700: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12701: fprintf(ficresplb,"\n");
12702:
1.218 brouard 12703:
12704: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12705:
12706: agebase=ageminpar;
12707: agelim=agemaxpar;
12708:
12709:
1.227 brouard 12710: i1=pow(2,cptcoveff);
1.218 brouard 12711: if (cptcovn < 1){i1=1;}
1.227 brouard 12712:
1.238 brouard 12713: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12714: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12715: k=TKresult[nres];
12716: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12717: /* if(i1 != 1 && TKresult[nres]!= k) */
12718: /* continue; */
12719: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12720: fprintf(ficresplb,"#******");
12721: printf("#******");
12722: fprintf(ficlog,"#******");
1.338 brouard 12723: 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) */
12724: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12725: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12726: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12727: }
1.338 brouard 12728: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12729: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12730: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12731: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12732: /* } */
12733: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12734: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12735: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12736: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12737: /* } */
1.238 brouard 12738: fprintf(ficresplb,"******\n");
12739: printf("******\n");
12740: fprintf(ficlog,"******\n");
12741: if(invalidvarcomb[k]){
12742: printf("\nCombination (%d) ignored because no cases \n",k);
12743: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12744: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12745: continue;
12746: }
1.218 brouard 12747:
1.238 brouard 12748: fprintf(ficresplb,"#Age ");
1.338 brouard 12749: for(j=1;j<=cptcovs;j++) {
12750: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12751: }
12752: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12753: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12754:
12755:
1.238 brouard 12756: for (age=agebase; age<=agelim; age++){
12757: /* for (age=agebase; age<=agebase; age++){ */
12758: if(mobilavproj > 0){
12759: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12760: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12761: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12762: }else if (mobilavproj == 0){
12763: 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);
12764: 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);
12765: exit(1);
12766: }else{
12767: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12768: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12769: /* printf("TOTOT\n"); */
12770: /* exit(1); */
1.238 brouard 12771: }
12772: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12773: for(j=1;j<=cptcovs;j++)
12774: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12775: tot=0.;
12776: for(i=1; i<=nlstate;i++){
12777: tot += bprlim[i][i];
12778: fprintf(ficresplb," %.5f", bprlim[i][i]);
12779: }
12780: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12781: } /* Age */
12782: /* was end of cptcod */
1.255 brouard 12783: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12784: /* } /\* end of any combination *\/ */
1.238 brouard 12785: } /* end of nres */
1.218 brouard 12786: /* hBijx(p, bage, fage); */
12787: /* fclose(ficrespijb); */
12788:
12789: return 0;
1.217 brouard 12790: }
1.218 brouard 12791:
1.180 brouard 12792: int hPijx(double *p, int bage, int fage){
12793: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12794: /* to be optimized with precov */
1.180 brouard 12795: int stepsize;
12796: int agelim;
12797: int hstepm;
12798: int nhstepm;
1.235 brouard 12799: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12800:
12801: double agedeb;
12802: double ***p3mat;
12803:
1.337 brouard 12804: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12805: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12806: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12807: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12808: }
12809: printf("Computing pij: result on file '%s' \n", filerespij);
12810: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12811:
12812: stepsize=(int) (stepm+YEARM-1)/YEARM;
12813: /*if (stepm<=24) stepsize=2;*/
12814:
12815: agelim=AGESUP;
12816: hstepm=stepsize*YEARM; /* Every year of age */
12817: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12818:
12819: /* hstepm=1; aff par mois*/
12820: pstamp(ficrespij);
12821: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12822: i1= pow(2,cptcoveff);
12823: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12824: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12825: /* k=k+1; */
12826: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12827: k=TKresult[nres];
1.338 brouard 12828: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12829: /* for(k=1; k<=i1;k++){ */
12830: /* if(i1 != 1 && TKresult[nres]!= k) */
12831: /* continue; */
12832: fprintf(ficrespij,"\n#****** ");
12833: for(j=1;j<=cptcovs;j++){
12834: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12835: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12836: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12837: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12838: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12839: }
12840: fprintf(ficrespij,"******\n");
12841:
12842: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12843: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12844: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12845:
12846: /* nhstepm=nhstepm*YEARM; aff par mois*/
12847:
12848: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12849: oldm=oldms;savm=savms;
12850: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12851: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12852: for(i=1; i<=nlstate;i++)
12853: for(j=1; j<=nlstate+ndeath;j++)
12854: fprintf(ficrespij," %1d-%1d",i,j);
12855: fprintf(ficrespij,"\n");
12856: for (h=0; h<=nhstepm; h++){
12857: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12858: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12859: for(i=1; i<=nlstate;i++)
12860: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12861: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12862: fprintf(ficrespij,"\n");
12863: }
1.337 brouard 12864: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12865: fprintf(ficrespij,"\n");
1.180 brouard 12866: }
1.337 brouard 12867: }
12868: /*}*/
12869: return 0;
1.180 brouard 12870: }
1.218 brouard 12871:
12872: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12873: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12874: /* To be optimized with precov */
1.217 brouard 12875: int stepsize;
1.218 brouard 12876: /* int agelim; */
12877: int ageminl;
1.217 brouard 12878: int hstepm;
12879: int nhstepm;
1.238 brouard 12880: int h, i, i1, j, k, nres;
1.218 brouard 12881:
1.217 brouard 12882: double agedeb;
12883: double ***p3mat;
1.218 brouard 12884:
12885: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12886: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12887: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12888: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12889: }
12890: printf("Computing pij back: result on file '%s' \n", filerespijb);
12891: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12892:
12893: stepsize=(int) (stepm+YEARM-1)/YEARM;
12894: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12895:
1.218 brouard 12896: /* agelim=AGESUP; */
1.289 brouard 12897: ageminl=AGEINF; /* was 30 */
1.218 brouard 12898: hstepm=stepsize*YEARM; /* Every year of age */
12899: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12900:
12901: /* hstepm=1; aff par mois*/
12902: pstamp(ficrespijb);
1.255 brouard 12903: 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 12904: i1= pow(2,cptcoveff);
1.218 brouard 12905: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12906: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12907: /* k=k+1; */
1.238 brouard 12908: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12909: k=TKresult[nres];
1.338 brouard 12910: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12911: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12912: /* if(i1 != 1 && TKresult[nres]!= k) */
12913: /* continue; */
12914: fprintf(ficrespijb,"\n#****** ");
12915: for(j=1;j<=cptcovs;j++){
1.338 brouard 12916: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12917: /* for(j=1;j<=cptcoveff;j++) */
12918: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12919: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12920: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12921: }
12922: fprintf(ficrespijb,"******\n");
12923: if(invalidvarcomb[k]){ /* Is it necessary here? */
12924: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12925: continue;
12926: }
12927:
12928: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12929: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12930: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12931: 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 */
12932: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12933:
12934: /* nhstepm=nhstepm*YEARM; aff par mois*/
12935:
12936: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12937: /* and memory limitations if stepm is small */
12938:
12939: /* oldm=oldms;savm=savms; */
12940: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12941: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12942: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12943: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12944: for(i=1; i<=nlstate;i++)
12945: for(j=1; j<=nlstate+ndeath;j++)
12946: fprintf(ficrespijb," %1d-%1d",i,j);
12947: fprintf(ficrespijb,"\n");
12948: for (h=0; h<=nhstepm; h++){
12949: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12950: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12951: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12952: for(i=1; i<=nlstate;i++)
12953: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12954: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12955: fprintf(ficrespijb,"\n");
1.337 brouard 12956: }
12957: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12958: fprintf(ficrespijb,"\n");
12959: } /* end age deb */
12960: /* } /\* end combination *\/ */
1.238 brouard 12961: } /* end nres */
1.218 brouard 12962: return 0;
12963: } /* hBijx */
1.217 brouard 12964:
1.180 brouard 12965:
1.136 brouard 12966: /***********************************************/
12967: /**************** Main Program *****************/
12968: /***********************************************/
12969:
12970: int main(int argc, char *argv[])
12971: {
12972: #ifdef GSL
12973: const gsl_multimin_fminimizer_type *T;
12974: size_t iteri = 0, it;
12975: int rval = GSL_CONTINUE;
12976: int status = GSL_SUCCESS;
12977: double ssval;
12978: #endif
12979: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12980: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12981: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12982: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12983: int jj, ll, li, lj, lk;
1.136 brouard 12984: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12985: int num_filled;
1.136 brouard 12986: int itimes;
12987: int NDIM=2;
12988: int vpopbased=0;
1.235 brouard 12989: int nres=0;
1.258 brouard 12990: int endishere=0;
1.277 brouard 12991: int noffset=0;
1.274 brouard 12992: int ncurrv=0; /* Temporary variable */
12993:
1.164 brouard 12994: char ca[32], cb[32];
1.136 brouard 12995: /* FILE *fichtm; *//* Html File */
12996: /* FILE *ficgp;*/ /*Gnuplot File */
12997: struct stat info;
1.191 brouard 12998: double agedeb=0.;
1.194 brouard 12999:
13000: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 13001: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 13002:
1.165 brouard 13003: double fret;
1.191 brouard 13004: double dum=0.; /* Dummy variable */
1.136 brouard 13005: double ***p3mat;
1.218 brouard 13006: /* double ***mobaverage; */
1.319 brouard 13007: double wald;
1.164 brouard 13008:
1.351 brouard 13009: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 13010: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
13011:
1.234 brouard 13012: char modeltemp[MAXLINE];
1.332 brouard 13013: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 13014:
1.136 brouard 13015: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 13016: char *tok, *val; /* pathtot */
1.334 brouard 13017: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 13018: int c, h , cpt, c2;
1.191 brouard 13019: int jl=0;
13020: int i1, j1, jk, stepsize=0;
1.194 brouard 13021: int count=0;
13022:
1.164 brouard 13023: int *tab;
1.136 brouard 13024: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 13025: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
13026: /* double anprojf, mprojf, jprojf; */
13027: /* double jintmean,mintmean,aintmean; */
13028: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13029: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13030: double yrfproj= 10.0; /* Number of years of forward projections */
13031: double yrbproj= 10.0; /* Number of years of backward projections */
13032: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 13033: int mobilav=0,popforecast=0;
1.191 brouard 13034: int hstepm=0, nhstepm=0;
1.136 brouard 13035: int agemortsup;
13036: float sumlpop=0.;
13037: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
13038: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
13039:
1.191 brouard 13040: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 13041: double ftolpl=FTOL;
13042: double **prlim;
1.217 brouard 13043: double **bprlim;
1.317 brouard 13044: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
13045: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 13046: double ***paramstart; /* Matrix of starting parameter values */
13047: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 13048: double **matcov; /* Matrix of covariance */
1.203 brouard 13049: double **hess; /* Hessian matrix */
1.136 brouard 13050: double ***delti3; /* Scale */
13051: double *delti; /* Scale */
13052: double ***eij, ***vareij;
13053: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 13054:
1.136 brouard 13055: double *epj, vepp;
1.164 brouard 13056:
1.273 brouard 13057: double dateprev1, dateprev2;
1.296 brouard 13058: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
13059: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
13060:
1.217 brouard 13061:
1.136 brouard 13062: double **ximort;
1.145 brouard 13063: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 13064: int *dcwave;
13065:
1.164 brouard 13066: char z[1]="c";
1.136 brouard 13067:
13068: /*char *strt;*/
13069: char strtend[80];
1.126 brouard 13070:
1.164 brouard 13071:
1.126 brouard 13072: /* setlocale (LC_ALL, ""); */
13073: /* bindtextdomain (PACKAGE, LOCALEDIR); */
13074: /* textdomain (PACKAGE); */
13075: /* setlocale (LC_CTYPE, ""); */
13076: /* setlocale (LC_MESSAGES, ""); */
13077:
13078: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 13079: rstart_time = time(NULL);
13080: /* (void) gettimeofday(&start_time,&tzp);*/
13081: start_time = *localtime(&rstart_time);
1.126 brouard 13082: curr_time=start_time;
1.157 brouard 13083: /*tml = *localtime(&start_time.tm_sec);*/
13084: /* strcpy(strstart,asctime(&tml)); */
13085: strcpy(strstart,asctime(&start_time));
1.126 brouard 13086:
13087: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13088: /* tp.tm_sec = tp.tm_sec +86400; */
13089: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13090: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13091: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13092: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13093: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13094: /* strt=asctime(&tmg); */
13095: /* printf("Time(after) =%s",strstart); */
13096: /* (void) time (&time_value);
13097: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13098: * tm = *localtime(&time_value);
13099: * strstart=asctime(&tm);
13100: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13101: */
13102:
13103: nberr=0; /* Number of errors and warnings */
13104: nbwarn=0;
1.184 brouard 13105: #ifdef WIN32
13106: _getcwd(pathcd, size);
13107: #else
1.126 brouard 13108: getcwd(pathcd, size);
1.184 brouard 13109: #endif
1.191 brouard 13110: syscompilerinfo(0);
1.196 brouard 13111: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13112: if(argc <=1){
13113: printf("\nEnter the parameter file name: ");
1.205 brouard 13114: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13115: printf("ERROR Empty parameter file name\n");
13116: goto end;
13117: }
1.126 brouard 13118: i=strlen(pathr);
13119: if(pathr[i-1]=='\n')
13120: pathr[i-1]='\0';
1.156 brouard 13121: i=strlen(pathr);
1.205 brouard 13122: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13123: pathr[i-1]='\0';
1.205 brouard 13124: }
13125: i=strlen(pathr);
13126: if( i==0 ){
13127: printf("ERROR Empty parameter file name\n");
13128: goto end;
13129: }
13130: for (tok = pathr; tok != NULL; ){
1.126 brouard 13131: printf("Pathr |%s|\n",pathr);
13132: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13133: printf("val= |%s| pathr=%s\n",val,pathr);
13134: strcpy (pathtot, val);
13135: if(pathr[0] == '\0') break; /* Dirty */
13136: }
13137: }
1.281 brouard 13138: else if (argc<=2){
13139: strcpy(pathtot,argv[1]);
13140: }
1.126 brouard 13141: else{
13142: strcpy(pathtot,argv[1]);
1.281 brouard 13143: strcpy(z,argv[2]);
13144: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13145: }
13146: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13147: /*cygwin_split_path(pathtot,path,optionfile);
13148: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13149: /* cutv(path,optionfile,pathtot,'\\');*/
13150:
13151: /* Split argv[0], imach program to get pathimach */
13152: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13153: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13154: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13155: /* strcpy(pathimach,argv[0]); */
13156: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13157: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13158: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13159: #ifdef WIN32
13160: _chdir(path); /* Can be a relative path */
13161: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13162: #else
1.126 brouard 13163: chdir(path); /* Can be a relative path */
1.184 brouard 13164: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13165: #endif
13166: printf("Current directory %s!\n",pathcd);
1.126 brouard 13167: strcpy(command,"mkdir ");
13168: strcat(command,optionfilefiname);
13169: if((outcmd=system(command)) != 0){
1.169 brouard 13170: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13171: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13172: /* fclose(ficlog); */
13173: /* exit(1); */
13174: }
13175: /* if((imk=mkdir(optionfilefiname))<0){ */
13176: /* perror("mkdir"); */
13177: /* } */
13178:
13179: /*-------- arguments in the command line --------*/
13180:
1.186 brouard 13181: /* Main Log file */
1.126 brouard 13182: strcat(filelog, optionfilefiname);
13183: strcat(filelog,".log"); /* */
13184: if((ficlog=fopen(filelog,"w"))==NULL) {
13185: printf("Problem with logfile %s\n",filelog);
13186: goto end;
13187: }
13188: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13189: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13190: fprintf(ficlog,"\nEnter the parameter file name: \n");
13191: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13192: path=%s \n\
13193: optionfile=%s\n\
13194: optionfilext=%s\n\
1.156 brouard 13195: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13196:
1.197 brouard 13197: syscompilerinfo(1);
1.167 brouard 13198:
1.126 brouard 13199: printf("Local time (at start):%s",strstart);
13200: fprintf(ficlog,"Local time (at start): %s",strstart);
13201: fflush(ficlog);
13202: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13203: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13204:
13205: /* */
13206: strcpy(fileres,"r");
13207: strcat(fileres, optionfilefiname);
1.201 brouard 13208: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13209: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13210: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13211:
1.186 brouard 13212: /* Main ---------arguments file --------*/
1.126 brouard 13213:
13214: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13215: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13216: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13217: fflush(ficlog);
1.149 brouard 13218: /* goto end; */
13219: exit(70);
1.126 brouard 13220: }
13221:
13222: strcpy(filereso,"o");
1.201 brouard 13223: strcat(filereso,fileresu);
1.126 brouard 13224: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13225: printf("Problem with Output resultfile: %s\n", filereso);
13226: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13227: fflush(ficlog);
13228: goto end;
13229: }
1.278 brouard 13230: /*-------- Rewriting parameter file ----------*/
13231: strcpy(rfileres,"r"); /* "Rparameterfile */
13232: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13233: strcat(rfileres,"."); /* */
13234: strcat(rfileres,optionfilext); /* Other files have txt extension */
13235: if((ficres =fopen(rfileres,"w"))==NULL) {
13236: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13237: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13238: fflush(ficlog);
13239: goto end;
13240: }
13241: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13242:
1.278 brouard 13243:
1.126 brouard 13244: /* Reads comments: lines beginning with '#' */
13245: numlinepar=0;
1.277 brouard 13246: /* Is it a BOM UTF-8 Windows file? */
13247: /* First parameter line */
1.197 brouard 13248: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13249: noffset=0;
13250: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13251: {
13252: noffset=noffset+3;
13253: printf("# File is an UTF8 Bom.\n"); // 0xBF
13254: }
1.302 brouard 13255: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13256: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13257: {
13258: noffset=noffset+2;
13259: printf("# File is an UTF16BE BOM file\n");
13260: }
13261: else if( line[0] == 0 && line[1] == 0)
13262: {
13263: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13264: noffset=noffset+4;
13265: printf("# File is an UTF16BE BOM file\n");
13266: }
13267: } else{
13268: ;/*printf(" Not a BOM file\n");*/
13269: }
13270:
1.197 brouard 13271: /* If line starts with a # it is a comment */
1.277 brouard 13272: if (line[noffset] == '#') {
1.197 brouard 13273: numlinepar++;
13274: fputs(line,stdout);
13275: fputs(line,ficparo);
1.278 brouard 13276: fputs(line,ficres);
1.197 brouard 13277: fputs(line,ficlog);
13278: continue;
13279: }else
13280: break;
13281: }
13282: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13283: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13284: if (num_filled != 5) {
13285: printf("Should be 5 parameters\n");
1.283 brouard 13286: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13287: }
1.126 brouard 13288: numlinepar++;
1.197 brouard 13289: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13290: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13291: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13292: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13293: }
13294: /* Second parameter line */
13295: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13296: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13297: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13298: if (line[0] == '#') {
13299: numlinepar++;
1.283 brouard 13300: printf("%s",line);
13301: fprintf(ficres,"%s",line);
13302: fprintf(ficparo,"%s",line);
13303: fprintf(ficlog,"%s",line);
1.197 brouard 13304: continue;
13305: }else
13306: break;
13307: }
1.223 brouard 13308: 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", \
13309: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13310: if (num_filled != 11) {
13311: 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 13312: printf("but line=%s\n",line);
1.283 brouard 13313: 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");
13314: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13315: }
1.286 brouard 13316: if( lastpass > maxwav){
13317: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13318: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13319: fflush(ficlog);
13320: goto end;
13321: }
13322: 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 13323: 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 13324: 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 13325: 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 13326: }
1.203 brouard 13327: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13328: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13329: /* Third parameter line */
13330: while(fgets(line, MAXLINE, ficpar)) {
13331: /* If line starts with a # it is a comment */
13332: if (line[0] == '#') {
13333: numlinepar++;
1.283 brouard 13334: printf("%s",line);
13335: fprintf(ficres,"%s",line);
13336: fprintf(ficparo,"%s",line);
13337: fprintf(ficlog,"%s",line);
1.197 brouard 13338: continue;
13339: }else
13340: break;
13341: }
1.351 brouard 13342: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
13343: if (num_filled != 1){
13344: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13345: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13346: model[0]='\0';
13347: goto end;
13348: }else{
13349: trimbtab(linetmp,line); /* Trims multiple blanks in line */
13350: strcpy(line, linetmp);
13351: }
13352: }
13353: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 13354: if (num_filled != 1){
1.302 brouard 13355: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13356: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13357: model[0]='\0';
13358: goto end;
13359: }
13360: else{
13361: if (model[0]=='+'){
13362: for(i=1; i<=strlen(model);i++)
13363: modeltemp[i-1]=model[i];
1.201 brouard 13364: strcpy(model,modeltemp);
1.197 brouard 13365: }
13366: }
1.338 brouard 13367: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13368: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13369: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13370: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13371: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13372: }
13373: /* 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); */
13374: /* numlinepar=numlinepar+3; /\* In general *\/ */
13375: /* 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 13376: /* 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); */
13377: /* 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 13378: fflush(ficlog);
1.190 brouard 13379: /* if(model[0]=='#'|| model[0]== '\0'){ */
13380: if(model[0]=='#'){
1.279 brouard 13381: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13382: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13383: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13384: if(mle != -1){
1.279 brouard 13385: 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 13386: exit(1);
13387: }
13388: }
1.126 brouard 13389: while((c=getc(ficpar))=='#' && c!= EOF){
13390: ungetc(c,ficpar);
13391: fgets(line, MAXLINE, ficpar);
13392: numlinepar++;
1.195 brouard 13393: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13394: z[0]=line[1];
1.342 brouard 13395: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13396: debugILK=1;printf("DebugILK\n");
1.195 brouard 13397: }
13398: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13399: fputs(line, stdout);
13400: //puts(line);
1.126 brouard 13401: fputs(line,ficparo);
13402: fputs(line,ficlog);
13403: }
13404: ungetc(c,ficpar);
13405:
13406:
1.290 brouard 13407: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13408: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13409: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13410: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13411: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13412: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13413: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13414: v1+v2*age+v2*v3 makes cptcovn = 3
13415: */
13416: if (strlen(model)>1)
1.187 brouard 13417: 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 13418: else
1.187 brouard 13419: ncovmodel=2; /* Constant and age */
1.133 brouard 13420: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13421: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13422: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13423: 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);
13424: 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);
13425: fflush(stdout);
13426: fclose (ficlog);
13427: goto end;
13428: }
1.126 brouard 13429: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13430: delti=delti3[1][1];
13431: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13432: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13433: /* We could also provide initial parameters values giving by simple logistic regression
13434: * only one way, that is without matrix product. We will have nlstate maximizations */
13435: /* for(i=1;i<nlstate;i++){ */
13436: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13437: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13438: /* } */
1.126 brouard 13439: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13440: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13441: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13442: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13443: fclose (ficparo);
13444: fclose (ficlog);
13445: goto end;
13446: exit(0);
1.220 brouard 13447: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13448: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13449: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13450: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13451: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13452: matcov=matrix(1,npar,1,npar);
1.203 brouard 13453: hess=matrix(1,npar,1,npar);
1.220 brouard 13454: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13455: /* Read guessed parameters */
1.126 brouard 13456: /* Reads comments: lines beginning with '#' */
13457: while((c=getc(ficpar))=='#' && c!= EOF){
13458: ungetc(c,ficpar);
13459: fgets(line, MAXLINE, ficpar);
13460: numlinepar++;
1.141 brouard 13461: fputs(line,stdout);
1.126 brouard 13462: fputs(line,ficparo);
13463: fputs(line,ficlog);
13464: }
13465: ungetc(c,ficpar);
13466:
13467: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13468: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13469: for(i=1; i <=nlstate; i++){
1.234 brouard 13470: j=0;
1.126 brouard 13471: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13472: if(jj==i) continue;
13473: j++;
1.292 brouard 13474: while((c=getc(ficpar))=='#' && c!= EOF){
13475: ungetc(c,ficpar);
13476: fgets(line, MAXLINE, ficpar);
13477: numlinepar++;
13478: fputs(line,stdout);
13479: fputs(line,ficparo);
13480: fputs(line,ficlog);
13481: }
13482: ungetc(c,ficpar);
1.234 brouard 13483: fscanf(ficpar,"%1d%1d",&i1,&j1);
13484: if ((i1 != i) || (j1 != jj)){
13485: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13486: It might be a problem of design; if ncovcol and the model are correct\n \
13487: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13488: exit(1);
13489: }
13490: fprintf(ficparo,"%1d%1d",i1,j1);
13491: if(mle==1)
13492: printf("%1d%1d",i,jj);
13493: fprintf(ficlog,"%1d%1d",i,jj);
13494: for(k=1; k<=ncovmodel;k++){
13495: fscanf(ficpar," %lf",¶m[i][j][k]);
13496: if(mle==1){
13497: printf(" %lf",param[i][j][k]);
13498: fprintf(ficlog," %lf",param[i][j][k]);
13499: }
13500: else
13501: fprintf(ficlog," %lf",param[i][j][k]);
13502: fprintf(ficparo," %lf",param[i][j][k]);
13503: }
13504: fscanf(ficpar,"\n");
13505: numlinepar++;
13506: if(mle==1)
13507: printf("\n");
13508: fprintf(ficlog,"\n");
13509: fprintf(ficparo,"\n");
1.126 brouard 13510: }
13511: }
13512: fflush(ficlog);
1.234 brouard 13513:
1.251 brouard 13514: /* Reads parameters values */
1.126 brouard 13515: p=param[1][1];
1.251 brouard 13516: pstart=paramstart[1][1];
1.126 brouard 13517:
13518: /* Reads comments: lines beginning with '#' */
13519: while((c=getc(ficpar))=='#' && c!= EOF){
13520: ungetc(c,ficpar);
13521: fgets(line, MAXLINE, ficpar);
13522: numlinepar++;
1.141 brouard 13523: fputs(line,stdout);
1.126 brouard 13524: fputs(line,ficparo);
13525: fputs(line,ficlog);
13526: }
13527: ungetc(c,ficpar);
13528:
13529: for(i=1; i <=nlstate; i++){
13530: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13531: fscanf(ficpar,"%1d%1d",&i1,&j1);
13532: if ( (i1-i) * (j1-j) != 0){
13533: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13534: exit(1);
13535: }
13536: printf("%1d%1d",i,j);
13537: fprintf(ficparo,"%1d%1d",i1,j1);
13538: fprintf(ficlog,"%1d%1d",i1,j1);
13539: for(k=1; k<=ncovmodel;k++){
13540: fscanf(ficpar,"%le",&delti3[i][j][k]);
13541: printf(" %le",delti3[i][j][k]);
13542: fprintf(ficparo," %le",delti3[i][j][k]);
13543: fprintf(ficlog," %le",delti3[i][j][k]);
13544: }
13545: fscanf(ficpar,"\n");
13546: numlinepar++;
13547: printf("\n");
13548: fprintf(ficparo,"\n");
13549: fprintf(ficlog,"\n");
1.126 brouard 13550: }
13551: }
13552: fflush(ficlog);
1.234 brouard 13553:
1.145 brouard 13554: /* Reads covariance matrix */
1.126 brouard 13555: delti=delti3[1][1];
1.220 brouard 13556:
13557:
1.126 brouard 13558: /* 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 13559:
1.126 brouard 13560: /* Reads comments: lines beginning with '#' */
13561: while((c=getc(ficpar))=='#' && c!= EOF){
13562: ungetc(c,ficpar);
13563: fgets(line, MAXLINE, ficpar);
13564: numlinepar++;
1.141 brouard 13565: fputs(line,stdout);
1.126 brouard 13566: fputs(line,ficparo);
13567: fputs(line,ficlog);
13568: }
13569: ungetc(c,ficpar);
1.220 brouard 13570:
1.126 brouard 13571: matcov=matrix(1,npar,1,npar);
1.203 brouard 13572: hess=matrix(1,npar,1,npar);
1.131 brouard 13573: for(i=1; i <=npar; i++)
13574: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13575:
1.194 brouard 13576: /* Scans npar lines */
1.126 brouard 13577: for(i=1; i <=npar; i++){
1.226 brouard 13578: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13579: if(count != 3){
1.226 brouard 13580: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13581: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13582: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13583: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13584: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13585: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13586: exit(1);
1.220 brouard 13587: }else{
1.226 brouard 13588: if(mle==1)
13589: printf("%1d%1d%d",i1,j1,jk);
13590: }
13591: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13592: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13593: for(j=1; j <=i; j++){
1.226 brouard 13594: fscanf(ficpar," %le",&matcov[i][j]);
13595: if(mle==1){
13596: printf(" %.5le",matcov[i][j]);
13597: }
13598: fprintf(ficlog," %.5le",matcov[i][j]);
13599: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13600: }
13601: fscanf(ficpar,"\n");
13602: numlinepar++;
13603: if(mle==1)
1.220 brouard 13604: printf("\n");
1.126 brouard 13605: fprintf(ficlog,"\n");
13606: fprintf(ficparo,"\n");
13607: }
1.194 brouard 13608: /* End of read covariance matrix npar lines */
1.126 brouard 13609: for(i=1; i <=npar; i++)
13610: for(j=i+1;j<=npar;j++)
1.226 brouard 13611: matcov[i][j]=matcov[j][i];
1.126 brouard 13612:
13613: if(mle==1)
13614: printf("\n");
13615: fprintf(ficlog,"\n");
13616:
13617: fflush(ficlog);
13618:
13619: } /* End of mle != -3 */
1.218 brouard 13620:
1.186 brouard 13621: /* Main data
13622: */
1.290 brouard 13623: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13624: /* num=lvector(1,n); */
13625: /* moisnais=vector(1,n); */
13626: /* annais=vector(1,n); */
13627: /* moisdc=vector(1,n); */
13628: /* andc=vector(1,n); */
13629: /* weight=vector(1,n); */
13630: /* agedc=vector(1,n); */
13631: /* cod=ivector(1,n); */
13632: /* for(i=1;i<=n;i++){ */
13633: num=lvector(firstobs,lastobs);
13634: moisnais=vector(firstobs,lastobs);
13635: annais=vector(firstobs,lastobs);
13636: moisdc=vector(firstobs,lastobs);
13637: andc=vector(firstobs,lastobs);
13638: weight=vector(firstobs,lastobs);
13639: agedc=vector(firstobs,lastobs);
13640: cod=ivector(firstobs,lastobs);
13641: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13642: num[i]=0;
13643: moisnais[i]=0;
13644: annais[i]=0;
13645: moisdc[i]=0;
13646: andc[i]=0;
13647: agedc[i]=0;
13648: cod[i]=0;
13649: weight[i]=1.0; /* Equal weights, 1 by default */
13650: }
1.290 brouard 13651: mint=matrix(1,maxwav,firstobs,lastobs);
13652: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13653: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13654: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13655: tab=ivector(1,NCOVMAX);
1.144 brouard 13656: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13657: 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 13658:
1.136 brouard 13659: /* Reads data from file datafile */
13660: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13661: goto end;
13662:
13663: /* Calculation of the number of parameters from char model */
1.234 brouard 13664: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13665: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13666: k=3 V4 Tvar[k=3]= 4 (from V4)
13667: k=2 V1 Tvar[k=2]= 1 (from V1)
13668: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13669: */
13670:
13671: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13672: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13673: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13674: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13675: TvarsD=ivector(1,NCOVMAX); /* */
13676: TvarsQind=ivector(1,NCOVMAX); /* */
13677: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13678: TvarF=ivector(1,NCOVMAX); /* */
13679: TvarFind=ivector(1,NCOVMAX); /* */
13680: TvarV=ivector(1,NCOVMAX); /* */
13681: TvarVind=ivector(1,NCOVMAX); /* */
13682: TvarA=ivector(1,NCOVMAX); /* */
13683: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13684: TvarFD=ivector(1,NCOVMAX); /* */
13685: TvarFDind=ivector(1,NCOVMAX); /* */
13686: TvarFQ=ivector(1,NCOVMAX); /* */
13687: TvarFQind=ivector(1,NCOVMAX); /* */
13688: TvarVD=ivector(1,NCOVMAX); /* */
13689: TvarVDind=ivector(1,NCOVMAX); /* */
13690: TvarVQ=ivector(1,NCOVMAX); /* */
13691: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13692: TvarVV=ivector(1,NCOVMAX); /* */
13693: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 13694: TvarVVA=ivector(1,NCOVMAX); /* */
13695: TvarVVAind=ivector(1,NCOVMAX); /* */
13696: TvarAVVA=ivector(1,NCOVMAX); /* */
13697: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13698:
1.230 brouard 13699: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13700: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13701: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13702: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13703: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 13704: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
13705: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
13706:
1.137 brouard 13707: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13708: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13709: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13710: */
13711: /* For model-covariate k tells which data-covariate to use but
13712: because this model-covariate is a construction we invent a new column
13713: ncovcol + k1
13714: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13715: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13716: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13717: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13718: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13719: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13720: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13721: */
1.145 brouard 13722: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13723: 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 13724: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13725: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 13726: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 13727: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13728: 4 covariates (3 plus signs)
13729: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13730: */
13731: for(i=1;i<NCOVMAX;i++)
13732: Tage[i]=0;
1.230 brouard 13733: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13734: * individual dummy, fixed or varying:
13735: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13736: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13737: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13738: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13739: * Tmodelind[1]@9={9,0,3,2,}*/
13740: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13741: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13742: * individual quantitative, fixed or varying:
13743: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13744: * 3, 1, 0, 0, 0, 0, 0, 0},
13745: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 13746:
13747: /* Probably useless zeroes */
13748: for(i=1;i<NCOVMAX;i++){
13749: DummyV[i]=0;
13750: FixedV[i]=0;
13751: }
13752:
13753: for(i=1; i <=ncovcol;i++){
13754: DummyV[i]=0;
13755: FixedV[i]=0;
13756: }
13757: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
13758: DummyV[i]=1;
13759: FixedV[i]=0;
13760: }
13761: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
13762: DummyV[i]=0;
13763: FixedV[i]=1;
13764: }
13765: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
13766: DummyV[i]=1;
13767: FixedV[i]=1;
13768: }
13769: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
13770: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13771: 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]);
13772: }
13773:
13774:
13775:
1.186 brouard 13776: /* Main decodemodel */
13777:
1.187 brouard 13778:
1.223 brouard 13779: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13780: goto end;
13781:
1.137 brouard 13782: if((double)(lastobs-imx)/(double)imx > 1.10){
13783: nbwarn++;
13784: 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);
13785: 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);
13786: }
1.136 brouard 13787: /* if(mle==1){*/
1.137 brouard 13788: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13789: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13790: }
13791:
13792: /*-calculation of age at interview from date of interview and age at death -*/
13793: agev=matrix(1,maxwav,1,imx);
13794:
13795: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13796: goto end;
13797:
1.126 brouard 13798:
1.136 brouard 13799: agegomp=(int)agemin;
1.290 brouard 13800: free_vector(moisnais,firstobs,lastobs);
13801: free_vector(annais,firstobs,lastobs);
1.126 brouard 13802: /* free_matrix(mint,1,maxwav,1,n);
13803: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13804: /* free_vector(moisdc,1,n); */
13805: /* free_vector(andc,1,n); */
1.145 brouard 13806: /* */
13807:
1.126 brouard 13808: wav=ivector(1,imx);
1.214 brouard 13809: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13810: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13811: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13812: 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.*/
13813: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13814: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13815:
13816: /* Concatenates waves */
1.214 brouard 13817: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13818: Death is a valid wave (if date is known).
13819: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13820: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13821: and mw[mi+1][i]. dh depends on stepm.
13822: */
13823:
1.126 brouard 13824: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13825: /* Concatenates waves */
1.145 brouard 13826:
1.290 brouard 13827: free_vector(moisdc,firstobs,lastobs);
13828: free_vector(andc,firstobs,lastobs);
1.215 brouard 13829:
1.126 brouard 13830: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13831: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13832: ncodemax[1]=1;
1.145 brouard 13833: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13834: cptcoveff=0;
1.220 brouard 13835: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13836: 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 13837: }
13838:
13839: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13840: invalidvarcomb=ivector(0, ncovcombmax);
13841: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13842: invalidvarcomb[i]=0;
13843:
1.211 brouard 13844: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13845: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13846: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13847:
1.200 brouard 13848: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13849: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13850: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13851: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13852: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13853: * (currently 0 or 1) in the data.
13854: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13855: * corresponding modality (h,j).
13856: */
13857:
1.145 brouard 13858: h=0;
13859: /*if (cptcovn > 0) */
1.126 brouard 13860: m=pow(2,cptcoveff);
13861:
1.144 brouard 13862: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13863: * For k=4 covariates, h goes from 1 to m=2**k
13864: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13865: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13866: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13867: *______________________________ *______________________
13868: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13869: * 2 2 1 1 1 * 1 0 0 0 1
13870: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13871: * 4 2 2 1 1 * 3 0 0 1 1
13872: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13873: * 6 2 1 2 1 * 5 0 1 0 1
13874: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13875: * 8 2 2 2 1 * 7 0 1 1 1
13876: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13877: * 10 2 1 1 2 * 9 1 0 0 1
13878: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13879: * 12 2 2 1 2 * 11 1 0 1 1
13880: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13881: * 14 2 1 2 2 * 13 1 1 0 1
13882: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13883: * 16 2 2 2 2 * 15 1 1 1 1
13884: */
1.212 brouard 13885: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13886: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13887: * and the value of each covariate?
13888: * V1=1, V2=1, V3=2, V4=1 ?
13889: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13890: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13891: * In order to get the real value in the data, we use nbcode
13892: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13893: * We are keeping this crazy system in order to be able (in the future?)
13894: * to have more than 2 values (0 or 1) for a covariate.
13895: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13896: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13897: * bbbbbbbb
13898: * 76543210
13899: * h-1 00000101 (6-1=5)
1.219 brouard 13900: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13901: * &
13902: * 1 00000001 (1)
1.219 brouard 13903: * 00000000 = 1 & ((h-1) >> (k-1))
13904: * +1= 00000001 =1
1.211 brouard 13905: *
13906: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13907: * h' 1101 =2^3+2^2+0x2^1+2^0
13908: * >>k' 11
13909: * & 00000001
13910: * = 00000001
13911: * +1 = 00000010=2 = codtabm(14,3)
13912: * Reverse h=6 and m=16?
13913: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13914: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13915: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13916: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13917: * V3=decodtabm(14,3,2**4)=2
13918: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13919: *(h-1) >> (j-1) 0011 =13 >> 2
13920: * &1 000000001
13921: * = 000000001
13922: * +1= 000000010 =2
13923: * 2211
13924: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13925: * V3=2
1.220 brouard 13926: * codtabm and decodtabm are identical
1.211 brouard 13927: */
13928:
1.145 brouard 13929:
13930: free_ivector(Ndum,-1,NCOVMAX);
13931:
13932:
1.126 brouard 13933:
1.186 brouard 13934: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13935: strcpy(optionfilegnuplot,optionfilefiname);
13936: if(mle==-3)
1.201 brouard 13937: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13938: strcat(optionfilegnuplot,".gp");
13939:
13940: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13941: printf("Problem with file %s",optionfilegnuplot);
13942: }
13943: else{
1.204 brouard 13944: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13945: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13946: //fprintf(ficgp,"set missing 'NaNq'\n");
13947: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13948: }
13949: /* fclose(ficgp);*/
1.186 brouard 13950:
13951:
13952: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13953:
13954: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13955: if(mle==-3)
1.201 brouard 13956: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13957: strcat(optionfilehtm,".htm");
13958: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13959: printf("Problem with %s \n",optionfilehtm);
13960: exit(0);
1.126 brouard 13961: }
13962:
13963: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13964: strcat(optionfilehtmcov,"-cov.htm");
13965: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13966: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13967: }
13968: else{
13969: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13970: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13971: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13972: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13973: }
13974:
1.335 brouard 13975: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13976: <title>IMaCh %s</title></head>\n\
13977: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13978: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13979: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13980: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13981: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13982:
13983: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13984: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13985: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13986: 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 13987: \n\
13988: <hr size=\"2\" color=\"#EC5E5E\">\
13989: <ul><li><h4>Parameter files</h4>\n\
13990: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13991: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13992: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13993: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13994: - Date and time at start: %s</ul>\n",\
1.335 brouard 13995: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13996: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13997: fileres,fileres,\
13998: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13999: fflush(fichtm);
14000:
14001: strcpy(pathr,path);
14002: strcat(pathr,optionfilefiname);
1.184 brouard 14003: #ifdef WIN32
14004: _chdir(optionfilefiname); /* Move to directory named optionfile */
14005: #else
1.126 brouard 14006: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 14007: #endif
14008:
1.126 brouard 14009:
1.220 brouard 14010: /* Calculates basic frequencies. Computes observed prevalence at single age
14011: and for any valid combination of covariates
1.126 brouard 14012: and prints on file fileres'p'. */
1.251 brouard 14013: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 14014: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 14015:
14016: fprintf(fichtm,"\n");
1.286 brouard 14017: 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 14018: ftol, stepm);
14019: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
14020: ncurrv=1;
14021: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
14022: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
14023: ncurrv=i;
14024: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14025: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 14026: ncurrv=i;
14027: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14028: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 14029: ncurrv=i;
14030: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
14031: 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", \
14032: nlstate, ndeath, maxwav, mle, weightopt);
14033:
14034: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
14035: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
14036:
14037:
1.317 brouard 14038: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 14039: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
14040: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 14041: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 14042: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 14043: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14044: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14045: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14046: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 14047:
1.126 brouard 14048: /* For Powell, parameters are in a vector p[] starting at p[1]
14049: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
14050: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
14051:
14052: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 14053: /* For mortality only */
1.126 brouard 14054: if (mle==-3){
1.136 brouard 14055: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 14056: for(i=1;i<=NDIM;i++)
14057: for(j=1;j<=NDIM;j++)
14058: ximort[i][j]=0.;
1.186 brouard 14059: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 14060: cens=ivector(firstobs,lastobs);
14061: ageexmed=vector(firstobs,lastobs);
14062: agecens=vector(firstobs,lastobs);
14063: dcwave=ivector(firstobs,lastobs);
1.223 brouard 14064:
1.126 brouard 14065: for (i=1; i<=imx; i++){
14066: dcwave[i]=-1;
14067: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 14068: if (s[m][i]>nlstate) {
14069: dcwave[i]=m;
14070: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
14071: break;
14072: }
1.126 brouard 14073: }
1.226 brouard 14074:
1.126 brouard 14075: for (i=1; i<=imx; i++) {
14076: if (wav[i]>0){
1.226 brouard 14077: ageexmed[i]=agev[mw[1][i]][i];
14078: j=wav[i];
14079: agecens[i]=1.;
14080:
14081: if (ageexmed[i]> 1 && wav[i] > 0){
14082: agecens[i]=agev[mw[j][i]][i];
14083: cens[i]= 1;
14084: }else if (ageexmed[i]< 1)
14085: cens[i]= -1;
14086: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
14087: cens[i]=0 ;
1.126 brouard 14088: }
14089: else cens[i]=-1;
14090: }
14091:
14092: for (i=1;i<=NDIM;i++) {
14093: for (j=1;j<=NDIM;j++)
1.226 brouard 14094: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 14095: }
14096:
1.302 brouard 14097: p[1]=0.0268; p[NDIM]=0.083;
14098: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14099:
14100:
1.136 brouard 14101: #ifdef GSL
14102: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14103: #else
1.126 brouard 14104: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14105: #endif
1.201 brouard 14106: strcpy(filerespow,"POW-MORT_");
14107: strcat(filerespow,fileresu);
1.126 brouard 14108: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14109: printf("Problem with resultfile: %s\n", filerespow);
14110: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14111: }
1.136 brouard 14112: #ifdef GSL
14113: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14114: #else
1.126 brouard 14115: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14116: #endif
1.126 brouard 14117: /* for (i=1;i<=nlstate;i++)
14118: for(j=1;j<=nlstate+ndeath;j++)
14119: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14120: */
14121: fprintf(ficrespow,"\n");
1.136 brouard 14122: #ifdef GSL
14123: /* gsl starts here */
14124: T = gsl_multimin_fminimizer_nmsimplex;
14125: gsl_multimin_fminimizer *sfm = NULL;
14126: gsl_vector *ss, *x;
14127: gsl_multimin_function minex_func;
14128:
14129: /* Initial vertex size vector */
14130: ss = gsl_vector_alloc (NDIM);
14131:
14132: if (ss == NULL){
14133: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14134: }
14135: /* Set all step sizes to 1 */
14136: gsl_vector_set_all (ss, 0.001);
14137:
14138: /* Starting point */
1.126 brouard 14139:
1.136 brouard 14140: x = gsl_vector_alloc (NDIM);
14141:
14142: if (x == NULL){
14143: gsl_vector_free(ss);
14144: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14145: }
14146:
14147: /* Initialize method and iterate */
14148: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14149: /* gsl_vector_set(x, 0, 0.0268); */
14150: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14151: gsl_vector_set(x, 0, p[1]);
14152: gsl_vector_set(x, 1, p[2]);
14153:
14154: minex_func.f = &gompertz_f;
14155: minex_func.n = NDIM;
14156: minex_func.params = (void *)&p; /* ??? */
14157:
14158: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14159: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14160:
14161: printf("Iterations beginning .....\n\n");
14162: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14163:
14164: iteri=0;
14165: while (rval == GSL_CONTINUE){
14166: iteri++;
14167: status = gsl_multimin_fminimizer_iterate(sfm);
14168:
14169: if (status) printf("error: %s\n", gsl_strerror (status));
14170: fflush(0);
14171:
14172: if (status)
14173: break;
14174:
14175: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14176: ssval = gsl_multimin_fminimizer_size (sfm);
14177:
14178: if (rval == GSL_SUCCESS)
14179: printf ("converged to a local maximum at\n");
14180:
14181: printf("%5d ", iteri);
14182: for (it = 0; it < NDIM; it++){
14183: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14184: }
14185: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14186: }
14187:
14188: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14189:
14190: gsl_vector_free(x); /* initial values */
14191: gsl_vector_free(ss); /* inital step size */
14192: for (it=0; it<NDIM; it++){
14193: p[it+1]=gsl_vector_get(sfm->x,it);
14194: fprintf(ficrespow," %.12lf", p[it]);
14195: }
14196: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14197: #endif
14198: #ifdef POWELL
14199: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14200: #endif
1.126 brouard 14201: fclose(ficrespow);
14202:
1.203 brouard 14203: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14204:
14205: for(i=1; i <=NDIM; i++)
14206: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14207: matcov[i][j]=matcov[j][i];
1.126 brouard 14208:
14209: printf("\nCovariance matrix\n ");
1.203 brouard 14210: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14211: for(i=1; i <=NDIM; i++) {
14212: for(j=1;j<=NDIM;j++){
1.220 brouard 14213: printf("%f ",matcov[i][j]);
14214: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14215: }
1.203 brouard 14216: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14217: }
14218:
14219: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14220: for (i=1;i<=NDIM;i++) {
1.126 brouard 14221: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14222: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14223: }
1.302 brouard 14224: lsurv=vector(agegomp,AGESUP);
14225: lpop=vector(agegomp,AGESUP);
14226: tpop=vector(agegomp,AGESUP);
1.126 brouard 14227: lsurv[agegomp]=100000;
14228:
14229: for (k=agegomp;k<=AGESUP;k++) {
14230: agemortsup=k;
14231: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14232: }
14233:
14234: for (k=agegomp;k<agemortsup;k++)
14235: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14236:
14237: for (k=agegomp;k<agemortsup;k++){
14238: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14239: sumlpop=sumlpop+lpop[k];
14240: }
14241:
14242: tpop[agegomp]=sumlpop;
14243: for (k=agegomp;k<(agemortsup-3);k++){
14244: /* tpop[k+1]=2;*/
14245: tpop[k+1]=tpop[k]-lpop[k];
14246: }
14247:
14248:
14249: printf("\nAge lx qx dx Lx Tx e(x)\n");
14250: for (k=agegomp;k<(agemortsup-2);k++)
14251: 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]);
14252:
14253:
14254: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14255: ageminpar=50;
14256: agemaxpar=100;
1.194 brouard 14257: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14258: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14259: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14260: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
14261: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14262: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14263: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14264: }else{
14265: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14266: 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 14267: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14268: }
1.201 brouard 14269: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14270: stepm, weightopt,\
14271: model,imx,p,matcov,agemortsup);
14272:
1.302 brouard 14273: free_vector(lsurv,agegomp,AGESUP);
14274: free_vector(lpop,agegomp,AGESUP);
14275: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14276: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14277: free_ivector(dcwave,firstobs,lastobs);
14278: free_vector(agecens,firstobs,lastobs);
14279: free_vector(ageexmed,firstobs,lastobs);
14280: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14281: #ifdef GSL
1.136 brouard 14282: #endif
1.186 brouard 14283: } /* Endof if mle==-3 mortality only */
1.205 brouard 14284: /* Standard */
14285: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14286: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14287: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14288: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14289: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14290: for (k=1; k<=npar;k++)
14291: printf(" %d %8.5f",k,p[k]);
14292: printf("\n");
1.205 brouard 14293: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14294: /* mlikeli uses func not funcone */
1.247 brouard 14295: /* for(i=1;i<nlstate;i++){ */
14296: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14297: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14298: /* } */
1.205 brouard 14299: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14300: }
14301: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14302: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14303: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14304: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14305: }
14306: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14307: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14308: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14309: /* exit(0); */
1.126 brouard 14310: for (k=1; k<=npar;k++)
14311: printf(" %d %8.5f",k,p[k]);
14312: printf("\n");
14313:
14314: /*--------- results files --------------*/
1.283 brouard 14315: /* 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 14316:
14317:
14318: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14319: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14320: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14321:
14322: printf("#model= 1 + age ");
14323: fprintf(ficres,"#model= 1 + age ");
14324: fprintf(ficlog,"#model= 1 + age ");
14325: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14326: </ul>", model);
14327:
14328: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14329: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14330: if(nagesqr==1){
14331: printf(" + age*age ");
14332: fprintf(ficres," + age*age ");
14333: fprintf(ficlog," + age*age ");
14334: fprintf(fichtm, "<th>+ age*age</th>");
14335: }
14336: for(j=1;j <=ncovmodel-2;j++){
14337: if(Typevar[j]==0) {
14338: printf(" + V%d ",Tvar[j]);
14339: fprintf(ficres," + V%d ",Tvar[j]);
14340: fprintf(ficlog," + V%d ",Tvar[j]);
14341: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14342: }else if(Typevar[j]==1) {
14343: printf(" + V%d*age ",Tvar[j]);
14344: fprintf(ficres," + V%d*age ",Tvar[j]);
14345: fprintf(ficlog," + V%d*age ",Tvar[j]);
14346: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14347: }else if(Typevar[j]==2) {
14348: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14349: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14350: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14351: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14352: }else if(Typevar[j]==3) { /* TO VERIFY */
14353: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14354: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14355: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14356: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14357: }
14358: }
14359: printf("\n");
14360: fprintf(ficres,"\n");
14361: fprintf(ficlog,"\n");
14362: fprintf(fichtm, "</tr>");
14363: fprintf(fichtm, "\n");
14364:
14365:
1.126 brouard 14366: for(i=1,jk=1; i <=nlstate; i++){
14367: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14368: if (k != i) {
1.319 brouard 14369: fprintf(fichtm, "<tr>");
1.225 brouard 14370: printf("%d%d ",i,k);
14371: fprintf(ficlog,"%d%d ",i,k);
14372: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14373: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14374: for(j=1; j <=ncovmodel; j++){
14375: printf("%12.7f ",p[jk]);
14376: fprintf(ficlog,"%12.7f ",p[jk]);
14377: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14378: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14379: jk++;
14380: }
14381: printf("\n");
14382: fprintf(ficlog,"\n");
14383: fprintf(ficres,"\n");
1.319 brouard 14384: fprintf(fichtm, "</tr>\n");
1.225 brouard 14385: }
1.126 brouard 14386: }
14387: }
1.319 brouard 14388: /* fprintf(fichtm,"</tr>\n"); */
14389: fprintf(fichtm,"</table>\n");
14390: fprintf(fichtm, "\n");
14391:
1.203 brouard 14392: if(mle != 0){
14393: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14394: ftolhess=ftol; /* Usually correct */
1.203 brouard 14395: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14396: 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");
14397: 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 14398: 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 14399: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14400: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14401: if(nagesqr==1){
14402: printf(" + age*age ");
14403: fprintf(ficres," + age*age ");
14404: fprintf(ficlog," + age*age ");
14405: fprintf(fichtm, "<th>+ age*age</th>");
14406: }
14407: for(j=1;j <=ncovmodel-2;j++){
14408: if(Typevar[j]==0) {
14409: printf(" + V%d ",Tvar[j]);
14410: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14411: }else if(Typevar[j]==1) {
14412: printf(" + V%d*age ",Tvar[j]);
14413: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14414: }else if(Typevar[j]==2) {
14415: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14416: }else if(Typevar[j]==3) { /* TO VERIFY */
14417: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14418: }
14419: }
14420: fprintf(fichtm, "</tr>\n");
14421:
1.203 brouard 14422: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14423: for(k=1; k <=(nlstate+ndeath); k++){
14424: if (k != i) {
1.319 brouard 14425: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14426: printf("%d%d ",i,k);
14427: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14428: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14429: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14430: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14431: 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]));
14432: 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 14433: if(fabs(wald) > 1.96){
1.321 brouard 14434: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14435: }else{
14436: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14437: }
1.324 brouard 14438: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14439: 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 14440: jk++;
14441: }
14442: printf("\n");
14443: fprintf(ficlog,"\n");
1.319 brouard 14444: fprintf(fichtm, "</tr>\n");
1.225 brouard 14445: }
14446: }
1.193 brouard 14447: }
1.203 brouard 14448: } /* end of hesscov and Wald tests */
1.319 brouard 14449: fprintf(fichtm,"</table>\n");
1.225 brouard 14450:
1.203 brouard 14451: /* */
1.126 brouard 14452: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14453: printf("# Scales (for hessian or gradient estimation)\n");
14454: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14455: for(i=1,jk=1; i <=nlstate; i++){
14456: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14457: if (j!=i) {
14458: fprintf(ficres,"%1d%1d",i,j);
14459: printf("%1d%1d",i,j);
14460: fprintf(ficlog,"%1d%1d",i,j);
14461: for(k=1; k<=ncovmodel;k++){
14462: printf(" %.5e",delti[jk]);
14463: fprintf(ficlog," %.5e",delti[jk]);
14464: fprintf(ficres," %.5e",delti[jk]);
14465: jk++;
14466: }
14467: printf("\n");
14468: fprintf(ficlog,"\n");
14469: fprintf(ficres,"\n");
14470: }
1.126 brouard 14471: }
14472: }
14473:
14474: 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 14475: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14476: 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");
14477: 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");
14478: /* # 121 Var(a12)\n\ */
14479: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14480: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14481: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14482: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14483: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14484: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14485: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14486:
14487:
14488: /* Just to have a covariance matrix which will be more understandable
14489: even is we still don't want to manage dictionary of variables
14490: */
14491: for(itimes=1;itimes<=2;itimes++){
14492: jj=0;
14493: for(i=1; i <=nlstate; i++){
1.225 brouard 14494: for(j=1; j <=nlstate+ndeath; j++){
14495: if(j==i) continue;
14496: for(k=1; k<=ncovmodel;k++){
14497: jj++;
14498: ca[0]= k+'a'-1;ca[1]='\0';
14499: if(itimes==1){
14500: if(mle>=1)
14501: printf("#%1d%1d%d",i,j,k);
14502: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14503: fprintf(ficres,"#%1d%1d%d",i,j,k);
14504: }else{
14505: if(mle>=1)
14506: printf("%1d%1d%d",i,j,k);
14507: fprintf(ficlog,"%1d%1d%d",i,j,k);
14508: fprintf(ficres,"%1d%1d%d",i,j,k);
14509: }
14510: ll=0;
14511: for(li=1;li <=nlstate; li++){
14512: for(lj=1;lj <=nlstate+ndeath; lj++){
14513: if(lj==li) continue;
14514: for(lk=1;lk<=ncovmodel;lk++){
14515: ll++;
14516: if(ll<=jj){
14517: cb[0]= lk +'a'-1;cb[1]='\0';
14518: if(ll<jj){
14519: if(itimes==1){
14520: if(mle>=1)
14521: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14522: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14523: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14524: }else{
14525: if(mle>=1)
14526: printf(" %.5e",matcov[jj][ll]);
14527: fprintf(ficlog," %.5e",matcov[jj][ll]);
14528: fprintf(ficres," %.5e",matcov[jj][ll]);
14529: }
14530: }else{
14531: if(itimes==1){
14532: if(mle>=1)
14533: printf(" Var(%s%1d%1d)",ca,i,j);
14534: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14535: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14536: }else{
14537: if(mle>=1)
14538: printf(" %.7e",matcov[jj][ll]);
14539: fprintf(ficlog," %.7e",matcov[jj][ll]);
14540: fprintf(ficres," %.7e",matcov[jj][ll]);
14541: }
14542: }
14543: }
14544: } /* end lk */
14545: } /* end lj */
14546: } /* end li */
14547: if(mle>=1)
14548: printf("\n");
14549: fprintf(ficlog,"\n");
14550: fprintf(ficres,"\n");
14551: numlinepar++;
14552: } /* end k*/
14553: } /*end j */
1.126 brouard 14554: } /* end i */
14555: } /* end itimes */
14556:
14557: fflush(ficlog);
14558: fflush(ficres);
1.225 brouard 14559: while(fgets(line, MAXLINE, ficpar)) {
14560: /* If line starts with a # it is a comment */
14561: if (line[0] == '#') {
14562: numlinepar++;
14563: fputs(line,stdout);
14564: fputs(line,ficparo);
14565: fputs(line,ficlog);
1.299 brouard 14566: fputs(line,ficres);
1.225 brouard 14567: continue;
14568: }else
14569: break;
14570: }
14571:
1.209 brouard 14572: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14573: /* ungetc(c,ficpar); */
14574: /* fgets(line, MAXLINE, ficpar); */
14575: /* fputs(line,stdout); */
14576: /* fputs(line,ficparo); */
14577: /* } */
14578: /* ungetc(c,ficpar); */
1.126 brouard 14579:
14580: estepm=0;
1.209 brouard 14581: 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 14582:
14583: if (num_filled != 6) {
14584: 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);
14585: 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);
14586: goto end;
14587: }
14588: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14589: }
14590: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14591: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14592:
1.209 brouard 14593: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14594: if (estepm==0 || estepm < stepm) estepm=stepm;
14595: if (fage <= 2) {
14596: bage = ageminpar;
14597: fage = agemaxpar;
14598: }
14599:
14600: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14601: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14602: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14603:
1.186 brouard 14604: /* Other stuffs, more or less useful */
1.254 brouard 14605: while(fgets(line, MAXLINE, ficpar)) {
14606: /* If line starts with a # it is a comment */
14607: if (line[0] == '#') {
14608: numlinepar++;
14609: fputs(line,stdout);
14610: fputs(line,ficparo);
14611: fputs(line,ficlog);
1.299 brouard 14612: fputs(line,ficres);
1.254 brouard 14613: continue;
14614: }else
14615: break;
14616: }
14617:
14618: 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){
14619:
14620: if (num_filled != 7) {
14621: 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);
14622: 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);
14623: goto end;
14624: }
14625: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14626: 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);
14627: 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);
14628: 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 14629: }
1.254 brouard 14630:
14631: while(fgets(line, MAXLINE, ficpar)) {
14632: /* If line starts with a # it is a comment */
14633: if (line[0] == '#') {
14634: numlinepar++;
14635: fputs(line,stdout);
14636: fputs(line,ficparo);
14637: fputs(line,ficlog);
1.299 brouard 14638: fputs(line,ficres);
1.254 brouard 14639: continue;
14640: }else
14641: break;
1.126 brouard 14642: }
14643:
14644:
14645: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14646: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14647:
1.254 brouard 14648: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14649: if (num_filled != 1) {
14650: 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);
14651: 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);
14652: goto end;
14653: }
14654: printf("pop_based=%d\n",popbased);
14655: fprintf(ficlog,"pop_based=%d\n",popbased);
14656: fprintf(ficparo,"pop_based=%d\n",popbased);
14657: fprintf(ficres,"pop_based=%d\n",popbased);
14658: }
14659:
1.258 brouard 14660: /* Results */
1.332 brouard 14661: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14662: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14663: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14664: endishere=0;
1.258 brouard 14665: nresult=0;
1.308 brouard 14666: parameterline=0;
1.258 brouard 14667: do{
14668: if(!fgets(line, MAXLINE, ficpar)){
14669: endishere=1;
1.308 brouard 14670: parameterline=15;
1.258 brouard 14671: }else if (line[0] == '#') {
14672: /* If line starts with a # it is a comment */
1.254 brouard 14673: numlinepar++;
14674: fputs(line,stdout);
14675: fputs(line,ficparo);
14676: fputs(line,ficlog);
1.299 brouard 14677: fputs(line,ficres);
1.254 brouard 14678: continue;
1.258 brouard 14679: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14680: parameterline=11;
1.296 brouard 14681: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14682: parameterline=12;
1.307 brouard 14683: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14684: parameterline=13;
1.307 brouard 14685: }
1.258 brouard 14686: else{
14687: parameterline=14;
1.254 brouard 14688: }
1.308 brouard 14689: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14690: case 11:
1.296 brouard 14691: 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)){
14692: 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 14693: 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);
14694: 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);
14695: 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);
14696: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14697: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14698: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14699: prvforecast = 1;
14700: }
14701: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14702: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14703: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14704: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14705: prvforecast = 2;
14706: }
14707: else {
14708: 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);
14709: 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);
14710: goto end;
1.258 brouard 14711: }
1.254 brouard 14712: break;
1.258 brouard 14713: case 12:
1.296 brouard 14714: 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)){
14715: 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);
14716: 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);
14717: 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);
14718: 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);
14719: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14720: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14721: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14722: prvbackcast = 1;
14723: }
14724: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14725: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14726: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14727: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14728: prvbackcast = 2;
14729: }
14730: else {
14731: 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);
14732: 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);
14733: goto end;
1.258 brouard 14734: }
1.230 brouard 14735: break;
1.258 brouard 14736: case 13:
1.332 brouard 14737: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14738: nresult++; /* Sum of resultlines */
1.342 brouard 14739: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14740: /* removefirstspace(&resultlineori); */
14741:
14742: if(strstr(resultlineori,"v") !=0){
14743: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14744: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14745: return 1;
14746: }
14747: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14748: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14749: if(nresult > MAXRESULTLINESPONE-1){
14750: 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);
14751: 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 14752: goto end;
14753: }
1.332 brouard 14754:
1.310 brouard 14755: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14756: fprintf(ficparo,"result: %s\n",resultline);
14757: fprintf(ficres,"result: %s\n",resultline);
14758: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14759: } else
14760: goto end;
1.307 brouard 14761: break;
14762: case 14:
14763: printf("Error: Unknown command '%s'\n",line);
14764: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14765: if(line[0] == ' ' || line[0] == '\n'){
14766: printf("It should not be an empty line '%s'\n",line);
14767: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14768: }
1.307 brouard 14769: if(ncovmodel >=2 && nresult==0 ){
14770: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14771: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14772: }
1.307 brouard 14773: /* goto end; */
14774: break;
1.308 brouard 14775: case 15:
14776: printf("End of resultlines.\n");
14777: fprintf(ficlog,"End of resultlines.\n");
14778: break;
14779: default: /* parameterline =0 */
1.307 brouard 14780: nresult=1;
14781: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14782: } /* End switch parameterline */
14783: }while(endishere==0); /* End do */
1.126 brouard 14784:
1.230 brouard 14785: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14786: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14787:
14788: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14789: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14790: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14791: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14792: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14793: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14794: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14795: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14796: }else{
1.270 brouard 14797: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14798: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14799: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14800: if(prvforecast==1){
14801: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14802: jprojd=jproj1;
14803: mprojd=mproj1;
14804: anprojd=anproj1;
14805: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14806: jprojf=jproj2;
14807: mprojf=mproj2;
14808: anprojf=anproj2;
14809: } else if(prvforecast == 2){
14810: dateprojd=dateintmean;
14811: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14812: dateprojf=dateintmean+yrfproj;
14813: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14814: }
14815: if(prvbackcast==1){
14816: datebackd=(jback1+12*mback1+365*anback1)/365;
14817: jbackd=jback1;
14818: mbackd=mback1;
14819: anbackd=anback1;
14820: datebackf=(jback2+12*mback2+365*anback2)/365;
14821: jbackf=jback2;
14822: mbackf=mback2;
14823: anbackf=anback2;
14824: } else if(prvbackcast == 2){
14825: datebackd=dateintmean;
14826: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14827: datebackf=dateintmean-yrbproj;
14828: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14829: }
14830:
1.350 brouard 14831: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 14832: }
14833: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14834: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14835: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14836:
1.225 brouard 14837: /*------------ free_vector -------------*/
14838: /* chdir(path); */
1.220 brouard 14839:
1.215 brouard 14840: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14841: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14842: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14843: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14844: free_lvector(num,firstobs,lastobs);
14845: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14846: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14847: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14848: fclose(ficparo);
14849: fclose(ficres);
1.220 brouard 14850:
14851:
1.186 brouard 14852: /* Other results (useful)*/
1.220 brouard 14853:
14854:
1.126 brouard 14855: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14856: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14857: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14858: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14859: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14860: fclose(ficrespl);
14861:
14862: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14863: /*#include "hpijx.h"*/
1.332 brouard 14864: /** 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?*/
14865: /* calls hpxij with combination k */
1.180 brouard 14866: hPijx(p, bage, fage);
1.145 brouard 14867: fclose(ficrespij);
1.227 brouard 14868:
1.220 brouard 14869: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14870: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14871: k=1;
1.126 brouard 14872: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14873:
1.269 brouard 14874: /* Prevalence for each covariate combination in probs[age][status][cov] */
14875: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14876: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14877: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14878: for(k=1;k<=ncovcombmax;k++)
14879: probs[i][j][k]=0.;
1.269 brouard 14880: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14881: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14882: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14883: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14884: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14885: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14886: for(k=1;k<=ncovcombmax;k++)
14887: mobaverages[i][j][k]=0.;
1.219 brouard 14888: mobaverage=mobaverages;
14889: if (mobilav!=0) {
1.235 brouard 14890: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14891: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14892: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14893: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14894: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14895: }
1.269 brouard 14896: } else if (mobilavproj !=0) {
1.235 brouard 14897: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14898: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14899: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14900: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14901: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14902: }
1.269 brouard 14903: }else{
14904: printf("Internal error moving average\n");
14905: fflush(stdout);
14906: exit(1);
1.219 brouard 14907: }
14908: }/* end if moving average */
1.227 brouard 14909:
1.126 brouard 14910: /*---------- Forecasting ------------------*/
1.296 brouard 14911: if(prevfcast==1){
14912: /* /\* if(stepm ==1){*\/ */
14913: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14914: /*This done previously after freqsummary.*/
14915: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14916: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14917:
14918: /* } else if (prvforecast==2){ */
14919: /* /\* if(stepm ==1){*\/ */
14920: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14921: /* } */
14922: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14923: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14924: }
1.269 brouard 14925:
1.296 brouard 14926: /* Prevbcasting */
14927: if(prevbcast==1){
1.219 brouard 14928: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14929: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14930: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14931:
14932: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14933:
14934: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14935:
1.219 brouard 14936: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14937: fclose(ficresplb);
14938:
1.222 brouard 14939: hBijx(p, bage, fage, mobaverage);
14940: fclose(ficrespijb);
1.219 brouard 14941:
1.296 brouard 14942: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14943: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14944: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14945: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14946: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14947: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14948:
14949:
1.269 brouard 14950: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14951:
14952:
1.269 brouard 14953: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14954: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14955: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14956: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14957: } /* end Prevbcasting */
1.268 brouard 14958:
1.186 brouard 14959:
14960: /* ------ Other prevalence ratios------------ */
1.126 brouard 14961:
1.215 brouard 14962: free_ivector(wav,1,imx);
14963: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14964: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14965: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14966:
14967:
1.127 brouard 14968: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14969:
1.201 brouard 14970: strcpy(filerese,"E_");
14971: strcat(filerese,fileresu);
1.126 brouard 14972: if((ficreseij=fopen(filerese,"w"))==NULL) {
14973: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14974: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14975: }
1.208 brouard 14976: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14977: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14978:
14979: pstamp(ficreseij);
1.219 brouard 14980:
1.351 brouard 14981: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
14982: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 14983:
1.351 brouard 14984: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
14985: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14986: /* if(i1 != 1 && TKresult[nres]!= k) */
14987: /* continue; */
1.219 brouard 14988: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14989: printf("\n#****** ");
1.351 brouard 14990: for(j=1;j<=cptcovs;j++){
14991: /* for(j=1;j<=cptcoveff;j++) { */
14992: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14993: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14994: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14995: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 14996: }
14997: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14998: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14999: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 15000: }
15001: fprintf(ficreseij,"******\n");
1.235 brouard 15002: printf("******\n");
1.219 brouard 15003:
15004: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15005: oldm=oldms;savm=savms;
1.330 brouard 15006: /* 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 15007: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 15008:
1.219 brouard 15009: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 15010: }
15011: fclose(ficreseij);
1.208 brouard 15012: printf("done evsij\n");fflush(stdout);
15013: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 15014:
1.218 brouard 15015:
1.227 brouard 15016: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 15017: /* Should be moved in a function */
1.201 brouard 15018: strcpy(filerest,"T_");
15019: strcat(filerest,fileresu);
1.127 brouard 15020: if((ficrest=fopen(filerest,"w"))==NULL) {
15021: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
15022: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
15023: }
1.208 brouard 15024: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
15025: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 15026: strcpy(fileresstde,"STDE_");
15027: strcat(fileresstde,fileresu);
1.126 brouard 15028: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 15029: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
15030: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 15031: }
1.227 brouard 15032: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
15033: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 15034:
1.201 brouard 15035: strcpy(filerescve,"CVE_");
15036: strcat(filerescve,fileresu);
1.126 brouard 15037: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 15038: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
15039: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 15040: }
1.227 brouard 15041: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
15042: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 15043:
1.201 brouard 15044: strcpy(fileresv,"V_");
15045: strcat(fileresv,fileresu);
1.126 brouard 15046: if((ficresvij=fopen(fileresv,"w"))==NULL) {
15047: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
15048: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
15049: }
1.227 brouard 15050: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
15051: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 15052:
1.235 brouard 15053: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
15054: if (cptcovn < 1){i1=1;}
15055:
1.334 brouard 15056: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
15057: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
15058: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
15059: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
15060: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
15061: /* */
15062: 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 15063: continue;
1.350 brouard 15064: printf("\n# model %s \n#****** Result for:", model); /* HERE model is empty */
1.321 brouard 15065: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
15066: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 15067: /* It might not be a good idea to mix dummies and quantitative */
15068: /* 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 *\/ */
15069: 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 */
15070: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
15071: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
15072: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
15073: * (V5 is quanti) V4 and V3 are dummies
15074: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
15075: * l=1 l=2
15076: * k=1 1 1 0 0
15077: * k=2 2 1 1 0
15078: * k=3 [1] [2] 0 1
15079: * k=4 2 2 1 1
15080: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
15081: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
15082: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
15083: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
15084: */
15085: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
15086: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
15087: /* We give up with the combinations!! */
1.342 brouard 15088: /* if(debugILK) */
15089: /* 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 15090:
15091: 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 15092: /* 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] */
15093: 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 */
15094: 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 */
15095: 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 15096: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15097: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15098: }else{
15099: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15100: }
15101: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15102: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15103: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15104: /* For each selected (single) quantitative value */
1.337 brouard 15105: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15106: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15107: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15108: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15109: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15110: }else{
15111: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15112: }
15113: }else{
15114: 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 */
15115: 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 */
15116: exit(1);
15117: }
1.335 brouard 15118: } /* End loop for each variable in the resultline */
1.334 brouard 15119: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15120: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15121: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15122: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15123: /* } */
1.208 brouard 15124: fprintf(ficrest,"******\n");
1.227 brouard 15125: fprintf(ficlog,"******\n");
15126: printf("******\n");
1.208 brouard 15127:
15128: fprintf(ficresstdeij,"\n#****** ");
15129: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15130: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15131: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15132: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15133: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15134: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15135: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15136: }
15137: 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 15138: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15139: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15140: }
1.208 brouard 15141: fprintf(ficresstdeij,"******\n");
15142: fprintf(ficrescveij,"******\n");
15143:
15144: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15145: /* pstamp(ficresvij); */
1.225 brouard 15146: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15147: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15148: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15149: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15150: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15151: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15152: }
1.208 brouard 15153: fprintf(ficresvij,"******\n");
15154:
15155: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15156: oldm=oldms;savm=savms;
1.235 brouard 15157: printf(" cvevsij ");
15158: fprintf(ficlog, " cvevsij ");
15159: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15160: printf(" end cvevsij \n ");
15161: fprintf(ficlog, " end cvevsij \n ");
15162:
15163: /*
15164: */
15165: /* goto endfree; */
15166:
15167: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15168: pstamp(ficrest);
15169:
1.269 brouard 15170: epj=vector(1,nlstate+1);
1.208 brouard 15171: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15172: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15173: cptcod= 0; /* To be deleted */
15174: printf("varevsij vpopbased=%d \n",vpopbased);
15175: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15176: 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 15177: 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 ");
15178: if(vpopbased==1)
15179: 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);
15180: else
1.288 brouard 15181: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15182: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15183: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15184: fprintf(ficrest,"\n");
15185: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15186: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15187: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15188: for(age=bage; age <=fage ;age++){
1.235 brouard 15189: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15190: if (vpopbased==1) {
15191: if(mobilav ==0){
15192: for(i=1; i<=nlstate;i++)
15193: prlim[i][i]=probs[(int)age][i][k];
15194: }else{ /* mobilav */
15195: for(i=1; i<=nlstate;i++)
15196: prlim[i][i]=mobaverage[(int)age][i][k];
15197: }
15198: }
1.219 brouard 15199:
1.227 brouard 15200: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15201: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15202: /* printf(" age %4.0f ",age); */
15203: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15204: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15205: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15206: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15207: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15208: }
15209: epj[nlstate+1] +=epj[j];
15210: }
15211: /* printf(" age %4.0f \n",age); */
1.219 brouard 15212:
1.227 brouard 15213: for(i=1, vepp=0.;i <=nlstate;i++)
15214: for(j=1;j <=nlstate;j++)
15215: vepp += vareij[i][j][(int)age];
15216: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15217: for(j=1;j <=nlstate;j++){
15218: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15219: }
15220: fprintf(ficrest,"\n");
15221: }
1.208 brouard 15222: } /* End vpopbased */
1.269 brouard 15223: free_vector(epj,1,nlstate+1);
1.208 brouard 15224: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15225: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15226: printf("done selection\n");fflush(stdout);
15227: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15228:
1.335 brouard 15229: } /* End k selection or end covariate selection for nres */
1.227 brouard 15230:
15231: printf("done State-specific expectancies\n");fflush(stdout);
15232: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15233:
1.335 brouard 15234: /* variance-covariance of forward period prevalence */
1.269 brouard 15235: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15236:
1.227 brouard 15237:
1.290 brouard 15238: free_vector(weight,firstobs,lastobs);
1.351 brouard 15239: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 15240: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15241: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15242: free_matrix(anint,1,maxwav,firstobs,lastobs);
15243: free_matrix(mint,1,maxwav,firstobs,lastobs);
15244: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15245: free_ivector(tab,1,NCOVMAX);
15246: fclose(ficresstdeij);
15247: fclose(ficrescveij);
15248: fclose(ficresvij);
15249: fclose(ficrest);
15250: fclose(ficpar);
15251:
15252:
1.126 brouard 15253: /*---------- End : free ----------------*/
1.219 brouard 15254: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15255: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15256: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15257: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15258: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15259: } /* mle==-3 arrives here for freeing */
1.227 brouard 15260: /* endfree:*/
15261: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15262: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15263: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15264: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15265: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15266: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15267: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15268: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15269: free_matrix(matcov,1,npar,1,npar);
15270: free_matrix(hess,1,npar,1,npar);
15271: /*free_vector(delti,1,npar);*/
15272: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15273: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15274: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15275: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15276:
15277: free_ivector(ncodemax,1,NCOVMAX);
15278: free_ivector(ncodemaxwundef,1,NCOVMAX);
15279: free_ivector(Dummy,-1,NCOVMAX);
15280: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 15281: free_ivector(DummyV,-1,NCOVMAX);
15282: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15283: free_ivector(Typevar,-1,NCOVMAX);
15284: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15285: free_ivector(TvarsQ,1,NCOVMAX);
15286: free_ivector(TvarsQind,1,NCOVMAX);
15287: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15288: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15289: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15290: free_ivector(TvarFD,1,NCOVMAX);
15291: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15292: free_ivector(TvarF,1,NCOVMAX);
15293: free_ivector(TvarFind,1,NCOVMAX);
15294: free_ivector(TvarV,1,NCOVMAX);
15295: free_ivector(TvarVind,1,NCOVMAX);
15296: free_ivector(TvarA,1,NCOVMAX);
15297: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15298: free_ivector(TvarFQ,1,NCOVMAX);
15299: free_ivector(TvarFQind,1,NCOVMAX);
15300: free_ivector(TvarVD,1,NCOVMAX);
15301: free_ivector(TvarVDind,1,NCOVMAX);
15302: free_ivector(TvarVQ,1,NCOVMAX);
15303: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 15304: free_ivector(TvarAVVA,1,NCOVMAX);
15305: free_ivector(TvarAVVAind,1,NCOVMAX);
15306: free_ivector(TvarVVA,1,NCOVMAX);
15307: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15308: free_ivector(TvarVV,1,NCOVMAX);
15309: free_ivector(TvarVVind,1,NCOVMAX);
15310:
1.230 brouard 15311: free_ivector(Tvarsel,1,NCOVMAX);
15312: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15313: free_ivector(Tposprod,1,NCOVMAX);
15314: free_ivector(Tprod,1,NCOVMAX);
15315: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15316: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15317: free_ivector(Tage,1,NCOVMAX);
15318: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15319: free_ivector(TmodelInvind,1,NCOVMAX);
15320: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15321:
15322: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15323:
1.227 brouard 15324: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15325: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15326: fflush(fichtm);
15327: fflush(ficgp);
15328:
1.227 brouard 15329:
1.126 brouard 15330: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15331: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15332: 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 15333: }else{
15334: printf("End of Imach\n");
15335: fprintf(ficlog,"End of Imach\n");
15336: }
15337: printf("See log file on %s\n",filelog);
15338: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15339: /*(void) gettimeofday(&end_time,&tzp);*/
15340: rend_time = time(NULL);
15341: end_time = *localtime(&rend_time);
15342: /* tml = *localtime(&end_time.tm_sec); */
15343: strcpy(strtend,asctime(&end_time));
1.126 brouard 15344: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15345: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15346: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15347:
1.157 brouard 15348: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15349: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15350: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15351: /* printf("Total time was %d uSec.\n", total_usecs);*/
15352: /* if(fileappend(fichtm,optionfilehtm)){ */
15353: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15354: fclose(fichtm);
15355: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15356: fclose(fichtmcov);
15357: fclose(ficgp);
15358: fclose(ficlog);
15359: /*------ End -----------*/
1.227 brouard 15360:
1.281 brouard 15361:
15362: /* Executes gnuplot */
1.227 brouard 15363:
15364: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15365: #ifdef WIN32
1.227 brouard 15366: if (_chdir(pathcd) != 0)
15367: printf("Can't move to directory %s!\n",path);
15368: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15369: #else
1.227 brouard 15370: if(chdir(pathcd) != 0)
15371: printf("Can't move to directory %s!\n", path);
15372: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15373: #endif
1.126 brouard 15374: printf("Current directory %s!\n",pathcd);
15375: /*strcat(plotcmd,CHARSEPARATOR);*/
15376: sprintf(plotcmd,"gnuplot");
1.157 brouard 15377: #ifdef _WIN32
1.126 brouard 15378: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15379: #endif
15380: if(!stat(plotcmd,&info)){
1.158 brouard 15381: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15382: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15383: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15384: }else
15385: strcpy(pplotcmd,plotcmd);
1.157 brouard 15386: #ifdef __unix
1.126 brouard 15387: strcpy(plotcmd,GNUPLOTPROGRAM);
15388: if(!stat(plotcmd,&info)){
1.158 brouard 15389: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15390: }else
15391: strcpy(pplotcmd,plotcmd);
15392: #endif
15393: }else
15394: strcpy(pplotcmd,plotcmd);
15395:
15396: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15397: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15398: strcpy(pplotcmd,plotcmd);
1.227 brouard 15399:
1.126 brouard 15400: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15401: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15402: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15403: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15404: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15405: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15406: strcpy(plotcmd,pplotcmd);
15407: }
1.126 brouard 15408: }
1.158 brouard 15409: printf(" Successful, please wait...");
1.126 brouard 15410: while (z[0] != 'q') {
15411: /* chdir(path); */
1.154 brouard 15412: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15413: scanf("%s",z);
15414: /* if (z[0] == 'c') system("./imach"); */
15415: if (z[0] == 'e') {
1.158 brouard 15416: #ifdef __APPLE__
1.152 brouard 15417: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15418: #elif __linux
15419: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15420: #else
1.152 brouard 15421: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15422: #endif
15423: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15424: system(pplotcmd);
1.126 brouard 15425: }
15426: else if (z[0] == 'g') system(plotcmd);
15427: else if (z[0] == 'q') exit(0);
15428: }
1.227 brouard 15429: end:
1.126 brouard 15430: while (z[0] != 'q') {
1.195 brouard 15431: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15432: scanf("%s",z);
15433: }
1.283 brouard 15434: printf("End\n");
1.282 brouard 15435: exit(0);
1.126 brouard 15436: }
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