Annotation of imach/src/imach.c, revision 1.355
1.355 ! brouard 1: /* $Id: imach.c,v 1.354 2023/05/21 05:05:17 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.355 ! brouard 4: Revision 1.354 2023/05/21 05:05:17 brouard
! 5: Summary: Temporary change for imachprax
! 6:
1.354 brouard 7: Revision 1.353 2023/05/08 18:48:22 brouard
8: *** empty log message ***
9:
1.353 brouard 10: Revision 1.352 2023/04/29 10:46:21 brouard
11: *** empty log message ***
12:
1.352 brouard 13: Revision 1.351 2023/04/29 10:43:47 brouard
14: Summary: 099r45
15:
1.351 brouard 16: Revision 1.350 2023/04/24 11:38:06 brouard
17: *** empty log message ***
18:
1.350 brouard 19: Revision 1.349 2023/01/31 09:19:37 brouard
20: Summary: Improvements in models with age*Vn*Vm
21:
1.348 brouard 22: Revision 1.347 2022/09/18 14:36:44 brouard
23: Summary: version 0.99r42
24:
1.347 brouard 25: Revision 1.346 2022/09/16 13:52:36 brouard
26: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
27:
1.346 brouard 28: Revision 1.345 2022/09/16 13:40:11 brouard
29: Summary: Version 0.99r41
30:
31: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
32:
1.345 brouard 33: Revision 1.344 2022/09/14 19:33:30 brouard
34: Summary: version 0.99r40
35:
36: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
37:
1.344 brouard 38: Revision 1.343 2022/09/14 14:22:16 brouard
39: Summary: version 0.99r39
40:
41: * imach.c (Module): Version 0.99r39 with colored dummy covariates
42: (fixed or time varying), using new last columns of
43: ILK_parameter.txt file.
44:
1.343 brouard 45: Revision 1.342 2022/09/11 19:54:09 brouard
46: Summary: 0.99r38
47:
48: * imach.c (Module): Adding timevarying products of any kinds,
49: should work before shifting cotvar from ncovcol+nqv columns in
50: order to have a correspondance between the column of cotvar and
51: the id of column.
52: (Module): Some cleaning and adding covariates in ILK.txt
53:
1.342 brouard 54: Revision 1.341 2022/09/11 07:58:42 brouard
55: Summary: Version 0.99r38
56:
57: After adding change in cotvar.
58:
1.341 brouard 59: Revision 1.340 2022/09/11 07:53:11 brouard
60: Summary: Version imach 0.99r37
61:
62: * imach.c (Module): Adding timevarying products of any kinds,
63: should work before shifting cotvar from ncovcol+nqv columns in
64: order to have a correspondance between the column of cotvar and
65: the id of column.
66:
1.340 brouard 67: Revision 1.339 2022/09/09 17:55:22 brouard
68: Summary: version 0.99r37
69:
70: * imach.c (Module): Many improvements for fixing products of fixed
71: timevarying as well as fixed * fixed, and test with quantitative
72: covariate.
73:
1.339 brouard 74: Revision 1.338 2022/09/04 17:40:33 brouard
75: Summary: 0.99r36
76:
77: * imach.c (Module): Now the easy runs i.e. without result or
78: model=1+age only did not work. The defautl combination should be 1
79: and not 0 because everything hasn't been tranformed yet.
80:
1.338 brouard 81: Revision 1.337 2022/09/02 14:26:02 brouard
82: Summary: version 0.99r35
83:
84: * src/imach.c: Version 0.99r35 because it outputs same results with
85: 1+age+V1+V1*age for females and 1+age for females only
86: (education=1 noweight)
87:
1.337 brouard 88: Revision 1.336 2022/08/31 09:52:36 brouard
89: *** empty log message ***
90:
1.336 brouard 91: Revision 1.335 2022/08/31 08:23:16 brouard
92: Summary: improvements...
93:
1.335 brouard 94: Revision 1.334 2022/08/25 09:08:41 brouard
95: Summary: In progress for quantitative
96:
1.334 brouard 97: Revision 1.333 2022/08/21 09:10:30 brouard
98: * src/imach.c (Module): Version 0.99r33 A lot of changes in
99: reassigning covariates: my first idea was that people will always
100: use the first covariate V1 into the model but in fact they are
101: producing data with many covariates and can use an equation model
102: with some of the covariate; it means that in a model V2+V3 instead
103: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
104: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
105: the equation model is restricted to two variables only (V2, V3)
106: and the combination for V2 should be codtabm(k,1) instead of
107: (codtabm(k,2), and the code should be
108: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
109: made. All of these should be simplified once a day like we did in
110: hpxij() for example by using precov[nres] which is computed in
111: decoderesult for each nres of each resultline. Loop should be done
112: on the equation model globally by distinguishing only product with
113: age (which are changing with age) and no more on type of
114: covariates, single dummies, single covariates.
115:
1.333 brouard 116: Revision 1.332 2022/08/21 09:06:25 brouard
117: Summary: Version 0.99r33
118:
119: * src/imach.c (Module): Version 0.99r33 A lot of changes in
120: reassigning covariates: my first idea was that people will always
121: use the first covariate V1 into the model but in fact they are
122: producing data with many covariates and can use an equation model
123: with some of the covariate; it means that in a model V2+V3 instead
124: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
125: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
126: the equation model is restricted to two variables only (V2, V3)
127: and the combination for V2 should be codtabm(k,1) instead of
128: (codtabm(k,2), and the code should be
129: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
130: made. All of these should be simplified once a day like we did in
131: hpxij() for example by using precov[nres] which is computed in
132: decoderesult for each nres of each resultline. Loop should be done
133: on the equation model globally by distinguishing only product with
134: age (which are changing with age) and no more on type of
135: covariates, single dummies, single covariates.
136:
1.332 brouard 137: Revision 1.331 2022/08/07 05:40:09 brouard
138: *** empty log message ***
139:
1.331 brouard 140: Revision 1.330 2022/08/06 07:18:25 brouard
141: Summary: last 0.99r31
142:
143: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
144:
1.330 brouard 145: Revision 1.329 2022/08/03 17:29:54 brouard
146: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
147:
1.329 brouard 148: Revision 1.328 2022/07/27 17:40:48 brouard
149: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
150:
1.328 brouard 151: Revision 1.327 2022/07/27 14:47:35 brouard
152: Summary: Still a problem for one-step probabilities in case of quantitative variables
153:
1.327 brouard 154: Revision 1.326 2022/07/26 17:33:55 brouard
155: Summary: some test with nres=1
156:
1.326 brouard 157: Revision 1.325 2022/07/25 14:27:23 brouard
158: Summary: r30
159:
160: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
161: coredumped, revealed by Feiuno, thank you.
162:
1.325 brouard 163: Revision 1.324 2022/07/23 17:44:26 brouard
164: *** empty log message ***
165:
1.324 brouard 166: Revision 1.323 2022/07/22 12:30:08 brouard
167: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
168:
1.323 brouard 169: Revision 1.322 2022/07/22 12:27:48 brouard
170: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
171:
1.322 brouard 172: Revision 1.321 2022/07/22 12:04:24 brouard
173: Summary: r28
174:
175: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
176:
1.321 brouard 177: Revision 1.320 2022/06/02 05:10:11 brouard
178: *** empty log message ***
179:
1.320 brouard 180: Revision 1.319 2022/06/02 04:45:11 brouard
181: * imach.c (Module): Adding the Wald tests from the log to the main
182: htm for better display of the maximum likelihood estimators.
183:
1.319 brouard 184: Revision 1.318 2022/05/24 08:10:59 brouard
185: * imach.c (Module): Some attempts to find a bug of wrong estimates
186: of confidencce intervals with product in the equation modelC
187:
1.318 brouard 188: Revision 1.317 2022/05/15 15:06:23 brouard
189: * imach.c (Module): Some minor improvements
190:
1.317 brouard 191: Revision 1.316 2022/05/11 15:11:31 brouard
192: Summary: r27
193:
1.316 brouard 194: Revision 1.315 2022/05/11 15:06:32 brouard
195: *** empty log message ***
196:
1.315 brouard 197: Revision 1.314 2022/04/13 17:43:09 brouard
198: * imach.c (Module): Adding link to text data files
199:
1.314 brouard 200: Revision 1.313 2022/04/11 15:57:42 brouard
201: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
202:
1.313 brouard 203: Revision 1.312 2022/04/05 21:24:39 brouard
204: *** empty log message ***
205:
1.312 brouard 206: Revision 1.311 2022/04/05 21:03:51 brouard
207: Summary: Fixed quantitative covariates
208:
209: Fixed covariates (dummy or quantitative)
210: with missing values have never been allowed but are ERRORS and
211: program quits. Standard deviations of fixed covariates were
212: wrongly computed. Mean and standard deviations of time varying
213: covariates are still not computed.
214:
1.311 brouard 215: Revision 1.310 2022/03/17 08:45:53 brouard
216: Summary: 99r25
217:
218: Improving detection of errors: result lines should be compatible with
219: the model.
220:
1.310 brouard 221: Revision 1.309 2021/05/20 12:39:14 brouard
222: Summary: Version 0.99r24
223:
1.309 brouard 224: Revision 1.308 2021/03/31 13:11:57 brouard
225: Summary: Version 0.99r23
226:
227:
228: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
229:
1.308 brouard 230: Revision 1.307 2021/03/08 18:11:32 brouard
231: Summary: 0.99r22 fixed bug on result:
232:
1.307 brouard 233: Revision 1.306 2021/02/20 15:44:02 brouard
234: Summary: Version 0.99r21
235:
236: * imach.c (Module): Fix bug on quitting after result lines!
237: (Module): Version 0.99r21
238:
1.306 brouard 239: Revision 1.305 2021/02/20 15:28:30 brouard
240: * imach.c (Module): Fix bug on quitting after result lines!
241:
1.305 brouard 242: Revision 1.304 2021/02/12 11:34:20 brouard
243: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
244:
1.304 brouard 245: Revision 1.303 2021/02/11 19:50:15 brouard
246: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
247:
1.303 brouard 248: Revision 1.302 2020/02/22 21:00:05 brouard
249: * (Module): imach.c Update mle=-3 (for computing Life expectancy
250: and life table from the data without any state)
251:
1.302 brouard 252: Revision 1.301 2019/06/04 13:51:20 brouard
253: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
254:
1.301 brouard 255: Revision 1.300 2019/05/22 19:09:45 brouard
256: Summary: version 0.99r19 of May 2019
257:
1.300 brouard 258: Revision 1.299 2019/05/22 18:37:08 brouard
259: Summary: Cleaned 0.99r19
260:
1.299 brouard 261: Revision 1.298 2019/05/22 18:19:56 brouard
262: *** empty log message ***
263:
1.298 brouard 264: Revision 1.297 2019/05/22 17:56:10 brouard
265: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
266:
1.297 brouard 267: Revision 1.296 2019/05/20 13:03:18 brouard
268: Summary: Projection syntax simplified
269:
270:
271: We can now start projections, forward or backward, from the mean date
272: of inteviews up to or down to a number of years of projection:
273: prevforecast=1 yearsfproj=15.3 mobil_average=0
274: or
275: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
276: or
277: prevbackcast=1 yearsbproj=12.3 mobil_average=1
278: or
279: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
280:
1.296 brouard 281: Revision 1.295 2019/05/18 09:52:50 brouard
282: Summary: doxygen tex bug
283:
1.295 brouard 284: Revision 1.294 2019/05/16 14:54:33 brouard
285: Summary: There was some wrong lines added
286:
1.294 brouard 287: Revision 1.293 2019/05/09 15:17:34 brouard
288: *** empty log message ***
289:
1.293 brouard 290: Revision 1.292 2019/05/09 14:17:20 brouard
291: Summary: Some updates
292:
1.292 brouard 293: Revision 1.291 2019/05/09 13:44:18 brouard
294: Summary: Before ncovmax
295:
1.291 brouard 296: Revision 1.290 2019/05/09 13:39:37 brouard
297: Summary: 0.99r18 unlimited number of individuals
298:
299: 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.
300:
1.290 brouard 301: Revision 1.289 2018/12/13 09:16:26 brouard
302: Summary: Bug for young ages (<-30) will be in r17
303:
1.289 brouard 304: Revision 1.288 2018/05/02 20:58:27 brouard
305: Summary: Some bugs fixed
306:
1.288 brouard 307: Revision 1.287 2018/05/01 17:57:25 brouard
308: Summary: Bug fixed by providing frequencies only for non missing covariates
309:
1.287 brouard 310: Revision 1.286 2018/04/27 14:27:04 brouard
311: Summary: some minor bugs
312:
1.286 brouard 313: Revision 1.285 2018/04/21 21:02:16 brouard
314: Summary: Some bugs fixed, valgrind tested
315:
1.285 brouard 316: Revision 1.284 2018/04/20 05:22:13 brouard
317: Summary: Computing mean and stdeviation of fixed quantitative variables
318:
1.284 brouard 319: Revision 1.283 2018/04/19 14:49:16 brouard
320: Summary: Some minor bugs fixed
321:
1.283 brouard 322: Revision 1.282 2018/02/27 22:50:02 brouard
323: *** empty log message ***
324:
1.282 brouard 325: Revision 1.281 2018/02/27 19:25:23 brouard
326: Summary: Adding second argument for quitting
327:
1.281 brouard 328: Revision 1.280 2018/02/21 07:58:13 brouard
329: Summary: 0.99r15
330:
331: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
332:
1.280 brouard 333: Revision 1.279 2017/07/20 13:35:01 brouard
334: Summary: temporary working
335:
1.279 brouard 336: Revision 1.278 2017/07/19 14:09:02 brouard
337: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
338:
1.278 brouard 339: Revision 1.277 2017/07/17 08:53:49 brouard
340: Summary: BOM files can be read now
341:
1.277 brouard 342: Revision 1.276 2017/06/30 15:48:31 brouard
343: Summary: Graphs improvements
344:
1.276 brouard 345: Revision 1.275 2017/06/30 13:39:33 brouard
346: Summary: Saito's color
347:
1.275 brouard 348: Revision 1.274 2017/06/29 09:47:08 brouard
349: Summary: Version 0.99r14
350:
1.274 brouard 351: Revision 1.273 2017/06/27 11:06:02 brouard
352: Summary: More documentation on projections
353:
1.273 brouard 354: Revision 1.272 2017/06/27 10:22:40 brouard
355: Summary: Color of backprojection changed from 6 to 5(yellow)
356:
1.272 brouard 357: Revision 1.271 2017/06/27 10:17:50 brouard
358: Summary: Some bug with rint
359:
1.271 brouard 360: Revision 1.270 2017/05/24 05:45:29 brouard
361: *** empty log message ***
362:
1.270 brouard 363: Revision 1.269 2017/05/23 08:39:25 brouard
364: Summary: Code into subroutine, cleanings
365:
1.269 brouard 366: Revision 1.268 2017/05/18 20:09:32 brouard
367: Summary: backprojection and confidence intervals of backprevalence
368:
1.268 brouard 369: Revision 1.267 2017/05/13 10:25:05 brouard
370: Summary: temporary save for backprojection
371:
1.267 brouard 372: Revision 1.266 2017/05/13 07:26:12 brouard
373: Summary: Version 0.99r13 (improvements and bugs fixed)
374:
1.266 brouard 375: Revision 1.265 2017/04/26 16:22:11 brouard
376: Summary: imach 0.99r13 Some bugs fixed
377:
1.265 brouard 378: Revision 1.264 2017/04/26 06:01:29 brouard
379: Summary: Labels in graphs
380:
1.264 brouard 381: Revision 1.263 2017/04/24 15:23:15 brouard
382: Summary: to save
383:
1.263 brouard 384: Revision 1.262 2017/04/18 16:48:12 brouard
385: *** empty log message ***
386:
1.262 brouard 387: Revision 1.261 2017/04/05 10:14:09 brouard
388: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
389:
1.261 brouard 390: Revision 1.260 2017/04/04 17:46:59 brouard
391: Summary: Gnuplot indexations fixed (humm)
392:
1.260 brouard 393: Revision 1.259 2017/04/04 13:01:16 brouard
394: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
395:
1.259 brouard 396: Revision 1.258 2017/04/03 10:17:47 brouard
397: Summary: Version 0.99r12
398:
399: Some cleanings, conformed with updated documentation.
400:
1.258 brouard 401: Revision 1.257 2017/03/29 16:53:30 brouard
402: Summary: Temp
403:
1.257 brouard 404: Revision 1.256 2017/03/27 05:50:23 brouard
405: Summary: Temporary
406:
1.256 brouard 407: Revision 1.255 2017/03/08 16:02:28 brouard
408: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
409:
1.255 brouard 410: Revision 1.254 2017/03/08 07:13:00 brouard
411: Summary: Fixing data parameter line
412:
1.254 brouard 413: Revision 1.253 2016/12/15 11:59:41 brouard
414: Summary: 0.99 in progress
415:
1.253 brouard 416: Revision 1.252 2016/09/15 21:15:37 brouard
417: *** empty log message ***
418:
1.252 brouard 419: Revision 1.251 2016/09/15 15:01:13 brouard
420: Summary: not working
421:
1.251 brouard 422: Revision 1.250 2016/09/08 16:07:27 brouard
423: Summary: continue
424:
1.250 brouard 425: Revision 1.249 2016/09/07 17:14:18 brouard
426: Summary: Starting values from frequencies
427:
1.249 brouard 428: Revision 1.248 2016/09/07 14:10:18 brouard
429: *** empty log message ***
430:
1.248 brouard 431: Revision 1.247 2016/09/02 11:11:21 brouard
432: *** empty log message ***
433:
1.247 brouard 434: Revision 1.246 2016/09/02 08:49:22 brouard
435: *** empty log message ***
436:
1.246 brouard 437: Revision 1.245 2016/09/02 07:25:01 brouard
438: *** empty log message ***
439:
1.245 brouard 440: Revision 1.244 2016/09/02 07:17:34 brouard
441: *** empty log message ***
442:
1.244 brouard 443: Revision 1.243 2016/09/02 06:45:35 brouard
444: *** empty log message ***
445:
1.243 brouard 446: Revision 1.242 2016/08/30 15:01:20 brouard
447: Summary: Fixing a lots
448:
1.242 brouard 449: Revision 1.241 2016/08/29 17:17:25 brouard
450: Summary: gnuplot problem in Back projection to fix
451:
1.241 brouard 452: Revision 1.240 2016/08/29 07:53:18 brouard
453: Summary: Better
454:
1.240 brouard 455: Revision 1.239 2016/08/26 15:51:03 brouard
456: Summary: Improvement in Powell output in order to copy and paste
457:
458: Author:
459:
1.239 brouard 460: Revision 1.238 2016/08/26 14:23:35 brouard
461: Summary: Starting tests of 0.99
462:
1.238 brouard 463: Revision 1.237 2016/08/26 09:20:19 brouard
464: Summary: to valgrind
465:
1.237 brouard 466: Revision 1.236 2016/08/25 10:50:18 brouard
467: *** empty log message ***
468:
1.236 brouard 469: Revision 1.235 2016/08/25 06:59:23 brouard
470: *** empty log message ***
471:
1.235 brouard 472: Revision 1.234 2016/08/23 16:51:20 brouard
473: *** empty log message ***
474:
1.234 brouard 475: Revision 1.233 2016/08/23 07:40:50 brouard
476: Summary: not working
477:
1.233 brouard 478: Revision 1.232 2016/08/22 14:20:21 brouard
479: Summary: not working
480:
1.232 brouard 481: Revision 1.231 2016/08/22 07:17:15 brouard
482: Summary: not working
483:
1.231 brouard 484: Revision 1.230 2016/08/22 06:55:53 brouard
485: Summary: Not working
486:
1.230 brouard 487: Revision 1.229 2016/07/23 09:45:53 brouard
488: Summary: Completing for func too
489:
1.229 brouard 490: Revision 1.228 2016/07/22 17:45:30 brouard
491: Summary: Fixing some arrays, still debugging
492:
1.227 brouard 493: Revision 1.226 2016/07/12 18:42:34 brouard
494: Summary: temp
495:
1.226 brouard 496: Revision 1.225 2016/07/12 08:40:03 brouard
497: Summary: saving but not running
498:
1.225 brouard 499: Revision 1.224 2016/07/01 13:16:01 brouard
500: Summary: Fixes
501:
1.224 brouard 502: Revision 1.223 2016/02/19 09:23:35 brouard
503: Summary: temporary
504:
1.223 brouard 505: Revision 1.222 2016/02/17 08:14:50 brouard
506: Summary: Probably last 0.98 stable version 0.98r6
507:
1.222 brouard 508: Revision 1.221 2016/02/15 23:35:36 brouard
509: Summary: minor bug
510:
1.220 brouard 511: Revision 1.219 2016/02/15 00:48:12 brouard
512: *** empty log message ***
513:
1.219 brouard 514: Revision 1.218 2016/02/12 11:29:23 brouard
515: Summary: 0.99 Back projections
516:
1.218 brouard 517: Revision 1.217 2015/12/23 17:18:31 brouard
518: Summary: Experimental backcast
519:
1.217 brouard 520: Revision 1.216 2015/12/18 17:32:11 brouard
521: Summary: 0.98r4 Warning and status=-2
522:
523: Version 0.98r4 is now:
524: - displaying an error when status is -1, date of interview unknown and date of death known;
525: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
526: Older changes concerning s=-2, dating from 2005 have been supersed.
527:
1.216 brouard 528: Revision 1.215 2015/12/16 08:52:24 brouard
529: Summary: 0.98r4 working
530:
1.215 brouard 531: Revision 1.214 2015/12/16 06:57:54 brouard
532: Summary: temporary not working
533:
1.214 brouard 534: Revision 1.213 2015/12/11 18:22:17 brouard
535: Summary: 0.98r4
536:
1.213 brouard 537: Revision 1.212 2015/11/21 12:47:24 brouard
538: Summary: minor typo
539:
1.212 brouard 540: Revision 1.211 2015/11/21 12:41:11 brouard
541: Summary: 0.98r3 with some graph of projected cross-sectional
542:
543: Author: Nicolas Brouard
544:
1.211 brouard 545: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 546: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 547: Summary: Adding ftolpl parameter
548: Author: N Brouard
549:
550: We had difficulties to get smoothed confidence intervals. It was due
551: to the period prevalence which wasn't computed accurately. The inner
552: parameter ftolpl is now an outer parameter of the .imach parameter
553: file after estepm. If ftolpl is small 1.e-4 and estepm too,
554: computation are long.
555:
1.209 brouard 556: Revision 1.208 2015/11/17 14:31:57 brouard
557: Summary: temporary
558:
1.208 brouard 559: Revision 1.207 2015/10/27 17:36:57 brouard
560: *** empty log message ***
561:
1.207 brouard 562: Revision 1.206 2015/10/24 07:14:11 brouard
563: *** empty log message ***
564:
1.206 brouard 565: Revision 1.205 2015/10/23 15:50:53 brouard
566: Summary: 0.98r3 some clarification for graphs on likelihood contributions
567:
1.205 brouard 568: Revision 1.204 2015/10/01 16:20:26 brouard
569: Summary: Some new graphs of contribution to likelihood
570:
1.204 brouard 571: Revision 1.203 2015/09/30 17:45:14 brouard
572: Summary: looking at better estimation of the hessian
573:
574: Also a better criteria for convergence to the period prevalence And
575: therefore adding the number of years needed to converge. (The
576: prevalence in any alive state shold sum to one
577:
1.203 brouard 578: Revision 1.202 2015/09/22 19:45:16 brouard
579: Summary: Adding some overall graph on contribution to likelihood. Might change
580:
1.202 brouard 581: Revision 1.201 2015/09/15 17:34:58 brouard
582: Summary: 0.98r0
583:
584: - Some new graphs like suvival functions
585: - Some bugs fixed like model=1+age+V2.
586:
1.201 brouard 587: Revision 1.200 2015/09/09 16:53:55 brouard
588: Summary: Big bug thanks to Flavia
589:
590: Even model=1+age+V2. did not work anymore
591:
1.200 brouard 592: Revision 1.199 2015/09/07 14:09:23 brouard
593: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
594:
1.199 brouard 595: Revision 1.198 2015/09/03 07:14:39 brouard
596: Summary: 0.98q5 Flavia
597:
1.198 brouard 598: Revision 1.197 2015/09/01 18:24:39 brouard
599: *** empty log message ***
600:
1.197 brouard 601: Revision 1.196 2015/08/18 23:17:52 brouard
602: Summary: 0.98q5
603:
1.196 brouard 604: Revision 1.195 2015/08/18 16:28:39 brouard
605: Summary: Adding a hack for testing purpose
606:
607: After reading the title, ftol and model lines, if the comment line has
608: a q, starting with #q, the answer at the end of the run is quit. It
609: permits to run test files in batch with ctest. The former workaround was
610: $ echo q | imach foo.imach
611:
1.195 brouard 612: Revision 1.194 2015/08/18 13:32:00 brouard
613: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
614:
1.194 brouard 615: Revision 1.193 2015/08/04 07:17:42 brouard
616: Summary: 0.98q4
617:
1.193 brouard 618: Revision 1.192 2015/07/16 16:49:02 brouard
619: Summary: Fixing some outputs
620:
1.192 brouard 621: Revision 1.191 2015/07/14 10:00:33 brouard
622: Summary: Some fixes
623:
1.191 brouard 624: Revision 1.190 2015/05/05 08:51:13 brouard
625: Summary: Adding digits in output parameters (7 digits instead of 6)
626:
627: Fix 1+age+.
628:
1.190 brouard 629: Revision 1.189 2015/04/30 14:45:16 brouard
630: Summary: 0.98q2
631:
1.189 brouard 632: Revision 1.188 2015/04/30 08:27:53 brouard
633: *** empty log message ***
634:
1.188 brouard 635: Revision 1.187 2015/04/29 09:11:15 brouard
636: *** empty log message ***
637:
1.187 brouard 638: Revision 1.186 2015/04/23 12:01:52 brouard
639: Summary: V1*age is working now, version 0.98q1
640:
641: Some codes had been disabled in order to simplify and Vn*age was
642: working in the optimization phase, ie, giving correct MLE parameters,
643: but, as usual, outputs were not correct and program core dumped.
644:
1.186 brouard 645: Revision 1.185 2015/03/11 13:26:42 brouard
646: Summary: Inclusion of compile and links command line for Intel Compiler
647:
1.185 brouard 648: Revision 1.184 2015/03/11 11:52:39 brouard
649: Summary: Back from Windows 8. Intel Compiler
650:
1.184 brouard 651: Revision 1.183 2015/03/10 20:34:32 brouard
652: Summary: 0.98q0, trying with directest, mnbrak fixed
653:
654: We use directest instead of original Powell test; probably no
655: incidence on the results, but better justifications;
656: We fixed Numerical Recipes mnbrak routine which was wrong and gave
657: wrong results.
658:
1.183 brouard 659: Revision 1.182 2015/02/12 08:19:57 brouard
660: Summary: Trying to keep directest which seems simpler and more general
661: Author: Nicolas Brouard
662:
1.182 brouard 663: Revision 1.181 2015/02/11 23:22:24 brouard
664: Summary: Comments on Powell added
665:
666: Author:
667:
1.181 brouard 668: Revision 1.180 2015/02/11 17:33:45 brouard
669: Summary: Finishing move from main to function (hpijx and prevalence_limit)
670:
1.180 brouard 671: Revision 1.179 2015/01/04 09:57:06 brouard
672: Summary: back to OS/X
673:
1.179 brouard 674: Revision 1.178 2015/01/04 09:35:48 brouard
675: *** empty log message ***
676:
1.178 brouard 677: Revision 1.177 2015/01/03 18:40:56 brouard
678: Summary: Still testing ilc32 on OSX
679:
1.177 brouard 680: Revision 1.176 2015/01/03 16:45:04 brouard
681: *** empty log message ***
682:
1.176 brouard 683: Revision 1.175 2015/01/03 16:33:42 brouard
684: *** empty log message ***
685:
1.175 brouard 686: Revision 1.174 2015/01/03 16:15:49 brouard
687: Summary: Still in cross-compilation
688:
1.174 brouard 689: Revision 1.173 2015/01/03 12:06:26 brouard
690: Summary: trying to detect cross-compilation
691:
1.173 brouard 692: Revision 1.172 2014/12/27 12:07:47 brouard
693: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
694:
1.172 brouard 695: Revision 1.171 2014/12/23 13:26:59 brouard
696: Summary: Back from Visual C
697:
698: Still problem with utsname.h on Windows
699:
1.171 brouard 700: Revision 1.170 2014/12/23 11:17:12 brouard
701: Summary: Cleaning some \%% back to %%
702:
703: The escape was mandatory for a specific compiler (which one?), but too many warnings.
704:
1.170 brouard 705: Revision 1.169 2014/12/22 23:08:31 brouard
706: Summary: 0.98p
707:
708: Outputs some informations on compiler used, OS etc. Testing on different platforms.
709:
1.169 brouard 710: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 711: Summary: update
1.169 brouard 712:
1.168 brouard 713: Revision 1.167 2014/12/22 13:50:56 brouard
714: Summary: Testing uname and compiler version and if compiled 32 or 64
715:
716: Testing on Linux 64
717:
1.167 brouard 718: Revision 1.166 2014/12/22 11:40:47 brouard
719: *** empty log message ***
720:
1.166 brouard 721: Revision 1.165 2014/12/16 11:20:36 brouard
722: Summary: After compiling on Visual C
723:
724: * imach.c (Module): Merging 1.61 to 1.162
725:
1.165 brouard 726: Revision 1.164 2014/12/16 10:52:11 brouard
727: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
728:
729: * imach.c (Module): Merging 1.61 to 1.162
730:
1.164 brouard 731: Revision 1.163 2014/12/16 10:30:11 brouard
732: * imach.c (Module): Merging 1.61 to 1.162
733:
1.163 brouard 734: Revision 1.162 2014/09/25 11:43:39 brouard
735: Summary: temporary backup 0.99!
736:
1.162 brouard 737: Revision 1.1 2014/09/16 11:06:58 brouard
738: Summary: With some code (wrong) for nlopt
739:
740: Author:
741:
742: Revision 1.161 2014/09/15 20:41:41 brouard
743: Summary: Problem with macro SQR on Intel compiler
744:
1.161 brouard 745: Revision 1.160 2014/09/02 09:24:05 brouard
746: *** empty log message ***
747:
1.160 brouard 748: Revision 1.159 2014/09/01 10:34:10 brouard
749: Summary: WIN32
750: Author: Brouard
751:
1.159 brouard 752: Revision 1.158 2014/08/27 17:11:51 brouard
753: *** empty log message ***
754:
1.158 brouard 755: Revision 1.157 2014/08/27 16:26:55 brouard
756: Summary: Preparing windows Visual studio version
757: Author: Brouard
758:
759: In order to compile on Visual studio, time.h is now correct and time_t
760: and tm struct should be used. difftime should be used but sometimes I
761: just make the differences in raw time format (time(&now).
762: Trying to suppress #ifdef LINUX
763: Add xdg-open for __linux in order to open default browser.
764:
1.157 brouard 765: Revision 1.156 2014/08/25 20:10:10 brouard
766: *** empty log message ***
767:
1.156 brouard 768: Revision 1.155 2014/08/25 18:32:34 brouard
769: Summary: New compile, minor changes
770: Author: Brouard
771:
1.155 brouard 772: Revision 1.154 2014/06/20 17:32:08 brouard
773: Summary: Outputs now all graphs of convergence to period prevalence
774:
1.154 brouard 775: Revision 1.153 2014/06/20 16:45:46 brouard
776: Summary: If 3 live state, convergence to period prevalence on same graph
777: Author: Brouard
778:
1.153 brouard 779: Revision 1.152 2014/06/18 17:54:09 brouard
780: Summary: open browser, use gnuplot on same dir than imach if not found in the path
781:
1.152 brouard 782: Revision 1.151 2014/06/18 16:43:30 brouard
783: *** empty log message ***
784:
1.151 brouard 785: Revision 1.150 2014/06/18 16:42:35 brouard
786: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
787: Author: brouard
788:
1.150 brouard 789: Revision 1.149 2014/06/18 15:51:14 brouard
790: Summary: Some fixes in parameter files errors
791: Author: Nicolas Brouard
792:
1.149 brouard 793: Revision 1.148 2014/06/17 17:38:48 brouard
794: Summary: Nothing new
795: Author: Brouard
796:
797: Just a new packaging for OS/X version 0.98nS
798:
1.148 brouard 799: Revision 1.147 2014/06/16 10:33:11 brouard
800: *** empty log message ***
801:
1.147 brouard 802: Revision 1.146 2014/06/16 10:20:28 brouard
803: Summary: Merge
804: Author: Brouard
805:
806: Merge, before building revised version.
807:
1.146 brouard 808: Revision 1.145 2014/06/10 21:23:15 brouard
809: Summary: Debugging with valgrind
810: Author: Nicolas Brouard
811:
812: Lot of changes in order to output the results with some covariates
813: After the Edimburgh REVES conference 2014, it seems mandatory to
814: improve the code.
815: No more memory valgrind error but a lot has to be done in order to
816: continue the work of splitting the code into subroutines.
817: Also, decodemodel has been improved. Tricode is still not
818: optimal. nbcode should be improved. Documentation has been added in
819: the source code.
820:
1.144 brouard 821: Revision 1.143 2014/01/26 09:45:38 brouard
822: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
823:
824: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
825: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
826:
1.143 brouard 827: Revision 1.142 2014/01/26 03:57:36 brouard
828: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
829:
830: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
831:
1.142 brouard 832: Revision 1.141 2014/01/26 02:42:01 brouard
833: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
834:
1.141 brouard 835: Revision 1.140 2011/09/02 10:37:54 brouard
836: Summary: times.h is ok with mingw32 now.
837:
1.140 brouard 838: Revision 1.139 2010/06/14 07:50:17 brouard
839: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
840: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
841:
1.139 brouard 842: Revision 1.138 2010/04/30 18:19:40 brouard
843: *** empty log message ***
844:
1.138 brouard 845: Revision 1.137 2010/04/29 18:11:38 brouard
846: (Module): Checking covariates for more complex models
847: than V1+V2. A lot of change to be done. Unstable.
848:
1.137 brouard 849: Revision 1.136 2010/04/26 20:30:53 brouard
850: (Module): merging some libgsl code. Fixing computation
851: of likelione (using inter/intrapolation if mle = 0) in order to
852: get same likelihood as if mle=1.
853: Some cleaning of code and comments added.
854:
1.136 brouard 855: Revision 1.135 2009/10/29 15:33:14 brouard
856: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
857:
1.135 brouard 858: Revision 1.134 2009/10/29 13:18:53 brouard
859: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
860:
1.134 brouard 861: Revision 1.133 2009/07/06 10:21:25 brouard
862: just nforces
863:
1.133 brouard 864: Revision 1.132 2009/07/06 08:22:05 brouard
865: Many tings
866:
1.132 brouard 867: Revision 1.131 2009/06/20 16:22:47 brouard
868: Some dimensions resccaled
869:
1.131 brouard 870: Revision 1.130 2009/05/26 06:44:34 brouard
871: (Module): Max Covariate is now set to 20 instead of 8. A
872: lot of cleaning with variables initialized to 0. Trying to make
873: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
874:
1.130 brouard 875: Revision 1.129 2007/08/31 13:49:27 lievre
876: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
877:
1.129 lievre 878: Revision 1.128 2006/06/30 13:02:05 brouard
879: (Module): Clarifications on computing e.j
880:
1.128 brouard 881: Revision 1.127 2006/04/28 18:11:50 brouard
882: (Module): Yes the sum of survivors was wrong since
883: imach-114 because nhstepm was no more computed in the age
884: loop. Now we define nhstepma in the age loop.
885: (Module): In order to speed up (in case of numerous covariates) we
886: compute health expectancies (without variances) in a first step
887: and then all the health expectancies with variances or standard
888: deviation (needs data from the Hessian matrices) which slows the
889: computation.
890: In the future we should be able to stop the program is only health
891: expectancies and graph are needed without standard deviations.
892:
1.127 brouard 893: Revision 1.126 2006/04/28 17:23:28 brouard
894: (Module): Yes the sum of survivors was wrong since
895: imach-114 because nhstepm was no more computed in the age
896: loop. Now we define nhstepma in the age loop.
897: Version 0.98h
898:
1.126 brouard 899: Revision 1.125 2006/04/04 15:20:31 lievre
900: Errors in calculation of health expectancies. Age was not initialized.
901: Forecasting file added.
902:
903: Revision 1.124 2006/03/22 17:13:53 lievre
904: Parameters are printed with %lf instead of %f (more numbers after the comma).
905: The log-likelihood is printed in the log file
906:
907: Revision 1.123 2006/03/20 10:52:43 brouard
908: * imach.c (Module): <title> changed, corresponds to .htm file
909: name. <head> headers where missing.
910:
911: * imach.c (Module): Weights can have a decimal point as for
912: English (a comma might work with a correct LC_NUMERIC environment,
913: otherwise the weight is truncated).
914: Modification of warning when the covariates values are not 0 or
915: 1.
916: Version 0.98g
917:
918: Revision 1.122 2006/03/20 09:45:41 brouard
919: (Module): Weights can have a decimal point as for
920: English (a comma might work with a correct LC_NUMERIC environment,
921: otherwise the weight is truncated).
922: Modification of warning when the covariates values are not 0 or
923: 1.
924: Version 0.98g
925:
926: Revision 1.121 2006/03/16 17:45:01 lievre
927: * imach.c (Module): Comments concerning covariates added
928:
929: * imach.c (Module): refinements in the computation of lli if
930: status=-2 in order to have more reliable computation if stepm is
931: not 1 month. Version 0.98f
932:
933: Revision 1.120 2006/03/16 15:10:38 lievre
934: (Module): refinements in the computation of lli if
935: status=-2 in order to have more reliable computation if stepm is
936: not 1 month. Version 0.98f
937:
938: Revision 1.119 2006/03/15 17:42:26 brouard
939: (Module): Bug if status = -2, the loglikelihood was
940: computed as likelihood omitting the logarithm. Version O.98e
941:
942: Revision 1.118 2006/03/14 18:20:07 brouard
943: (Module): varevsij Comments added explaining the second
944: table of variances if popbased=1 .
945: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
946: (Module): Function pstamp added
947: (Module): Version 0.98d
948:
949: Revision 1.117 2006/03/14 17:16:22 brouard
950: (Module): varevsij Comments added explaining the second
951: table of variances if popbased=1 .
952: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
953: (Module): Function pstamp added
954: (Module): Version 0.98d
955:
956: Revision 1.116 2006/03/06 10:29:27 brouard
957: (Module): Variance-covariance wrong links and
958: varian-covariance of ej. is needed (Saito).
959:
960: Revision 1.115 2006/02/27 12:17:45 brouard
961: (Module): One freematrix added in mlikeli! 0.98c
962:
963: Revision 1.114 2006/02/26 12:57:58 brouard
964: (Module): Some improvements in processing parameter
965: filename with strsep.
966:
967: Revision 1.113 2006/02/24 14:20:24 brouard
968: (Module): Memory leaks checks with valgrind and:
969: datafile was not closed, some imatrix were not freed and on matrix
970: allocation too.
971:
972: Revision 1.112 2006/01/30 09:55:26 brouard
973: (Module): Back to gnuplot.exe instead of wgnuplot.exe
974:
975: Revision 1.111 2006/01/25 20:38:18 brouard
976: (Module): Lots of cleaning and bugs added (Gompertz)
977: (Module): Comments can be added in data file. Missing date values
978: can be a simple dot '.'.
979:
980: Revision 1.110 2006/01/25 00:51:50 brouard
981: (Module): Lots of cleaning and bugs added (Gompertz)
982:
983: Revision 1.109 2006/01/24 19:37:15 brouard
984: (Module): Comments (lines starting with a #) are allowed in data.
985:
986: Revision 1.108 2006/01/19 18:05:42 lievre
987: Gnuplot problem appeared...
988: To be fixed
989:
990: Revision 1.107 2006/01/19 16:20:37 brouard
991: Test existence of gnuplot in imach path
992:
993: Revision 1.106 2006/01/19 13:24:36 brouard
994: Some cleaning and links added in html output
995:
996: Revision 1.105 2006/01/05 20:23:19 lievre
997: *** empty log message ***
998:
999: Revision 1.104 2005/09/30 16:11:43 lievre
1000: (Module): sump fixed, loop imx fixed, and simplifications.
1001: (Module): If the status is missing at the last wave but we know
1002: that the person is alive, then we can code his/her status as -2
1003: (instead of missing=-1 in earlier versions) and his/her
1004: contributions to the likelihood is 1 - Prob of dying from last
1005: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1006: the healthy state at last known wave). Version is 0.98
1007:
1008: Revision 1.103 2005/09/30 15:54:49 lievre
1009: (Module): sump fixed, loop imx fixed, and simplifications.
1010:
1011: Revision 1.102 2004/09/15 17:31:30 brouard
1012: Add the possibility to read data file including tab characters.
1013:
1014: Revision 1.101 2004/09/15 10:38:38 brouard
1015: Fix on curr_time
1016:
1017: Revision 1.100 2004/07/12 18:29:06 brouard
1018: Add version for Mac OS X. Just define UNIX in Makefile
1019:
1020: Revision 1.99 2004/06/05 08:57:40 brouard
1021: *** empty log message ***
1022:
1023: Revision 1.98 2004/05/16 15:05:56 brouard
1024: New version 0.97 . First attempt to estimate force of mortality
1025: directly from the data i.e. without the need of knowing the health
1026: state at each age, but using a Gompertz model: log u =a + b*age .
1027: This is the basic analysis of mortality and should be done before any
1028: other analysis, in order to test if the mortality estimated from the
1029: cross-longitudinal survey is different from the mortality estimated
1030: from other sources like vital statistic data.
1031:
1032: The same imach parameter file can be used but the option for mle should be -3.
1033:
1.324 brouard 1034: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1035: former routines in order to include the new code within the former code.
1036:
1037: The output is very simple: only an estimate of the intercept and of
1038: the slope with 95% confident intervals.
1039:
1040: Current limitations:
1041: A) Even if you enter covariates, i.e. with the
1042: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1043: B) There is no computation of Life Expectancy nor Life Table.
1044:
1045: Revision 1.97 2004/02/20 13:25:42 lievre
1046: Version 0.96d. Population forecasting command line is (temporarily)
1047: suppressed.
1048:
1049: Revision 1.96 2003/07/15 15:38:55 brouard
1050: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1051: rewritten within the same printf. Workaround: many printfs.
1052:
1053: Revision 1.95 2003/07/08 07:54:34 brouard
1054: * imach.c (Repository):
1055: (Repository): Using imachwizard code to output a more meaningful covariance
1056: matrix (cov(a12,c31) instead of numbers.
1057:
1058: Revision 1.94 2003/06/27 13:00:02 brouard
1059: Just cleaning
1060:
1061: Revision 1.93 2003/06/25 16:33:55 brouard
1062: (Module): On windows (cygwin) function asctime_r doesn't
1063: exist so I changed back to asctime which exists.
1064: (Module): Version 0.96b
1065:
1066: Revision 1.92 2003/06/25 16:30:45 brouard
1067: (Module): On windows (cygwin) function asctime_r doesn't
1068: exist so I changed back to asctime which exists.
1069:
1070: Revision 1.91 2003/06/25 15:30:29 brouard
1071: * imach.c (Repository): Duplicated warning errors corrected.
1072: (Repository): Elapsed time after each iteration is now output. It
1073: helps to forecast when convergence will be reached. Elapsed time
1074: is stamped in powell. We created a new html file for the graphs
1075: concerning matrix of covariance. It has extension -cov.htm.
1076:
1077: Revision 1.90 2003/06/24 12:34:15 brouard
1078: (Module): Some bugs corrected for windows. Also, when
1079: mle=-1 a template is output in file "or"mypar.txt with the design
1080: of the covariance matrix to be input.
1081:
1082: Revision 1.89 2003/06/24 12:30:52 brouard
1083: (Module): Some bugs corrected for windows. Also, when
1084: mle=-1 a template is output in file "or"mypar.txt with the design
1085: of the covariance matrix to be input.
1086:
1087: Revision 1.88 2003/06/23 17:54:56 brouard
1088: * 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.
1089:
1090: Revision 1.87 2003/06/18 12:26:01 brouard
1091: Version 0.96
1092:
1093: Revision 1.86 2003/06/17 20:04:08 brouard
1094: (Module): Change position of html and gnuplot routines and added
1095: routine fileappend.
1096:
1097: Revision 1.85 2003/06/17 13:12:43 brouard
1098: * imach.c (Repository): Check when date of death was earlier that
1099: current date of interview. It may happen when the death was just
1100: prior to the death. In this case, dh was negative and likelihood
1101: was wrong (infinity). We still send an "Error" but patch by
1102: assuming that the date of death was just one stepm after the
1103: interview.
1104: (Repository): Because some people have very long ID (first column)
1105: we changed int to long in num[] and we added a new lvector for
1106: memory allocation. But we also truncated to 8 characters (left
1107: truncation)
1108: (Repository): No more line truncation errors.
1109:
1110: Revision 1.84 2003/06/13 21:44:43 brouard
1111: * imach.c (Repository): Replace "freqsummary" at a correct
1112: place. It differs from routine "prevalence" which may be called
1113: many times. Probs is memory consuming and must be used with
1114: parcimony.
1115: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1116:
1117: Revision 1.83 2003/06/10 13:39:11 lievre
1118: *** empty log message ***
1119:
1120: Revision 1.82 2003/06/05 15:57:20 brouard
1121: Add log in imach.c and fullversion number is now printed.
1122:
1123: */
1124: /*
1125: Interpolated Markov Chain
1126:
1127: Short summary of the programme:
1128:
1.227 brouard 1129: This program computes Healthy Life Expectancies or State-specific
1130: (if states aren't health statuses) Expectancies from
1131: cross-longitudinal data. Cross-longitudinal data consist in:
1132:
1133: -1- a first survey ("cross") where individuals from different ages
1134: are interviewed on their health status or degree of disability (in
1135: the case of a health survey which is our main interest)
1136:
1137: -2- at least a second wave of interviews ("longitudinal") which
1138: measure each change (if any) in individual health status. Health
1139: expectancies are computed from the time spent in each health state
1140: according to a model. More health states you consider, more time is
1141: necessary to reach the Maximum Likelihood of the parameters involved
1142: in the model. The simplest model is the multinomial logistic model
1143: where pij is the probability to be observed in state j at the second
1144: wave conditional to be observed in state i at the first
1145: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1146: etc , where 'age' is age and 'sex' is a covariate. If you want to
1147: have a more complex model than "constant and age", you should modify
1148: the program where the markup *Covariates have to be included here
1149: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1150: convergence.
1151:
1152: The advantage of this computer programme, compared to a simple
1153: multinomial logistic model, is clear when the delay between waves is not
1154: identical for each individual. Also, if a individual missed an
1155: intermediate interview, the information is lost, but taken into
1156: account using an interpolation or extrapolation.
1157:
1158: hPijx is the probability to be observed in state i at age x+h
1159: conditional to the observed state i at age x. The delay 'h' can be
1160: split into an exact number (nh*stepm) of unobserved intermediate
1161: states. This elementary transition (by month, quarter,
1162: semester or year) is modelled as a multinomial logistic. The hPx
1163: matrix is simply the matrix product of nh*stepm elementary matrices
1164: and the contribution of each individual to the likelihood is simply
1165: hPijx.
1166:
1167: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1168: of the life expectancies. It also computes the period (stable) prevalence.
1169:
1170: Back prevalence and projections:
1.227 brouard 1171:
1172: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1173: double agemaxpar, double ftolpl, int *ncvyearp, double
1174: dateprev1,double dateprev2, int firstpass, int lastpass, int
1175: mobilavproj)
1176:
1177: Computes the back prevalence limit for any combination of
1178: covariate values k at any age between ageminpar and agemaxpar and
1179: returns it in **bprlim. In the loops,
1180:
1181: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1182: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1183:
1184: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1185: Computes for any combination of covariates k and any age between bage and fage
1186: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1187: oldm=oldms;savm=savms;
1.227 brouard 1188:
1.267 brouard 1189: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1190: Computes the transition matrix starting at age 'age' over
1191: 'nhstepm*hstepm*stepm' months (i.e. until
1192: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1193: nhstepm*hstepm matrices.
1194:
1195: Returns p3mat[i][j][h] after calling
1196: p3mat[i][j][h]=matprod2(newm,
1197: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1198: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1199: oldm);
1.226 brouard 1200:
1201: Important routines
1202:
1203: - func (or funcone), computes logit (pij) distinguishing
1204: o fixed variables (single or product dummies or quantitative);
1205: o varying variables by:
1206: (1) wave (single, product dummies, quantitative),
1207: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1208: % fixed dummy (treated) or quantitative (not done because time-consuming);
1209: % varying dummy (not done) or quantitative (not done);
1210: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1211: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1212: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1213: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1214: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1215:
1.226 brouard 1216:
1217:
1.324 brouard 1218: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1219: Institut national d'études démographiques, Paris.
1.126 brouard 1220: This software have been partly granted by Euro-REVES, a concerted action
1221: from the European Union.
1222: It is copyrighted identically to a GNU software product, ie programme and
1223: software can be distributed freely for non commercial use. Latest version
1224: can be accessed at http://euroreves.ined.fr/imach .
1225:
1226: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1227: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1228:
1229: **********************************************************************/
1230: /*
1231: main
1232: read parameterfile
1233: read datafile
1234: concatwav
1235: freqsummary
1236: if (mle >= 1)
1237: mlikeli
1238: print results files
1239: if mle==1
1240: computes hessian
1241: read end of parameter file: agemin, agemax, bage, fage, estepm
1242: begin-prev-date,...
1243: open gnuplot file
1244: open html file
1.145 brouard 1245: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1246: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1247: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1248: freexexit2 possible for memory heap.
1249:
1250: h Pij x | pij_nom ficrestpij
1251: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1252: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1253: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1254:
1255: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1256: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1257: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1258: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1259: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1260:
1.126 brouard 1261: forecasting if prevfcast==1 prevforecast call prevalence()
1262: health expectancies
1263: Variance-covariance of DFLE
1264: prevalence()
1265: movingaverage()
1266: varevsij()
1267: if popbased==1 varevsij(,popbased)
1268: total life expectancies
1269: Variance of period (stable) prevalence
1270: end
1271: */
1272:
1.187 brouard 1273: /* #define DEBUG */
1274: /* #define DEBUGBRENT */
1.203 brouard 1275: /* #define DEBUGLINMIN */
1276: /* #define DEBUGHESS */
1277: #define DEBUGHESSIJ
1.224 brouard 1278: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1279: #define POWELL /* Instead of NLOPT */
1.224 brouard 1280: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1281: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1282: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1283: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1284:
1285: #include <math.h>
1286: #include <stdio.h>
1287: #include <stdlib.h>
1288: #include <string.h>
1.226 brouard 1289: #include <ctype.h>
1.159 brouard 1290:
1291: #ifdef _WIN32
1292: #include <io.h>
1.172 brouard 1293: #include <windows.h>
1294: #include <tchar.h>
1.159 brouard 1295: #else
1.126 brouard 1296: #include <unistd.h>
1.159 brouard 1297: #endif
1.126 brouard 1298:
1299: #include <limits.h>
1300: #include <sys/types.h>
1.171 brouard 1301:
1302: #if defined(__GNUC__)
1303: #include <sys/utsname.h> /* Doesn't work on Windows */
1304: #endif
1305:
1.126 brouard 1306: #include <sys/stat.h>
1307: #include <errno.h>
1.159 brouard 1308: /* extern int errno; */
1.126 brouard 1309:
1.157 brouard 1310: /* #ifdef LINUX */
1311: /* #include <time.h> */
1312: /* #include "timeval.h" */
1313: /* #else */
1314: /* #include <sys/time.h> */
1315: /* #endif */
1316:
1.126 brouard 1317: #include <time.h>
1318:
1.136 brouard 1319: #ifdef GSL
1320: #include <gsl/gsl_errno.h>
1321: #include <gsl/gsl_multimin.h>
1322: #endif
1323:
1.167 brouard 1324:
1.162 brouard 1325: #ifdef NLOPT
1326: #include <nlopt.h>
1327: typedef struct {
1328: double (* function)(double [] );
1329: } myfunc_data ;
1330: #endif
1331:
1.126 brouard 1332: /* #include <libintl.h> */
1333: /* #define _(String) gettext (String) */
1334:
1.349 brouard 1335: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1336:
1337: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1338: #define GNUPLOTVERSION 5.1
1339: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1340: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1341: #define FILENAMELENGTH 256
1.126 brouard 1342:
1343: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1344: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1345:
1.349 brouard 1346: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1347: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1348:
1349: #define NINTERVMAX 8
1.144 brouard 1350: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1351: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1352: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1353: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1354: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1355: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1356: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1357: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1358: /* #define AGESUP 130 */
1.288 brouard 1359: /* #define AGESUP 150 */
1360: #define AGESUP 200
1.268 brouard 1361: #define AGEINF 0
1.218 brouard 1362: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1363: #define AGEBASE 40
1.194 brouard 1364: #define AGEOVERFLOW 1.e20
1.164 brouard 1365: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1366: #ifdef _WIN32
1367: #define DIRSEPARATOR '\\'
1368: #define CHARSEPARATOR "\\"
1369: #define ODIRSEPARATOR '/'
1370: #else
1.126 brouard 1371: #define DIRSEPARATOR '/'
1372: #define CHARSEPARATOR "/"
1373: #define ODIRSEPARATOR '\\'
1374: #endif
1375:
1.355 ! brouard 1376: /* $Id: imach.c,v 1.354 2023/05/21 05:05:17 brouard Exp $ */
1.126 brouard 1377: /* $State: Exp $ */
1.196 brouard 1378: #include "version.h"
1379: char version[]=__IMACH_VERSION__;
1.352 brouard 1380: 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";
1.355 ! brouard 1381: char fullversion[]="$Revision: 1.354 $ $Date: 2023/05/21 05:05:17 $";
1.126 brouard 1382: char strstart[80];
1383: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1384: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1385: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1386: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1387: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1388: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1389: 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 1390: 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 1391: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1392: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1393: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1394: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1395: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1396: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1397: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1398: 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 1399: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1400: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1401: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1402: 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 */
1403: 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 */
1404: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1405: 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 1406: int nsd=0; /**< Total number of single dummy variables (output) */
1407: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1408: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1409: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1410: int ntveff=0; /**< ntveff number of effective time varying variables */
1411: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1412: int cptcov=0; /* Working variable */
1.334 brouard 1413: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1414: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1415: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1416: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1417: int nlstate=2; /* Number of live states */
1418: int ndeath=1; /* Number of dead states */
1.130 brouard 1419: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1420: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1421: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1422: int popbased=0;
1423:
1424: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1425: int maxwav=0; /* Maxim number of waves */
1426: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1427: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1428: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1429: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1430: int mle=1, weightopt=0;
1.126 brouard 1431: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1432: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1433: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1434: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1435: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1436: int selected(int kvar); /* Is covariate kvar selected for printing results */
1437:
1.130 brouard 1438: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1439: double **matprod2(); /* test */
1.126 brouard 1440: double **oldm, **newm, **savm; /* Working pointers to matrices */
1441: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1442: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1443:
1.136 brouard 1444: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1445: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1446: FILE *ficlog, *ficrespow;
1.130 brouard 1447: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1448: double fretone; /* Only one call to likelihood */
1.130 brouard 1449: long ipmx=0; /* Number of contributions */
1.126 brouard 1450: double sw; /* Sum of weights */
1451: char filerespow[FILENAMELENGTH];
1452: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1453: FILE *ficresilk;
1454: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1455: FILE *ficresprobmorprev;
1456: FILE *fichtm, *fichtmcov; /* Html File */
1457: FILE *ficreseij;
1458: char filerese[FILENAMELENGTH];
1459: FILE *ficresstdeij;
1460: char fileresstde[FILENAMELENGTH];
1461: FILE *ficrescveij;
1462: char filerescve[FILENAMELENGTH];
1463: FILE *ficresvij;
1464: char fileresv[FILENAMELENGTH];
1.269 brouard 1465:
1.126 brouard 1466: char title[MAXLINE];
1.234 brouard 1467: char model[MAXLINE]; /**< The model line */
1.217 brouard 1468: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1469: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1470: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1471: char command[FILENAMELENGTH];
1472: int outcmd=0;
1473:
1.217 brouard 1474: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1475: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1476: char filelog[FILENAMELENGTH]; /* Log file */
1477: char filerest[FILENAMELENGTH];
1478: char fileregp[FILENAMELENGTH];
1479: char popfile[FILENAMELENGTH];
1480:
1481: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1482:
1.157 brouard 1483: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1484: /* struct timezone tzp; */
1485: /* extern int gettimeofday(); */
1486: struct tm tml, *gmtime(), *localtime();
1487:
1488: extern time_t time();
1489:
1490: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1491: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1492: time_t rlast_btime; /* raw time */
1.157 brouard 1493: struct tm tm;
1494:
1.126 brouard 1495: char strcurr[80], strfor[80];
1496:
1497: char *endptr;
1498: long lval;
1499: double dval;
1500:
1501: #define NR_END 1
1502: #define FREE_ARG char*
1503: #define FTOL 1.0e-10
1504:
1505: #define NRANSI
1.240 brouard 1506: #define ITMAX 200
1507: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1508:
1509: #define TOL 2.0e-4
1510:
1511: #define CGOLD 0.3819660
1512: #define ZEPS 1.0e-10
1513: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1514:
1515: #define GOLD 1.618034
1516: #define GLIMIT 100.0
1517: #define TINY 1.0e-20
1518:
1519: static double maxarg1,maxarg2;
1520: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1521: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1522:
1523: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1524: #define rint(a) floor(a+0.5)
1.166 brouard 1525: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1526: #define mytinydouble 1.0e-16
1.166 brouard 1527: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1528: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1529: /* static double dsqrarg; */
1530: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1531: static double sqrarg;
1532: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1533: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1534: int agegomp= AGEGOMP;
1535:
1536: int imx;
1537: int stepm=1;
1538: /* Stepm, step in month: minimum step interpolation*/
1539:
1540: int estepm;
1541: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1542:
1543: int m,nb;
1544: long *num;
1.197 brouard 1545: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1546: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1547: covariate for which somebody answered excluding
1548: undefined. Usually 2: 0 and 1. */
1549: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1550: covariate for which somebody answered including
1551: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1552: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1553: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1554: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1555: 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 1556: double *ageexmed,*agecens;
1557: double dateintmean=0;
1.296 brouard 1558: double anprojd, mprojd, jprojd; /* For eventual projections */
1559: double anprojf, mprojf, jprojf;
1.126 brouard 1560:
1.296 brouard 1561: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1562: double anbackf, mbackf, jbackf;
1563: double jintmean,mintmean,aintmean;
1.126 brouard 1564: double *weight;
1565: int **s; /* Status */
1.141 brouard 1566: double *agedc;
1.145 brouard 1567: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1568: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1569: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1570: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1571: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1572: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1573: double idx;
1574: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1575: /* Some documentation */
1576: /* Design original data
1577: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1578: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1579: * ntv=3 nqtv=1
1.330 brouard 1580: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1581: * For time varying covariate, quanti or dummies
1582: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1583: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1584: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1585: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1586: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1587: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1588: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1589: * k= 1 2 3 4 5 6 7 8 9 10 11
1590: */
1591: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1592: /* 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
1593: # States 1=Coresidence, 2 Living alone, 3 Institution
1594: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1595: */
1.349 brouard 1596: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1597: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1598: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1599: /* fixed or varying), 1 for age product, 2 for*/
1600: /* product without age, 3 for age and double product */
1601: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1602: /*(single or product without age), 2 dummy*/
1603: /* with age product, 3 quant with age product*/
1604: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1605: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1606: /*TnsdVar[Tvar] 1 2 3 */
1607: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1608: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1609: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1610: /* nsq 1 2 */ /* Counting single quantit tv */
1611: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1612: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1613: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1614: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1615: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1616: /* 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"*/
1617: /* p Tvard[1][1]@21 = {6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0}*/
1.354 brouard 1618: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>} */
1.350 brouard 1619: /* 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}*/
1620: /* 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 1621: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1622: /* 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 1623: /* 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 1624: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1625: /* Type */
1626: /* V 1 2 3 4 5 */
1627: /* F F V V V */
1628: /* D Q D D Q */
1629: /* */
1630: int *TvarsD;
1.330 brouard 1631: int *TnsdVar;
1.234 brouard 1632: int *TvarsDind;
1633: int *TvarsQ;
1634: int *TvarsQind;
1635:
1.318 brouard 1636: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1637: int nresult=0;
1.258 brouard 1638: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1639: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1640: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1641: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1642: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1643: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1644: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1645: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1646: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1647: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1648: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1649:
1650: /* 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
1651: # States 1=Coresidence, 2 Living alone, 3 Institution
1652: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1653: */
1.234 brouard 1654: /* 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 1655: 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 */
1656: 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 */
1657: 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 */
1658: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1659: 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 */
1660: 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 1661: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1662: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1663: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1664: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1665: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1666: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1667: 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 */
1668: 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 1669: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1670: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1671: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1672: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1673: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1674: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1675: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1676: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1677: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1678: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1679: /* 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 1680: int *Tvarsel; /**< Selected covariates for output */
1681: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1682: 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 1683: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1684: 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 1685: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1686: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1687: int *Tage;
1.227 brouard 1688: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1689: 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 1690: 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*/
1691: 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 1692: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1693: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1694: int **Tvard;
1.330 brouard 1695: int **Tvardk;
1.227 brouard 1696: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1697: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1698: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1699: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1700: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1701: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1702: double *lsurv, *lpop, *tpop;
1703:
1.231 brouard 1704: #define FD 1; /* Fixed dummy covariate */
1705: #define FQ 2; /* Fixed quantitative covariate */
1706: #define FP 3; /* Fixed product covariate */
1707: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1708: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1709: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1710: #define VD 10; /* Varying dummy covariate */
1711: #define VQ 11; /* Varying quantitative covariate */
1712: #define VP 12; /* Varying product covariate */
1713: #define VPDD 13; /* Varying product dummy*dummy covariate */
1714: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1715: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1716: #define APFD 16; /* Age product * fixed dummy covariate */
1717: #define APFQ 17; /* Age product * fixed quantitative covariate */
1718: #define APVD 18; /* Age product * varying dummy covariate */
1719: #define APVQ 19; /* Age product * varying quantitative covariate */
1720:
1721: #define FTYPE 1; /* Fixed covariate */
1722: #define VTYPE 2; /* Varying covariate (loop in wave) */
1723: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1724:
1725: struct kmodel{
1726: int maintype; /* main type */
1727: int subtype; /* subtype */
1728: };
1729: struct kmodel modell[NCOVMAX];
1730:
1.143 brouard 1731: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1732: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1733:
1734: /**************** split *************************/
1735: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1736: {
1737: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1738: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1739: */
1740: char *ss; /* pointer */
1.186 brouard 1741: int l1=0, l2=0; /* length counters */
1.126 brouard 1742:
1743: l1 = strlen(path ); /* length of path */
1744: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1745: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1746: if ( ss == NULL ) { /* no directory, so determine current directory */
1747: strcpy( name, path ); /* we got the fullname name because no directory */
1748: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1749: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1750: /* get current working directory */
1751: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1752: #ifdef WIN32
1753: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1754: #else
1755: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1756: #endif
1.126 brouard 1757: return( GLOCK_ERROR_GETCWD );
1758: }
1759: /* got dirc from getcwd*/
1760: printf(" DIRC = %s \n",dirc);
1.205 brouard 1761: } else { /* strip directory from path */
1.126 brouard 1762: ss++; /* after this, the filename */
1763: l2 = strlen( ss ); /* length of filename */
1764: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1765: strcpy( name, ss ); /* save file name */
1766: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1767: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1768: printf(" DIRC2 = %s \n",dirc);
1769: }
1770: /* We add a separator at the end of dirc if not exists */
1771: l1 = strlen( dirc ); /* length of directory */
1772: if( dirc[l1-1] != DIRSEPARATOR ){
1773: dirc[l1] = DIRSEPARATOR;
1774: dirc[l1+1] = 0;
1775: printf(" DIRC3 = %s \n",dirc);
1776: }
1777: ss = strrchr( name, '.' ); /* find last / */
1778: if (ss >0){
1779: ss++;
1780: strcpy(ext,ss); /* save extension */
1781: l1= strlen( name);
1782: l2= strlen(ss)+1;
1783: strncpy( finame, name, l1-l2);
1784: finame[l1-l2]= 0;
1785: }
1786:
1787: return( 0 ); /* we're done */
1788: }
1789:
1790:
1791: /******************************************/
1792:
1793: void replace_back_to_slash(char *s, char*t)
1794: {
1795: int i;
1796: int lg=0;
1797: i=0;
1798: lg=strlen(t);
1799: for(i=0; i<= lg; i++) {
1800: (s[i] = t[i]);
1801: if (t[i]== '\\') s[i]='/';
1802: }
1803: }
1804:
1.132 brouard 1805: char *trimbb(char *out, char *in)
1.137 brouard 1806: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1807: char *s;
1808: s=out;
1809: while (*in != '\0'){
1.137 brouard 1810: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1811: in++;
1812: }
1813: *out++ = *in++;
1814: }
1815: *out='\0';
1816: return s;
1817: }
1818:
1.351 brouard 1819: char *trimbtab(char *out, char *in)
1820: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1821: char *s;
1822: s=out;
1823: while (*in != '\0'){
1824: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1825: in++;
1826: }
1827: *out++ = *in++;
1828: }
1829: *out='\0';
1830: return s;
1831: }
1832:
1.187 brouard 1833: /* char *substrchaine(char *out, char *in, char *chain) */
1834: /* { */
1835: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1836: /* char *s, *t; */
1837: /* t=in;s=out; */
1838: /* while ((*in != *chain) && (*in != '\0')){ */
1839: /* *out++ = *in++; */
1840: /* } */
1841:
1842: /* /\* *in matches *chain *\/ */
1843: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1844: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1845: /* } */
1846: /* in--; chain--; */
1847: /* while ( (*in != '\0')){ */
1848: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1849: /* *out++ = *in++; */
1850: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1851: /* } */
1852: /* *out='\0'; */
1853: /* out=s; */
1854: /* return out; */
1855: /* } */
1856: char *substrchaine(char *out, char *in, char *chain)
1857: {
1858: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1859: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1860:
1861: char *strloc;
1862:
1.349 brouard 1863: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1864: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1865: 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 1866: if(strloc != NULL){
1.349 brouard 1867: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1868: 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)*/
1869: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1870: }
1.349 brouard 1871: 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 1872: return out;
1873: }
1874:
1875:
1.145 brouard 1876: char *cutl(char *blocc, char *alocc, char *in, char occ)
1877: {
1.187 brouard 1878: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1879: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1880: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1881: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1882: */
1.160 brouard 1883: char *s, *t;
1.145 brouard 1884: t=in;s=in;
1885: while ((*in != occ) && (*in != '\0')){
1886: *alocc++ = *in++;
1887: }
1888: if( *in == occ){
1889: *(alocc)='\0';
1890: s=++in;
1891: }
1892:
1893: if (s == t) {/* occ not found */
1894: *(alocc-(in-s))='\0';
1895: in=s;
1896: }
1897: while ( *in != '\0'){
1898: *blocc++ = *in++;
1899: }
1900:
1901: *blocc='\0';
1902: return t;
1903: }
1.137 brouard 1904: char *cutv(char *blocc, char *alocc, char *in, char occ)
1905: {
1.187 brouard 1906: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1907: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1908: gives blocc="abcdef2ghi" and alocc="j".
1909: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1910: */
1911: char *s, *t;
1912: t=in;s=in;
1913: while (*in != '\0'){
1914: while( *in == occ){
1915: *blocc++ = *in++;
1916: s=in;
1917: }
1918: *blocc++ = *in++;
1919: }
1920: if (s == t) /* occ not found */
1921: *(blocc-(in-s))='\0';
1922: else
1923: *(blocc-(in-s)-1)='\0';
1924: in=s;
1925: while ( *in != '\0'){
1926: *alocc++ = *in++;
1927: }
1928:
1929: *alocc='\0';
1930: return s;
1931: }
1932:
1.126 brouard 1933: int nbocc(char *s, char occ)
1934: {
1935: int i,j=0;
1936: int lg=20;
1937: i=0;
1938: lg=strlen(s);
1939: for(i=0; i<= lg; i++) {
1.234 brouard 1940: if (s[i] == occ ) j++;
1.126 brouard 1941: }
1942: return j;
1943: }
1944:
1.349 brouard 1945: int nboccstr(char *textin, char *chain)
1946: {
1947: /* Counts the number of occurence of "chain" in string textin */
1948: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1949: char *strloc;
1950:
1951: int i,j=0;
1952:
1953: i=0;
1954:
1955: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1956: for(;;) {
1957: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1958: if(strloc != NULL){
1959: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1960: j++;
1961: }else
1962: break;
1963: }
1964: return j;
1965:
1966: }
1.137 brouard 1967: /* void cutv(char *u,char *v, char*t, char occ) */
1968: /* { */
1969: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1970: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1971: /* gives u="abcdef2ghi" and v="j" *\/ */
1972: /* int i,lg,j,p=0; */
1973: /* i=0; */
1974: /* lg=strlen(t); */
1975: /* for(j=0; j<=lg-1; j++) { */
1976: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1977: /* } */
1.126 brouard 1978:
1.137 brouard 1979: /* for(j=0; j<p; j++) { */
1980: /* (u[j] = t[j]); */
1981: /* } */
1982: /* u[p]='\0'; */
1.126 brouard 1983:
1.137 brouard 1984: /* for(j=0; j<= lg; j++) { */
1985: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1986: /* } */
1987: /* } */
1.126 brouard 1988:
1.160 brouard 1989: #ifdef _WIN32
1990: char * strsep(char **pp, const char *delim)
1991: {
1992: char *p, *q;
1993:
1994: if ((p = *pp) == NULL)
1995: return 0;
1996: if ((q = strpbrk (p, delim)) != NULL)
1997: {
1998: *pp = q + 1;
1999: *q = '\0';
2000: }
2001: else
2002: *pp = 0;
2003: return p;
2004: }
2005: #endif
2006:
1.126 brouard 2007: /********************** nrerror ********************/
2008:
2009: void nrerror(char error_text[])
2010: {
2011: fprintf(stderr,"ERREUR ...\n");
2012: fprintf(stderr,"%s\n",error_text);
2013: exit(EXIT_FAILURE);
2014: }
2015: /*********************** vector *******************/
2016: double *vector(int nl, int nh)
2017: {
2018: double *v;
2019: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2020: if (!v) nrerror("allocation failure in vector");
2021: return v-nl+NR_END;
2022: }
2023:
2024: /************************ free vector ******************/
2025: void free_vector(double*v, int nl, int nh)
2026: {
2027: free((FREE_ARG)(v+nl-NR_END));
2028: }
2029:
2030: /************************ivector *******************************/
2031: int *ivector(long nl,long nh)
2032: {
2033: int *v;
2034: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2035: if (!v) nrerror("allocation failure in ivector");
2036: return v-nl+NR_END;
2037: }
2038:
2039: /******************free ivector **************************/
2040: void free_ivector(int *v, long nl, long nh)
2041: {
2042: free((FREE_ARG)(v+nl-NR_END));
2043: }
2044:
2045: /************************lvector *******************************/
2046: long *lvector(long nl,long nh)
2047: {
2048: long *v;
2049: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2050: if (!v) nrerror("allocation failure in ivector");
2051: return v-nl+NR_END;
2052: }
2053:
2054: /******************free lvector **************************/
2055: void free_lvector(long *v, long nl, long nh)
2056: {
2057: free((FREE_ARG)(v+nl-NR_END));
2058: }
2059:
2060: /******************* imatrix *******************************/
2061: int **imatrix(long nrl, long nrh, long ncl, long nch)
2062: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2063: {
2064: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2065: int **m;
2066:
2067: /* allocate pointers to rows */
2068: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2069: if (!m) nrerror("allocation failure 1 in matrix()");
2070: m += NR_END;
2071: m -= nrl;
2072:
2073:
2074: /* allocate rows and set pointers to them */
2075: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2076: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2077: m[nrl] += NR_END;
2078: m[nrl] -= ncl;
2079:
2080: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2081:
2082: /* return pointer to array of pointers to rows */
2083: return m;
2084: }
2085:
2086: /****************** free_imatrix *************************/
2087: void free_imatrix(m,nrl,nrh,ncl,nch)
2088: int **m;
2089: long nch,ncl,nrh,nrl;
2090: /* free an int matrix allocated by imatrix() */
2091: {
2092: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2093: free((FREE_ARG) (m+nrl-NR_END));
2094: }
2095:
2096: /******************* matrix *******************************/
2097: double **matrix(long nrl, long nrh, long ncl, long nch)
2098: {
2099: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2100: double **m;
2101:
2102: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2103: if (!m) nrerror("allocation failure 1 in matrix()");
2104: m += NR_END;
2105: m -= nrl;
2106:
2107: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2108: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2109: m[nrl] += NR_END;
2110: m[nrl] -= ncl;
2111:
2112: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2113: return m;
1.145 brouard 2114: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2115: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2116: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2117: */
2118: }
2119:
2120: /*************************free matrix ************************/
2121: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2122: {
2123: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2124: free((FREE_ARG)(m+nrl-NR_END));
2125: }
2126:
2127: /******************* ma3x *******************************/
2128: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2129: {
2130: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2131: double ***m;
2132:
2133: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2134: if (!m) nrerror("allocation failure 1 in matrix()");
2135: m += NR_END;
2136: m -= nrl;
2137:
2138: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2139: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2140: m[nrl] += NR_END;
2141: m[nrl] -= ncl;
2142:
2143: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2144:
2145: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2146: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2147: m[nrl][ncl] += NR_END;
2148: m[nrl][ncl] -= nll;
2149: for (j=ncl+1; j<=nch; j++)
2150: m[nrl][j]=m[nrl][j-1]+nlay;
2151:
2152: for (i=nrl+1; i<=nrh; i++) {
2153: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2154: for (j=ncl+1; j<=nch; j++)
2155: m[i][j]=m[i][j-1]+nlay;
2156: }
2157: return m;
2158: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2159: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2160: */
2161: }
2162:
2163: /*************************free ma3x ************************/
2164: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2165: {
2166: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2167: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2168: free((FREE_ARG)(m+nrl-NR_END));
2169: }
2170:
2171: /*************** function subdirf ***********/
2172: char *subdirf(char fileres[])
2173: {
2174: /* Caution optionfilefiname is hidden */
2175: strcpy(tmpout,optionfilefiname);
2176: strcat(tmpout,"/"); /* Add to the right */
2177: strcat(tmpout,fileres);
2178: return tmpout;
2179: }
2180:
2181: /*************** function subdirf2 ***********/
2182: char *subdirf2(char fileres[], char *preop)
2183: {
1.314 brouard 2184: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2185: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2186: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2187: /* Caution optionfilefiname is hidden */
2188: strcpy(tmpout,optionfilefiname);
2189: strcat(tmpout,"/");
2190: strcat(tmpout,preop);
2191: strcat(tmpout,fileres);
2192: return tmpout;
2193: }
2194:
2195: /*************** function subdirf3 ***********/
2196: char *subdirf3(char fileres[], char *preop, char *preop2)
2197: {
2198:
2199: /* Caution optionfilefiname is hidden */
2200: strcpy(tmpout,optionfilefiname);
2201: strcat(tmpout,"/");
2202: strcat(tmpout,preop);
2203: strcat(tmpout,preop2);
2204: strcat(tmpout,fileres);
2205: return tmpout;
2206: }
1.213 brouard 2207:
2208: /*************** function subdirfext ***********/
2209: char *subdirfext(char fileres[], char *preop, char *postop)
2210: {
2211:
2212: strcpy(tmpout,preop);
2213: strcat(tmpout,fileres);
2214: strcat(tmpout,postop);
2215: return tmpout;
2216: }
1.126 brouard 2217:
1.213 brouard 2218: /*************** function subdirfext3 ***********/
2219: char *subdirfext3(char fileres[], char *preop, char *postop)
2220: {
2221:
2222: /* Caution optionfilefiname is hidden */
2223: strcpy(tmpout,optionfilefiname);
2224: strcat(tmpout,"/");
2225: strcat(tmpout,preop);
2226: strcat(tmpout,fileres);
2227: strcat(tmpout,postop);
2228: return tmpout;
2229: }
2230:
1.162 brouard 2231: char *asc_diff_time(long time_sec, char ascdiff[])
2232: {
2233: long sec_left, days, hours, minutes;
2234: days = (time_sec) / (60*60*24);
2235: sec_left = (time_sec) % (60*60*24);
2236: hours = (sec_left) / (60*60) ;
2237: sec_left = (sec_left) %(60*60);
2238: minutes = (sec_left) /60;
2239: sec_left = (sec_left) % (60);
2240: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2241: return ascdiff;
2242: }
2243:
1.126 brouard 2244: /***************** f1dim *************************/
2245: extern int ncom;
2246: extern double *pcom,*xicom;
2247: extern double (*nrfunc)(double []);
2248:
2249: double f1dim(double x)
2250: {
2251: int j;
2252: double f;
2253: double *xt;
2254:
2255: xt=vector(1,ncom);
2256: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2257: f=(*nrfunc)(xt);
2258: free_vector(xt,1,ncom);
2259: return f;
2260: }
2261:
2262: /*****************brent *************************/
2263: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2264: {
2265: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2266: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2267: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2268: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2269: * returned function value.
2270: */
1.126 brouard 2271: int iter;
2272: double a,b,d,etemp;
1.159 brouard 2273: double fu=0,fv,fw,fx;
1.164 brouard 2274: double ftemp=0.;
1.126 brouard 2275: double p,q,r,tol1,tol2,u,v,w,x,xm;
2276: double e=0.0;
2277:
2278: a=(ax < cx ? ax : cx);
2279: b=(ax > cx ? ax : cx);
2280: x=w=v=bx;
2281: fw=fv=fx=(*f)(x);
2282: for (iter=1;iter<=ITMAX;iter++) {
2283: xm=0.5*(a+b);
2284: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2285: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2286: printf(".");fflush(stdout);
2287: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2288: #ifdef DEBUGBRENT
1.126 brouard 2289: 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);
2290: 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);
2291: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2292: #endif
2293: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2294: *xmin=x;
2295: return fx;
2296: }
2297: ftemp=fu;
2298: if (fabs(e) > tol1) {
2299: r=(x-w)*(fx-fv);
2300: q=(x-v)*(fx-fw);
2301: p=(x-v)*q-(x-w)*r;
2302: q=2.0*(q-r);
2303: if (q > 0.0) p = -p;
2304: q=fabs(q);
2305: etemp=e;
2306: e=d;
2307: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2308: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2309: else {
1.224 brouard 2310: d=p/q;
2311: u=x+d;
2312: if (u-a < tol2 || b-u < tol2)
2313: d=SIGN(tol1,xm-x);
1.126 brouard 2314: }
2315: } else {
2316: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2317: }
2318: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2319: fu=(*f)(u);
2320: if (fu <= fx) {
2321: if (u >= x) a=x; else b=x;
2322: SHFT(v,w,x,u)
1.183 brouard 2323: SHFT(fv,fw,fx,fu)
2324: } else {
2325: if (u < x) a=u; else b=u;
2326: if (fu <= fw || w == x) {
1.224 brouard 2327: v=w;
2328: w=u;
2329: fv=fw;
2330: fw=fu;
1.183 brouard 2331: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2332: v=u;
2333: fv=fu;
1.183 brouard 2334: }
2335: }
1.126 brouard 2336: }
2337: nrerror("Too many iterations in brent");
2338: *xmin=x;
2339: return fx;
2340: }
2341:
2342: /****************** mnbrak ***********************/
2343:
2344: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2345: double (*func)(double))
1.183 brouard 2346: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2347: the downhill direction (defined by the function as evaluated at the initial points) and returns
2348: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2349: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2350: */
1.126 brouard 2351: double ulim,u,r,q, dum;
2352: double fu;
1.187 brouard 2353:
2354: double scale=10.;
2355: int iterscale=0;
2356:
2357: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2358: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2359:
2360:
2361: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2362: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2363: /* *bx = *ax - (*ax - *bx)/scale; */
2364: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2365: /* } */
2366:
1.126 brouard 2367: if (*fb > *fa) {
2368: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2369: SHFT(dum,*fb,*fa,dum)
2370: }
1.126 brouard 2371: *cx=(*bx)+GOLD*(*bx-*ax);
2372: *fc=(*func)(*cx);
1.183 brouard 2373: #ifdef DEBUG
1.224 brouard 2374: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2375: 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 2376: #endif
1.224 brouard 2377: 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 2378: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2379: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2380: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2381: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2382: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2383: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2384: fu=(*func)(u);
1.163 brouard 2385: #ifdef DEBUG
2386: /* f(x)=A(x-u)**2+f(u) */
2387: double A, fparabu;
2388: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2389: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2390: 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);
2391: 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 2392: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2393: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2394: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2395: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2396: #endif
1.184 brouard 2397: #ifdef MNBRAKORIGINAL
1.183 brouard 2398: #else
1.191 brouard 2399: /* if (fu > *fc) { */
2400: /* #ifdef DEBUG */
2401: /* printf("mnbrak4 fu > fc \n"); */
2402: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2403: /* #endif */
2404: /* /\* 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 *\\/ *\/ */
2405: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2406: /* dum=u; /\* Shifting c and u *\/ */
2407: /* u = *cx; */
2408: /* *cx = dum; */
2409: /* dum = fu; */
2410: /* fu = *fc; */
2411: /* *fc =dum; */
2412: /* } else { /\* end *\/ */
2413: /* #ifdef DEBUG */
2414: /* printf("mnbrak3 fu < fc \n"); */
2415: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2416: /* #endif */
2417: /* dum=u; /\* Shifting c and u *\/ */
2418: /* u = *cx; */
2419: /* *cx = dum; */
2420: /* dum = fu; */
2421: /* fu = *fc; */
2422: /* *fc =dum; */
2423: /* } */
1.224 brouard 2424: #ifdef DEBUGMNBRAK
2425: double A, fparabu;
2426: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2427: fparabu= *fa - A*(*ax-u)*(*ax-u);
2428: 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);
2429: 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 2430: #endif
1.191 brouard 2431: dum=u; /* Shifting c and u */
2432: u = *cx;
2433: *cx = dum;
2434: dum = fu;
2435: fu = *fc;
2436: *fc =dum;
1.183 brouard 2437: #endif
1.162 brouard 2438: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2439: #ifdef DEBUG
1.224 brouard 2440: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2441: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2442: #endif
1.126 brouard 2443: fu=(*func)(u);
2444: if (fu < *fc) {
1.183 brouard 2445: #ifdef DEBUG
1.224 brouard 2446: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2447: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2448: #endif
2449: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2450: SHFT(*fb,*fc,fu,(*func)(u))
2451: #ifdef DEBUG
2452: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2453: #endif
2454: }
1.162 brouard 2455: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2456: #ifdef DEBUG
1.224 brouard 2457: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2458: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2459: #endif
1.126 brouard 2460: u=ulim;
2461: fu=(*func)(u);
1.183 brouard 2462: } else { /* u could be left to b (if r > q parabola has a maximum) */
2463: #ifdef DEBUG
1.224 brouard 2464: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2465: 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 2466: #endif
1.126 brouard 2467: u=(*cx)+GOLD*(*cx-*bx);
2468: fu=(*func)(u);
1.224 brouard 2469: #ifdef DEBUG
2470: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2471: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2472: #endif
1.183 brouard 2473: } /* end tests */
1.126 brouard 2474: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2475: SHFT(*fa,*fb,*fc,fu)
2476: #ifdef DEBUG
1.224 brouard 2477: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2478: 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 2479: #endif
2480: } /* 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 2481: }
2482:
2483: /*************** linmin ************************/
1.162 brouard 2484: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2485: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2486: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2487: the value of func at the returned location p . This is actually all accomplished by calling the
2488: routines mnbrak and brent .*/
1.126 brouard 2489: int ncom;
2490: double *pcom,*xicom;
2491: double (*nrfunc)(double []);
2492:
1.224 brouard 2493: #ifdef LINMINORIGINAL
1.126 brouard 2494: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2495: #else
2496: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2497: #endif
1.126 brouard 2498: {
2499: double brent(double ax, double bx, double cx,
2500: double (*f)(double), double tol, double *xmin);
2501: double f1dim(double x);
2502: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2503: double *fc, double (*func)(double));
2504: int j;
2505: double xx,xmin,bx,ax;
2506: double fx,fb,fa;
1.187 brouard 2507:
1.203 brouard 2508: #ifdef LINMINORIGINAL
2509: #else
2510: double scale=10., axs, xxs; /* Scale added for infinity */
2511: #endif
2512:
1.126 brouard 2513: ncom=n;
2514: pcom=vector(1,n);
2515: xicom=vector(1,n);
2516: nrfunc=func;
2517: for (j=1;j<=n;j++) {
2518: pcom[j]=p[j];
1.202 brouard 2519: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2520: }
1.187 brouard 2521:
1.203 brouard 2522: #ifdef LINMINORIGINAL
2523: xx=1.;
2524: #else
2525: axs=0.0;
2526: xxs=1.;
2527: do{
2528: xx= xxs;
2529: #endif
1.187 brouard 2530: ax=0.;
2531: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2532: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2533: /* 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)) */
2534: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2535: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2536: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2537: /* 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 2538: #ifdef LINMINORIGINAL
2539: #else
2540: if (fx != fx){
1.224 brouard 2541: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2542: printf("|");
2543: fprintf(ficlog,"|");
1.203 brouard 2544: #ifdef DEBUGLINMIN
1.224 brouard 2545: 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 2546: #endif
2547: }
1.224 brouard 2548: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2549: #endif
2550:
1.191 brouard 2551: #ifdef DEBUGLINMIN
2552: 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 2553: 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 2554: #endif
1.224 brouard 2555: #ifdef LINMINORIGINAL
2556: #else
1.317 brouard 2557: if(fb == fx){ /* Flat function in the direction */
2558: xmin=xx;
1.224 brouard 2559: *flat=1;
1.317 brouard 2560: }else{
1.224 brouard 2561: *flat=0;
2562: #endif
2563: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2564: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2565: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2566: /* fmin = f(p[j] + xmin * xi[j]) */
2567: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2568: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2569: #ifdef DEBUG
1.224 brouard 2570: 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);
2571: 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);
2572: #endif
2573: #ifdef LINMINORIGINAL
2574: #else
2575: }
1.126 brouard 2576: #endif
1.191 brouard 2577: #ifdef DEBUGLINMIN
2578: printf("linmin end ");
1.202 brouard 2579: fprintf(ficlog,"linmin end ");
1.191 brouard 2580: #endif
1.126 brouard 2581: for (j=1;j<=n;j++) {
1.203 brouard 2582: #ifdef LINMINORIGINAL
2583: xi[j] *= xmin;
2584: #else
2585: #ifdef DEBUGLINMIN
2586: if(xxs <1.0)
2587: printf(" before xi[%d]=%12.8f", j,xi[j]);
2588: #endif
2589: 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) */
2590: #ifdef DEBUGLINMIN
2591: if(xxs <1.0)
2592: 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 );
2593: #endif
2594: #endif
1.187 brouard 2595: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2596: }
1.191 brouard 2597: #ifdef DEBUGLINMIN
1.203 brouard 2598: printf("\n");
1.191 brouard 2599: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2600: 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 2601: for (j=1;j<=n;j++) {
1.202 brouard 2602: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2603: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2604: if(j % ncovmodel == 0){
1.191 brouard 2605: printf("\n");
1.202 brouard 2606: fprintf(ficlog,"\n");
2607: }
1.191 brouard 2608: }
1.203 brouard 2609: #else
1.191 brouard 2610: #endif
1.126 brouard 2611: free_vector(xicom,1,n);
2612: free_vector(pcom,1,n);
2613: }
2614:
2615:
2616: /*************** powell ************************/
1.162 brouard 2617: /*
1.317 brouard 2618: Minimization of a function func of n variables. Input consists in an initial starting point
2619: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2620: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2621: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2622: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2623: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2624: */
1.224 brouard 2625: #ifdef LINMINORIGINAL
2626: #else
2627: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2628: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2629: #endif
1.126 brouard 2630: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2631: double (*func)(double []))
2632: {
1.224 brouard 2633: #ifdef LINMINORIGINAL
2634: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2635: double (*func)(double []));
1.224 brouard 2636: #else
1.241 brouard 2637: void linmin(double p[], double xi[], int n, double *fret,
2638: double (*func)(double []),int *flat);
1.224 brouard 2639: #endif
1.239 brouard 2640: int i,ibig,j,jk,k;
1.126 brouard 2641: double del,t,*pt,*ptt,*xit;
1.181 brouard 2642: double directest;
1.126 brouard 2643: double fp,fptt;
2644: double *xits;
2645: int niterf, itmp;
1.349 brouard 2646: int Bigter=0, nBigterf=1;
2647:
1.126 brouard 2648: pt=vector(1,n);
2649: ptt=vector(1,n);
2650: xit=vector(1,n);
2651: xits=vector(1,n);
2652: *fret=(*func)(p);
2653: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2654: rcurr_time = time(NULL);
2655: fp=(*fret); /* Initialisation */
1.126 brouard 2656: for (*iter=1;;++(*iter)) {
2657: ibig=0;
2658: del=0.0;
1.157 brouard 2659: rlast_time=rcurr_time;
1.349 brouard 2660: rlast_btime=rcurr_time;
1.157 brouard 2661: /* (void) gettimeofday(&curr_time,&tzp); */
2662: rcurr_time = time(NULL);
2663: curr_time = *localtime(&rcurr_time);
1.337 brouard 2664: /* 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); */
2665: /* 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 2666: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
2667: 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);
2668: 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);
2669: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2670: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2671: for (i=1;i<=n;i++) {
1.126 brouard 2672: fprintf(ficrespow," %.12lf", p[i]);
2673: }
1.239 brouard 2674: fprintf(ficrespow,"\n");fflush(ficrespow);
2675: printf("\n#model= 1 + age ");
2676: fprintf(ficlog,"\n#model= 1 + age ");
2677: if(nagesqr==1){
1.241 brouard 2678: printf(" + age*age ");
2679: fprintf(ficlog," + age*age ");
1.239 brouard 2680: }
2681: for(j=1;j <=ncovmodel-2;j++){
2682: if(Typevar[j]==0) {
2683: printf(" + V%d ",Tvar[j]);
2684: fprintf(ficlog," + V%d ",Tvar[j]);
2685: }else if(Typevar[j]==1) {
2686: printf(" + V%d*age ",Tvar[j]);
2687: fprintf(ficlog," + V%d*age ",Tvar[j]);
2688: }else if(Typevar[j]==2) {
2689: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2690: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 2691: }else if(Typevar[j]==3) {
2692: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2693: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2694: }
2695: }
1.126 brouard 2696: printf("\n");
1.239 brouard 2697: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2698: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2699: fprintf(ficlog,"\n");
1.239 brouard 2700: for(i=1,jk=1; i <=nlstate; i++){
2701: for(k=1; k <=(nlstate+ndeath); k++){
2702: if (k != i) {
2703: printf("%d%d ",i,k);
2704: fprintf(ficlog,"%d%d ",i,k);
2705: for(j=1; j <=ncovmodel; j++){
2706: printf("%12.7f ",p[jk]);
2707: fprintf(ficlog,"%12.7f ",p[jk]);
2708: jk++;
2709: }
2710: printf("\n");
2711: fprintf(ficlog,"\n");
2712: }
2713: }
2714: }
1.241 brouard 2715: if(*iter <=3 && *iter >1){
1.157 brouard 2716: tml = *localtime(&rcurr_time);
2717: strcpy(strcurr,asctime(&tml));
2718: rforecast_time=rcurr_time;
1.126 brouard 2719: itmp = strlen(strcurr);
2720: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2721: strcurr[itmp-1]='\0';
1.162 brouard 2722: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2723: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 2724: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
2725: niterf=nBigterf*ncovmodel;
2726: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2727: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2728: forecast_time = *localtime(&rforecast_time);
2729: strcpy(strfor,asctime(&forecast_time));
2730: itmp = strlen(strfor);
2731: if(strfor[itmp-1]=='\n')
2732: strfor[itmp-1]='\0';
1.349 brouard 2733: 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);
2734: 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 2735: }
2736: }
1.187 brouard 2737: for (i=1;i<=n;i++) { /* For each direction i */
2738: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2739: fptt=(*fret);
2740: #ifdef DEBUG
1.203 brouard 2741: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2742: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2743: #endif
1.203 brouard 2744: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2745: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2746: #ifdef LINMINORIGINAL
1.188 brouard 2747: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2748: #else
2749: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2750: flatdir[i]=flat; /* Function is vanishing in that direction i */
2751: #endif
2752: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2753: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2754: /* because that direction will be replaced unless the gain del is small */
2755: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2756: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2757: /* with the new direction. */
2758: del=fabs(fptt-(*fret));
2759: ibig=i;
1.126 brouard 2760: }
2761: #ifdef DEBUG
2762: printf("%d %.12e",i,(*fret));
2763: fprintf(ficlog,"%d %.12e",i,(*fret));
2764: for (j=1;j<=n;j++) {
1.224 brouard 2765: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2766: printf(" x(%d)=%.12e",j,xit[j]);
2767: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2768: }
2769: for(j=1;j<=n;j++) {
1.225 brouard 2770: printf(" p(%d)=%.12e",j,p[j]);
2771: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2772: }
2773: printf("\n");
2774: fprintf(ficlog,"\n");
2775: #endif
1.187 brouard 2776: } /* end loop on each direction i */
2777: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2778: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2779: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2780: for(j=1;j<=n;j++) {
2781: if(flatdir[j] >0){
2782: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2783: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2784: }
1.319 brouard 2785: /* printf("\n"); */
2786: /* fprintf(ficlog,"\n"); */
2787: }
1.243 brouard 2788: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2789: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2790: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2791: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2792: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2793: /* decreased of more than 3.84 */
2794: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2795: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2796: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2797:
1.188 brouard 2798: /* Starting the program with initial values given by a former maximization will simply change */
2799: /* the scales of the directions and the directions, because the are reset to canonical directions */
2800: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2801: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2802: #ifdef DEBUG
2803: int k[2],l;
2804: k[0]=1;
2805: k[1]=-1;
2806: printf("Max: %.12e",(*func)(p));
2807: fprintf(ficlog,"Max: %.12e",(*func)(p));
2808: for (j=1;j<=n;j++) {
2809: printf(" %.12e",p[j]);
2810: fprintf(ficlog," %.12e",p[j]);
2811: }
2812: printf("\n");
2813: fprintf(ficlog,"\n");
2814: for(l=0;l<=1;l++) {
2815: for (j=1;j<=n;j++) {
2816: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2817: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2818: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2819: }
2820: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2821: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2822: }
2823: #endif
2824:
2825: free_vector(xit,1,n);
2826: free_vector(xits,1,n);
2827: free_vector(ptt,1,n);
2828: free_vector(pt,1,n);
2829: return;
1.192 brouard 2830: } /* enough precision */
1.240 brouard 2831: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2832: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2833: ptt[j]=2.0*p[j]-pt[j];
2834: xit[j]=p[j]-pt[j];
2835: pt[j]=p[j];
2836: }
1.181 brouard 2837: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2838: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2839: if (*iter <=4) {
1.225 brouard 2840: #else
2841: #endif
1.224 brouard 2842: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2843: #else
1.161 brouard 2844: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2845: #endif
1.162 brouard 2846: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2847: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2848: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2849: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2850: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2851: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2852: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2853: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2854: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2855: /* Even if f3 <f1, directest can be negative and t >0 */
2856: /* mu² and del² are equal when f3=f1 */
2857: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2858: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2859: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2860: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2861: #ifdef NRCORIGINAL
2862: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2863: #else
2864: 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 2865: t= t- del*SQR(fp-fptt);
1.183 brouard 2866: #endif
1.202 brouard 2867: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2868: #ifdef DEBUG
1.181 brouard 2869: 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);
2870: 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 2871: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2872: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2873: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2874: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2875: 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);
2876: 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);
2877: #endif
1.183 brouard 2878: #ifdef POWELLORIGINAL
2879: if (t < 0.0) { /* Then we use it for new direction */
2880: #else
1.182 brouard 2881: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2882: 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 2883: 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 2884: 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 2885: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2886: }
1.181 brouard 2887: if (directest < 0.0) { /* Then we use it for new direction */
2888: #endif
1.191 brouard 2889: #ifdef DEBUGLINMIN
1.234 brouard 2890: printf("Before linmin in direction P%d-P0\n",n);
2891: for (j=1;j<=n;j++) {
2892: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2893: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2894: if(j % ncovmodel == 0){
2895: printf("\n");
2896: fprintf(ficlog,"\n");
2897: }
2898: }
1.224 brouard 2899: #endif
2900: #ifdef LINMINORIGINAL
1.234 brouard 2901: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2902: #else
1.234 brouard 2903: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2904: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2905: #endif
1.234 brouard 2906:
1.191 brouard 2907: #ifdef DEBUGLINMIN
1.234 brouard 2908: for (j=1;j<=n;j++) {
2909: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2910: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2911: if(j % ncovmodel == 0){
2912: printf("\n");
2913: fprintf(ficlog,"\n");
2914: }
2915: }
1.224 brouard 2916: #endif
1.234 brouard 2917: for (j=1;j<=n;j++) {
2918: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2919: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2920: }
1.224 brouard 2921: #ifdef LINMINORIGINAL
2922: #else
1.234 brouard 2923: for (j=1, flatd=0;j<=n;j++) {
2924: if(flatdir[j]>0)
2925: flatd++;
2926: }
2927: if(flatd >0){
1.255 brouard 2928: printf("%d flat directions: ",flatd);
2929: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2930: for (j=1;j<=n;j++) {
2931: if(flatdir[j]>0){
2932: printf("%d ",j);
2933: fprintf(ficlog,"%d ",j);
2934: }
2935: }
2936: printf("\n");
2937: fprintf(ficlog,"\n");
1.319 brouard 2938: #ifdef FLATSUP
2939: free_vector(xit,1,n);
2940: free_vector(xits,1,n);
2941: free_vector(ptt,1,n);
2942: free_vector(pt,1,n);
2943: return;
2944: #endif
1.234 brouard 2945: }
1.191 brouard 2946: #endif
1.234 brouard 2947: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2948: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2949:
1.126 brouard 2950: #ifdef DEBUG
1.234 brouard 2951: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2952: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2953: for(j=1;j<=n;j++){
2954: printf(" %lf",xit[j]);
2955: fprintf(ficlog," %lf",xit[j]);
2956: }
2957: printf("\n");
2958: fprintf(ficlog,"\n");
1.126 brouard 2959: #endif
1.192 brouard 2960: } /* end of t or directest negative */
1.224 brouard 2961: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2962: #else
1.234 brouard 2963: } /* end if (fptt < fp) */
1.192 brouard 2964: #endif
1.225 brouard 2965: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2966: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2967: #else
1.224 brouard 2968: #endif
1.234 brouard 2969: } /* loop iteration */
1.126 brouard 2970: }
1.234 brouard 2971:
1.126 brouard 2972: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2973:
1.235 brouard 2974: 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 2975: {
1.338 brouard 2976: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2977: * (and selected quantitative values in nres)
2978: * by left multiplying the unit
2979: * matrix by transitions matrix until convergence is reached with precision ftolpl
2980: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2981: * Wx is row vector: population in state 1, population in state 2, population dead
2982: * or prevalence in state 1, prevalence in state 2, 0
2983: * newm is the matrix after multiplications, its rows are identical at a factor.
2984: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2985: * Output is prlim.
2986: * Initial matrix pimij
2987: */
1.206 brouard 2988: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2989: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2990: /* 0, 0 , 1} */
2991: /*
2992: * and after some iteration: */
2993: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2994: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2995: /* 0, 0 , 1} */
2996: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2997: /* {0.51571254859325999, 0.4842874514067399, */
2998: /* 0.51326036147820708, 0.48673963852179264} */
2999: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 3000:
1.332 brouard 3001: int i, ii,j,k, k1;
1.209 brouard 3002: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 3003: /* double **matprod2(); */ /* test */
1.218 brouard 3004: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 3005: double **newm;
1.209 brouard 3006: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 3007: int ncvloop=0;
1.288 brouard 3008: int first=0;
1.169 brouard 3009:
1.209 brouard 3010: min=vector(1,nlstate);
3011: max=vector(1,nlstate);
3012: meandiff=vector(1,nlstate);
3013:
1.218 brouard 3014: /* Starting with matrix unity */
1.126 brouard 3015: for (ii=1;ii<=nlstate+ndeath;ii++)
3016: for (j=1;j<=nlstate+ndeath;j++){
3017: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3018: }
1.169 brouard 3019:
3020: cov[1]=1.;
3021:
3022: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 3023: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 3024: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 3025: ncvloop++;
1.126 brouard 3026: newm=savm;
3027: /* Covariates have to be included here again */
1.138 brouard 3028: cov[2]=agefin;
1.319 brouard 3029: if(nagesqr==1){
3030: cov[3]= agefin*agefin;
3031: }
1.332 brouard 3032: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3033: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3034: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3035: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3036: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3037: }else{
3038: cov[2+nagesqr+k1]=precov[nres][k1];
3039: }
3040: }/* End of loop on model equation */
3041:
3042: /* Start of old code (replaced by a loop on position in the model equation */
3043: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3044: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3045: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3046: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3047: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3048: /* * k 1 2 3 4 5 6 7 8 */
3049: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3050: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3051: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3052: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3053: /* *nsd=3 (1) (2) (3) */
3054: /* *TvarsD[nsd] [1]=2 1 3 */
3055: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3056: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3057: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3058: /* *Tvard[] [1][1]=1 [2][1]=1 */
3059: /* * [1][2]=3 [2][2]=2 */
3060: /* *Tprod[](=k) [1]=1 [2]=8 */
3061: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3062: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3063: /* *TvarsDpType */
3064: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3065: /* * nsd=1 (1) (2) */
3066: /* *TvarsD[nsd] 3 2 */
3067: /* *TnsdVar (3)=1 (2)=2 */
3068: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3069: /* *Tage[] [1]=2 [2]= 3 */
3070: /* *\/ */
3071: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3072: /* /\* 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)); *\/ */
3073: /* } */
3074: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3075: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3076: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3077: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3078: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3079: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3080: /* /\* 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]); *\/ */
3081: /* } */
3082: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3083: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3084: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3085: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3086: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3087: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3088: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3089: /* } */
3090: /* /\* 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]); *\/ */
3091: /* } */
3092: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3093: /* /\* 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]); *\/ */
3094: /* if(Dummy[Tvard[k][1]]==0){ */
3095: /* if(Dummy[Tvard[k][2]]==0){ */
3096: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3097: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3098: /* }else{ */
3099: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3100: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3101: /* } */
3102: /* }else{ */
3103: /* if(Dummy[Tvard[k][2]]==0){ */
3104: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3105: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3106: /* }else{ */
3107: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3108: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3109: /* } */
3110: /* } */
3111: /* } /\* End product without age *\/ */
3112: /* ENd of old code */
1.138 brouard 3113: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3114: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3115: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3116: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3117: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3118: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3119: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3120:
1.126 brouard 3121: savm=oldm;
3122: oldm=newm;
1.209 brouard 3123:
3124: for(j=1; j<=nlstate; j++){
3125: max[j]=0.;
3126: min[j]=1.;
3127: }
3128: for(i=1;i<=nlstate;i++){
3129: sumnew=0;
3130: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3131: for(j=1; j<=nlstate; j++){
3132: prlim[i][j]= newm[i][j]/(1-sumnew);
3133: max[j]=FMAX(max[j],prlim[i][j]);
3134: min[j]=FMIN(min[j],prlim[i][j]);
3135: }
3136: }
3137:
1.126 brouard 3138: maxmax=0.;
1.209 brouard 3139: for(j=1; j<=nlstate; j++){
3140: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3141: maxmax=FMAX(maxmax,meandiff[j]);
3142: /* 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 3143: } /* j loop */
1.203 brouard 3144: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3145: /* 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 3146: if(maxmax < ftolpl){
1.209 brouard 3147: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3148: free_vector(min,1,nlstate);
3149: free_vector(max,1,nlstate);
3150: free_vector(meandiff,1,nlstate);
1.126 brouard 3151: return prlim;
3152: }
1.288 brouard 3153: } /* agefin loop */
1.208 brouard 3154: /* After some age loop it doesn't converge */
1.288 brouard 3155: if(!first){
3156: first=1;
3157: 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 3158: 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);
3159: }else if (first >=1 && first <10){
3160: 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);
3161: first++;
3162: }else if (first ==10){
3163: 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);
3164: 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");
3165: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3166: first++;
1.288 brouard 3167: }
3168:
1.209 brouard 3169: /* 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); */
3170: free_vector(min,1,nlstate);
3171: free_vector(max,1,nlstate);
3172: free_vector(meandiff,1,nlstate);
1.208 brouard 3173:
1.169 brouard 3174: return prlim; /* should not reach here */
1.126 brouard 3175: }
3176:
1.217 brouard 3177:
3178: /**** Back Prevalence limit (stable or period prevalence) ****************/
3179:
1.218 brouard 3180: /* 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) */
3181: /* 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 3182: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3183: {
1.264 brouard 3184: /* 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 3185: matrix by transitions matrix until convergence is reached with precision ftolpl */
3186: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3187: /* Wx is row vector: population in state 1, population in state 2, population dead */
3188: /* or prevalence in state 1, prevalence in state 2, 0 */
3189: /* newm is the matrix after multiplications, its rows are identical at a factor */
3190: /* Initial matrix pimij */
3191: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3192: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3193: /* 0, 0 , 1} */
3194: /*
3195: * and after some iteration: */
3196: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3197: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3198: /* 0, 0 , 1} */
3199: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3200: /* {0.51571254859325999, 0.4842874514067399, */
3201: /* 0.51326036147820708, 0.48673963852179264} */
3202: /* If we start from prlim again, prlim tends to a constant matrix */
3203:
1.332 brouard 3204: int i, ii,j,k, k1;
1.247 brouard 3205: int first=0;
1.217 brouard 3206: double *min, *max, *meandiff, maxmax,sumnew=0.;
3207: /* double **matprod2(); */ /* test */
3208: double **out, cov[NCOVMAX+1], **bmij();
3209: double **newm;
1.218 brouard 3210: double **dnewm, **doldm, **dsavm; /* for use */
3211: double **oldm, **savm; /* for use */
3212:
1.217 brouard 3213: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3214: int ncvloop=0;
3215:
3216: min=vector(1,nlstate);
3217: max=vector(1,nlstate);
3218: meandiff=vector(1,nlstate);
3219:
1.266 brouard 3220: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3221: oldm=oldms; savm=savms;
3222:
3223: /* Starting with matrix unity */
3224: for (ii=1;ii<=nlstate+ndeath;ii++)
3225: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3226: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3227: }
3228:
3229: cov[1]=1.;
3230:
3231: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3232: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3233: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3234: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3235: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3236: ncvloop++;
1.218 brouard 3237: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3238: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3239: /* Covariates have to be included here again */
3240: cov[2]=agefin;
1.319 brouard 3241: if(nagesqr==1){
1.217 brouard 3242: cov[3]= agefin*agefin;;
1.319 brouard 3243: }
1.332 brouard 3244: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3245: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3246: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3247: }else{
1.332 brouard 3248: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3249: }
1.332 brouard 3250: }/* End of loop on model equation */
3251:
3252: /* Old code */
3253:
3254: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3255: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3256: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3257: /* /\* 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)); *\/ */
3258: /* } */
3259: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3260: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3261: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3262: /* /\* /\\* 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])]); *\\/ *\/ */
3263: /* /\* } *\/ */
3264: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3265: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3266: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3267: /* /\* 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]); *\/ */
3268: /* } */
3269: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3270: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3271: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3272: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3273: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3274: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3275: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3276: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3277: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3278: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3279: /* } */
3280: /* /\* 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]); *\/ */
3281: /* } */
3282: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3283: /* /\* 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]); *\/ */
3284: /* if(Dummy[Tvard[k][1]]==0){ */
3285: /* if(Dummy[Tvard[k][2]]==0){ */
3286: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3287: /* }else{ */
3288: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3289: /* } */
3290: /* }else{ */
3291: /* if(Dummy[Tvard[k][2]]==0){ */
3292: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3293: /* }else{ */
3294: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3295: /* } */
3296: /* } */
3297: /* } */
1.217 brouard 3298:
3299: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3300: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3301: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3302: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3303: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3304: /* ij should be linked to the correct index of cov */
3305: /* age and covariate values ij are in 'cov', but we need to pass
3306: * ij for the observed prevalence at age and status and covariate
3307: * number: prevacurrent[(int)agefin][ii][ij]
3308: */
3309: /* 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 *\/ */
3310: /* 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 *\/ */
3311: 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 3312: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3313: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3314: /* for(i=1; i<=nlstate+ndeath; i++) { */
3315: /* printf("%d newm= ",i); */
3316: /* for(j=1;j<=nlstate+ndeath;j++) { */
3317: /* printf("%f ",newm[i][j]); */
3318: /* } */
3319: /* printf("oldm * "); */
3320: /* for(j=1;j<=nlstate+ndeath;j++) { */
3321: /* printf("%f ",oldm[i][j]); */
3322: /* } */
1.268 brouard 3323: /* printf(" bmmij "); */
1.266 brouard 3324: /* for(j=1;j<=nlstate+ndeath;j++) { */
3325: /* printf("%f ",pmmij[i][j]); */
3326: /* } */
3327: /* printf("\n"); */
3328: /* } */
3329: /* } */
1.217 brouard 3330: savm=oldm;
3331: oldm=newm;
1.266 brouard 3332:
1.217 brouard 3333: for(j=1; j<=nlstate; j++){
3334: max[j]=0.;
3335: min[j]=1.;
3336: }
3337: for(j=1; j<=nlstate; j++){
3338: for(i=1;i<=nlstate;i++){
1.234 brouard 3339: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3340: bprlim[i][j]= newm[i][j];
3341: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3342: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3343: }
3344: }
1.218 brouard 3345:
1.217 brouard 3346: maxmax=0.;
3347: for(i=1; i<=nlstate; i++){
1.318 brouard 3348: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3349: maxmax=FMAX(maxmax,meandiff[i]);
3350: /* 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 3351: } /* i loop */
1.217 brouard 3352: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3353: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3354: if(maxmax < ftolpl){
1.220 brouard 3355: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3356: free_vector(min,1,nlstate);
3357: free_vector(max,1,nlstate);
3358: free_vector(meandiff,1,nlstate);
3359: return bprlim;
3360: }
1.288 brouard 3361: } /* agefin loop */
1.217 brouard 3362: /* After some age loop it doesn't converge */
1.288 brouard 3363: if(!first){
1.247 brouard 3364: first=1;
3365: 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\
3366: 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);
3367: }
3368: 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 3369: 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);
3370: /* 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); */
3371: free_vector(min,1,nlstate);
3372: free_vector(max,1,nlstate);
3373: free_vector(meandiff,1,nlstate);
3374:
3375: return bprlim; /* should not reach here */
3376: }
3377:
1.126 brouard 3378: /*************** transition probabilities ***************/
3379:
3380: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3381: {
1.138 brouard 3382: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3383: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3384: model to the ncovmodel covariates (including constant and age).
3385: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3386: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3387: ncth covariate in the global vector x is given by the formula:
3388: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3389: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3390: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3391: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3392: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3393: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3394: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3395: */
3396: double s1, lnpijopii;
1.126 brouard 3397: /*double t34;*/
1.164 brouard 3398: int i,j, nc, ii, jj;
1.126 brouard 3399:
1.223 brouard 3400: for(i=1; i<= nlstate; i++){
3401: for(j=1; j<i;j++){
3402: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3403: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3404: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3405: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3406: }
3407: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3408: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3409: }
3410: for(j=i+1; j<=nlstate+ndeath;j++){
3411: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3412: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3413: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3414: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3415: }
3416: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3417: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3418: }
3419: }
1.218 brouard 3420:
1.223 brouard 3421: for(i=1; i<= nlstate; i++){
3422: s1=0;
3423: for(j=1; j<i; j++){
1.339 brouard 3424: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3425: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3426: }
3427: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3428: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3429: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3430: }
3431: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3432: ps[i][i]=1./(s1+1.);
3433: /* Computing other pijs */
3434: for(j=1; j<i; j++)
1.325 brouard 3435: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3436: for(j=i+1; j<=nlstate+ndeath; j++)
3437: ps[i][j]= exp(ps[i][j])*ps[i][i];
3438: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3439: } /* end i */
1.218 brouard 3440:
1.223 brouard 3441: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3442: for(jj=1; jj<= nlstate+ndeath; jj++){
3443: ps[ii][jj]=0;
3444: ps[ii][ii]=1;
3445: }
3446: }
1.294 brouard 3447:
3448:
1.223 brouard 3449: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3450: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3451: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3452: /* } */
3453: /* printf("\n "); */
3454: /* } */
3455: /* printf("\n ");printf("%lf ",cov[2]);*/
3456: /*
3457: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3458: goto end;*/
1.266 brouard 3459: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3460: }
3461:
1.218 brouard 3462: /*************** backward transition probabilities ***************/
3463:
3464: /* 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 ) */
3465: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3466: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3467: {
1.302 brouard 3468: /* 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 3469: * 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 3470: */
1.218 brouard 3471: int i, ii, j,k;
1.222 brouard 3472:
3473: double **out, **pmij();
3474: double sumnew=0.;
1.218 brouard 3475: double agefin;
1.292 brouard 3476: 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 3477: double **dnewm, **dsavm, **doldm;
3478: double **bbmij;
3479:
1.218 brouard 3480: doldm=ddoldms; /* global pointers */
1.222 brouard 3481: dnewm=ddnewms;
3482: dsavm=ddsavms;
1.318 brouard 3483:
3484: /* Debug */
3485: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3486: agefin=cov[2];
1.268 brouard 3487: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3488: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3489: the observed prevalence (with this covariate ij) at beginning of transition */
3490: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3491:
3492: /* P_x */
1.325 brouard 3493: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3494: /* outputs pmmij which is a stochastic matrix in row */
3495:
3496: /* Diag(w_x) */
1.292 brouard 3497: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3498: sumnew=0.;
1.269 brouard 3499: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3500: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3501: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3502: sumnew+=prevacurrent[(int)agefin][ii][ij];
3503: }
3504: if(sumnew >0.01){ /* At least some value in the prevalence */
3505: for (ii=1;ii<=nlstate+ndeath;ii++){
3506: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3507: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3508: }
3509: }else{
3510: for (ii=1;ii<=nlstate+ndeath;ii++){
3511: for (j=1;j<=nlstate+ndeath;j++)
3512: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3513: }
3514: /* if(sumnew <0.9){ */
3515: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3516: /* } */
3517: }
3518: k3=0.0; /* We put the last diagonal to 0 */
3519: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3520: doldm[ii][ii]= k3;
3521: }
3522: /* End doldm, At the end doldm is diag[(w_i)] */
3523:
1.292 brouard 3524: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3525: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3526:
1.292 brouard 3527: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3528: /* 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 3529: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3530: sumnew=0.;
1.222 brouard 3531: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3532: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3533: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3534: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3535: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3536: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3537: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3538: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3539: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3540: /* }else */
1.268 brouard 3541: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3542: } /*End ii */
3543: } /* 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 */
3544:
1.292 brouard 3545: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3546: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3547: /* end bmij */
1.266 brouard 3548: return ps; /*pointer is unchanged */
1.218 brouard 3549: }
1.217 brouard 3550: /*************** transition probabilities ***************/
3551:
1.218 brouard 3552: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3553: {
3554: /* According to parameters values stored in x and the covariate's values stored in cov,
3555: computes the probability to be observed in state j being in state i by appying the
3556: model to the ncovmodel covariates (including constant and age).
3557: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3558: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3559: ncth covariate in the global vector x is given by the formula:
3560: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3561: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3562: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3563: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3564: Outputs ps[i][j] the probability to be observed in j being in j according to
3565: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3566: */
3567: double s1, lnpijopii;
3568: /*double t34;*/
3569: int i,j, nc, ii, jj;
3570:
1.234 brouard 3571: for(i=1; i<= nlstate; i++){
3572: for(j=1; j<i;j++){
3573: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3574: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3575: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3576: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3577: }
3578: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3579: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3580: }
3581: for(j=i+1; j<=nlstate+ndeath;j++){
3582: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3583: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3584: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3585: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3586: }
3587: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3588: }
3589: }
3590:
3591: for(i=1; i<= nlstate; i++){
3592: s1=0;
3593: for(j=1; j<i; j++){
3594: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3595: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3596: }
3597: for(j=i+1; j<=nlstate+ndeath; j++){
3598: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3599: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3600: }
3601: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3602: ps[i][i]=1./(s1+1.);
3603: /* Computing other pijs */
3604: for(j=1; j<i; j++)
3605: ps[i][j]= exp(ps[i][j])*ps[i][i];
3606: for(j=i+1; j<=nlstate+ndeath; j++)
3607: ps[i][j]= exp(ps[i][j])*ps[i][i];
3608: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3609: } /* end i */
3610:
3611: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3612: for(jj=1; jj<= nlstate+ndeath; jj++){
3613: ps[ii][jj]=0;
3614: ps[ii][ii]=1;
3615: }
3616: }
1.296 brouard 3617: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3618: for(jj=1; jj<= nlstate+ndeath; jj++){
3619: s1=0.;
3620: for(ii=1; ii<= nlstate+ndeath; ii++){
3621: s1+=ps[ii][jj];
3622: }
3623: for(ii=1; ii<= nlstate; ii++){
3624: ps[ii][jj]=ps[ii][jj]/s1;
3625: }
3626: }
3627: /* Transposition */
3628: for(jj=1; jj<= nlstate+ndeath; jj++){
3629: for(ii=jj; ii<= nlstate+ndeath; ii++){
3630: s1=ps[ii][jj];
3631: ps[ii][jj]=ps[jj][ii];
3632: ps[jj][ii]=s1;
3633: }
3634: }
3635: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3636: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3637: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3638: /* } */
3639: /* printf("\n "); */
3640: /* } */
3641: /* printf("\n ");printf("%lf ",cov[2]);*/
3642: /*
3643: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3644: goto end;*/
3645: return ps;
1.217 brouard 3646: }
3647:
3648:
1.126 brouard 3649: /**************** Product of 2 matrices ******************/
3650:
1.145 brouard 3651: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3652: {
3653: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3654: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3655: /* in, b, out are matrice of pointers which should have been initialized
3656: before: only the contents of out is modified. The function returns
3657: a pointer to pointers identical to out */
1.145 brouard 3658: int i, j, k;
1.126 brouard 3659: for(i=nrl; i<= nrh; i++)
1.145 brouard 3660: for(k=ncolol; k<=ncoloh; k++){
3661: out[i][k]=0.;
3662: for(j=ncl; j<=nch; j++)
3663: out[i][k] +=in[i][j]*b[j][k];
3664: }
1.126 brouard 3665: return out;
3666: }
3667:
3668:
3669: /************* Higher Matrix Product ***************/
3670:
1.235 brouard 3671: 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 3672: {
1.336 brouard 3673: /* Already optimized with precov.
3674: 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 3675: 'nhstepm*hstepm*stepm' months (i.e. until
3676: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3677: nhstepm*hstepm matrices.
3678: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3679: (typically every 2 years instead of every month which is too big
3680: for the memory).
3681: Model is determined by parameters x and covariates have to be
3682: included manually here.
3683:
3684: */
3685:
1.330 brouard 3686: int i, j, d, h, k, k1;
1.131 brouard 3687: double **out, cov[NCOVMAX+1];
1.126 brouard 3688: double **newm;
1.187 brouard 3689: double agexact;
1.214 brouard 3690: double agebegin, ageend;
1.126 brouard 3691:
3692: /* Hstepm could be zero and should return the unit matrix */
3693: for (i=1;i<=nlstate+ndeath;i++)
3694: for (j=1;j<=nlstate+ndeath;j++){
3695: oldm[i][j]=(i==j ? 1.0 : 0.0);
3696: po[i][j][0]=(i==j ? 1.0 : 0.0);
3697: }
3698: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3699: for(h=1; h <=nhstepm; h++){
3700: for(d=1; d <=hstepm; d++){
3701: newm=savm;
3702: /* Covariates have to be included here again */
3703: cov[1]=1.;
1.214 brouard 3704: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3705: cov[2]=agexact;
1.319 brouard 3706: if(nagesqr==1){
1.227 brouard 3707: cov[3]= agexact*agexact;
1.319 brouard 3708: }
1.330 brouard 3709: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3710: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3711: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3712: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3713: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3714: }else{
3715: cov[2+nagesqr+k1]=precov[nres][k1];
3716: }
3717: }/* End of loop on model equation */
3718: /* Old code */
3719: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3720: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3721: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3722: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3723: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3724: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3725: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3726: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3727: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3728: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3729: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3730: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3731: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3732: /* /\* 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]])); *\/ */
3733: /* 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); */
3734: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3735: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3736: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3737: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3738: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3739: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3740: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3741: /* 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]]); */
3742: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3743: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3744: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3745: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3746: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3747: /* 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]); */
3748: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3749:
3750: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3751: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3752: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3753: /* /\* *\/ */
1.330 brouard 3754: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3755: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3756: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3757: /* /\*cptcovage=2 1 2 *\/ */
3758: /* /\*Tage[k]= 5 8 *\/ */
3759: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3760: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3761: /* 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]]); */
3762: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3763: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3764: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3765: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3766: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3767: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3768: /* /\* 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); *\/ */
3769: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3770: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3771: /* /\* } *\/ */
3772: /* /\* 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]); *\/ */
3773: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3774: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3775: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3776: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3777: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3778: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3779: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3780: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3781: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3782:
1.332 brouard 3783: /* /\* 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])]); *\/ */
3784: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3785: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3786: /* 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]]); */
3787: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3788:
3789: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3790: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3791: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3792: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3793: /* /\* 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]])]; *\/ */
3794: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3795: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3796: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3797: /* /\* } *\/ */
3798: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3799: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3800: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3801: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3802: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3803: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3804: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3805: /* /\* } *\/ */
3806: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3807: /* }/\*end of products *\/ */
3808: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3809: /* for (k=1; k<=cptcovn;k++) */
3810: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3811: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3812: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3813: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3814: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3815:
3816:
1.126 brouard 3817: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3818: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3819: /* right multiplication of oldm by the current matrix */
1.126 brouard 3820: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3821: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3822: /* if((int)age == 70){ */
3823: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3824: /* for(i=1; i<=nlstate+ndeath; i++) { */
3825: /* printf("%d pmmij ",i); */
3826: /* for(j=1;j<=nlstate+ndeath;j++) { */
3827: /* printf("%f ",pmmij[i][j]); */
3828: /* } */
3829: /* printf(" oldm "); */
3830: /* for(j=1;j<=nlstate+ndeath;j++) { */
3831: /* printf("%f ",oldm[i][j]); */
3832: /* } */
3833: /* printf("\n"); */
3834: /* } */
3835: /* } */
1.126 brouard 3836: savm=oldm;
3837: oldm=newm;
3838: }
3839: for(i=1; i<=nlstate+ndeath; i++)
3840: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3841: po[i][j][h]=newm[i][j];
3842: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3843: }
1.128 brouard 3844: /*printf("h=%d ",h);*/
1.126 brouard 3845: } /* end h */
1.267 brouard 3846: /* printf("\n H=%d \n",h); */
1.126 brouard 3847: return po;
3848: }
3849:
1.217 brouard 3850: /************* Higher Back Matrix Product ***************/
1.218 brouard 3851: /* 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 3852: 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 3853: {
1.332 brouard 3854: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3855: computes the transition matrix starting at age 'age' over
1.217 brouard 3856: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3857: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3858: nhstepm*hstepm matrices.
3859: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3860: (typically every 2 years instead of every month which is too big
1.217 brouard 3861: for the memory).
1.218 brouard 3862: Model is determined by parameters x and covariates have to be
1.266 brouard 3863: included manually here. Then we use a call to bmij(x and cov)
3864: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3865: */
1.217 brouard 3866:
1.332 brouard 3867: int i, j, d, h, k, k1;
1.266 brouard 3868: double **out, cov[NCOVMAX+1], **bmij();
3869: double **newm, ***newmm;
1.217 brouard 3870: double agexact;
3871: double agebegin, ageend;
1.222 brouard 3872: double **oldm, **savm;
1.217 brouard 3873:
1.266 brouard 3874: newmm=po; /* To be saved */
3875: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3876: /* Hstepm could be zero and should return the unit matrix */
3877: for (i=1;i<=nlstate+ndeath;i++)
3878: for (j=1;j<=nlstate+ndeath;j++){
3879: oldm[i][j]=(i==j ? 1.0 : 0.0);
3880: po[i][j][0]=(i==j ? 1.0 : 0.0);
3881: }
3882: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3883: for(h=1; h <=nhstepm; h++){
3884: for(d=1; d <=hstepm; d++){
3885: newm=savm;
3886: /* Covariates have to be included here again */
3887: cov[1]=1.;
1.271 brouard 3888: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3889: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3890: /* Debug */
3891: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3892: cov[2]=agexact;
1.332 brouard 3893: if(nagesqr==1){
1.222 brouard 3894: cov[3]= agexact*agexact;
1.332 brouard 3895: }
3896: /** New code */
3897: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3898: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3899: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3900: }else{
1.332 brouard 3901: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3902: }
1.332 brouard 3903: }/* End of loop on model equation */
3904: /** End of new code */
3905: /** This was old code */
3906: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3907: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3908: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3909: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3910: /* /\* 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)); *\/ */
3911: /* } */
3912: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3913: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3914: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3915: /* /\* 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]); *\/ */
3916: /* } */
3917: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3918: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3919: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3920: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3921: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3922: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3923: /* } */
3924: /* /\* 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]); *\/ */
3925: /* } */
3926: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3927: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3928: /* if(Dummy[Tvard[k][1]]==0){ */
3929: /* if(Dummy[Tvard[k][2]]==0){ */
3930: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3931: /* }else{ */
3932: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3933: /* } */
3934: /* }else{ */
3935: /* if(Dummy[Tvard[k][2]]==0){ */
3936: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3937: /* }else{ */
3938: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3939: /* } */
3940: /* } */
3941: /* } */
3942: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3943: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3944: /** End of old code */
3945:
1.218 brouard 3946: /* Careful transposed matrix */
1.266 brouard 3947: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3948: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3949: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3950: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3951: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3952: /* if((int)age == 70){ */
3953: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3954: /* for(i=1; i<=nlstate+ndeath; i++) { */
3955: /* printf("%d pmmij ",i); */
3956: /* for(j=1;j<=nlstate+ndeath;j++) { */
3957: /* printf("%f ",pmmij[i][j]); */
3958: /* } */
3959: /* printf(" oldm "); */
3960: /* for(j=1;j<=nlstate+ndeath;j++) { */
3961: /* printf("%f ",oldm[i][j]); */
3962: /* } */
3963: /* printf("\n"); */
3964: /* } */
3965: /* } */
3966: savm=oldm;
3967: oldm=newm;
3968: }
3969: for(i=1; i<=nlstate+ndeath; i++)
3970: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3971: po[i][j][h]=newm[i][j];
1.268 brouard 3972: /* if(h==nhstepm) */
3973: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3974: }
1.268 brouard 3975: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3976: } /* end h */
1.268 brouard 3977: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3978: return po;
3979: }
3980:
3981:
1.162 brouard 3982: #ifdef NLOPT
3983: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3984: double fret;
3985: double *xt;
3986: int j;
3987: myfunc_data *d2 = (myfunc_data *) pd;
3988: /* xt = (p1-1); */
3989: xt=vector(1,n);
3990: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3991:
3992: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3993: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3994: printf("Function = %.12lf ",fret);
3995: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3996: printf("\n");
3997: free_vector(xt,1,n);
3998: return fret;
3999: }
4000: #endif
1.126 brouard 4001:
4002: /*************** log-likelihood *************/
4003: double func( double *x)
4004: {
1.336 brouard 4005: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 4006: int ioffset=0;
1.339 brouard 4007: int ipos=0,iposold=0,ncovv=0;
4008:
1.340 brouard 4009: double cotvarv, cotvarvold;
1.226 brouard 4010: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
4011: double **out;
4012: double lli; /* Individual log likelihood */
4013: int s1, s2;
1.228 brouard 4014: 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 4015:
1.226 brouard 4016: double bbh, survp;
4017: double agexact;
1.336 brouard 4018: double agebegin, ageend;
1.226 brouard 4019: /*extern weight */
4020: /* We are differentiating ll according to initial status */
4021: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4022: /*for(i=1;i<imx;i++)
4023: printf(" %d\n",s[4][i]);
4024: */
1.162 brouard 4025:
1.226 brouard 4026: ++countcallfunc;
1.162 brouard 4027:
1.226 brouard 4028: cov[1]=1.;
1.126 brouard 4029:
1.226 brouard 4030: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4031: ioffset=0;
1.226 brouard 4032: if(mle==1){
4033: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4034: /* Computes the values of the ncovmodel covariates of the model
4035: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4036: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4037: to be observed in j being in i according to the model.
4038: */
1.243 brouard 4039: ioffset=2+nagesqr ;
1.233 brouard 4040: /* Fixed */
1.345 brouard 4041: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4042: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4043: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4044: /* 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 4045: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4046: 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 4047: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4048: }
1.226 brouard 4049: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4050: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4051: has been calculated etc */
4052: /* For an individual i, wav[i] gives the number of effective waves */
4053: /* We compute the contribution to Likelihood of each effective transition
4054: mw[mi][i] is real wave of the mi th effectve wave */
4055: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4056: s2=s[mw[mi+1][i]][i];
1.341 brouard 4057: 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 4058: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4059: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4060: */
1.336 brouard 4061: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4062: /* Wave varying (but not age varying) */
1.339 brouard 4063: /* 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*\/ */
4064: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4065: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4066: /* } */
1.340 brouard 4067: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4068: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4069: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4070: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4071: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4072: }else{ /* fixed covariate */
1.345 brouard 4073: 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 4074: }
1.339 brouard 4075: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4076: cotvarvold=cotvarv;
4077: }else{ /* A second product */
4078: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4079: }
4080: iposold=ipos;
1.340 brouard 4081: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4082: }
1.339 brouard 4083: /* for products of time varying to be done */
1.234 brouard 4084: for (ii=1;ii<=nlstate+ndeath;ii++)
4085: for (j=1;j<=nlstate+ndeath;j++){
4086: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4087: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4088: }
1.336 brouard 4089:
4090: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4091: 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 4092: for(d=0; d<dh[mi][i]; d++){
4093: newm=savm;
4094: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4095: cov[2]=agexact;
4096: if(nagesqr==1)
4097: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 4098: /* for (kk=1; kk<=cptcovage;kk++) { */
4099: /* if(!FixedV[Tvar[Tage[kk]]]) */
4100: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
4101: /* else */
4102: /* 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) *\/ */
4103: /* } */
4104: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4105: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4106: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4107: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4108: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4109: }else{ /* fixed covariate */
4110: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4111: }
4112: if(ipos!=iposold){ /* Not a product or first of a product */
4113: cotvarvold=cotvarv;
4114: }else{ /* A second product */
4115: cotvarv=cotvarv*cotvarvold;
4116: }
4117: iposold=ipos;
4118: cov[ioffset+ipos]=cotvarv*agexact;
4119: /* For products */
1.234 brouard 4120: }
1.349 brouard 4121:
1.234 brouard 4122: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4123: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4124: savm=oldm;
4125: oldm=newm;
4126: } /* end mult */
4127:
4128: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4129: /* But now since version 0.9 we anticipate for bias at large stepm.
4130: * If stepm is larger than one month (smallest stepm) and if the exact delay
4131: * (in months) between two waves is not a multiple of stepm, we rounded to
4132: * the nearest (and in case of equal distance, to the lowest) interval but now
4133: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4134: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4135: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4136: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4137: * -stepm/2 to stepm/2 .
4138: * For stepm=1 the results are the same as for previous versions of Imach.
4139: * For stepm > 1 the results are less biased than in previous versions.
4140: */
1.234 brouard 4141: s1=s[mw[mi][i]][i];
4142: s2=s[mw[mi+1][i]][i];
4143: bbh=(double)bh[mi][i]/(double)stepm;
4144: /* bias bh is positive if real duration
4145: * is higher than the multiple of stepm and negative otherwise.
4146: */
4147: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4148: if( s2 > nlstate){
4149: /* i.e. if s2 is a death state and if the date of death is known
4150: then the contribution to the likelihood is the probability to
4151: die between last step unit time and current step unit time,
4152: which is also equal to probability to die before dh
4153: minus probability to die before dh-stepm .
4154: In version up to 0.92 likelihood was computed
4155: as if date of death was unknown. Death was treated as any other
4156: health state: the date of the interview describes the actual state
4157: and not the date of a change in health state. The former idea was
4158: to consider that at each interview the state was recorded
4159: (healthy, disable or death) and IMaCh was corrected; but when we
4160: introduced the exact date of death then we should have modified
4161: the contribution of an exact death to the likelihood. This new
4162: contribution is smaller and very dependent of the step unit
4163: stepm. It is no more the probability to die between last interview
4164: and month of death but the probability to survive from last
4165: interview up to one month before death multiplied by the
4166: probability to die within a month. Thanks to Chris
4167: Jackson for correcting this bug. Former versions increased
4168: mortality artificially. The bad side is that we add another loop
4169: which slows down the processing. The difference can be up to 10%
4170: lower mortality.
4171: */
4172: /* If, at the beginning of the maximization mostly, the
4173: cumulative probability or probability to be dead is
4174: constant (ie = 1) over time d, the difference is equal to
4175: 0. out[s1][3] = savm[s1][3]: probability, being at state
4176: s1 at precedent wave, to be dead a month before current
4177: wave is equal to probability, being at state s1 at
4178: precedent wave, to be dead at mont of the current
4179: wave. Then the observed probability (that this person died)
4180: is null according to current estimated parameter. In fact,
4181: it should be very low but not zero otherwise the log go to
4182: infinity.
4183: */
1.183 brouard 4184: /* #ifdef INFINITYORIGINAL */
4185: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4186: /* #else */
4187: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4188: /* lli=log(mytinydouble); */
4189: /* else */
4190: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4191: /* #endif */
1.226 brouard 4192: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4193:
1.226 brouard 4194: } else if ( s2==-1 ) { /* alive */
4195: for (j=1,survp=0. ; j<=nlstate; j++)
4196: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4197: /*survp += out[s1][j]; */
4198: lli= log(survp);
4199: }
1.336 brouard 4200: /* else if (s2==-4) { */
4201: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4202: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4203: /* lli= log(survp); */
4204: /* } */
4205: /* else if (s2==-5) { */
4206: /* for (j=1,survp=0. ; j<=2; j++) */
4207: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4208: /* lli= log(survp); */
4209: /* } */
1.226 brouard 4210: else{
4211: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4212: /* 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 */
4213: }
4214: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4215: /*if(lli ==000.0)*/
1.340 brouard 4216: /* 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 4217: ipmx +=1;
4218: sw += weight[i];
4219: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4220: /* if (lli < log(mytinydouble)){ */
4221: /* 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); */
4222: /* 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]); */
4223: /* } */
4224: } /* end of wave */
4225: } /* end of individual */
4226: } else if(mle==2){
4227: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4228: ioffset=2+nagesqr ;
4229: for (k=1; k<=ncovf;k++)
4230: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4231: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4232: for(k=1; k <= ncovv ; k++){
1.341 brouard 4233: 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 4234: }
1.226 brouard 4235: for (ii=1;ii<=nlstate+ndeath;ii++)
4236: for (j=1;j<=nlstate+ndeath;j++){
4237: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4238: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4239: }
4240: for(d=0; d<=dh[mi][i]; d++){
4241: newm=savm;
4242: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4243: cov[2]=agexact;
4244: if(nagesqr==1)
4245: cov[3]= agexact*agexact;
4246: for (kk=1; kk<=cptcovage;kk++) {
4247: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4248: }
4249: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4250: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4251: savm=oldm;
4252: oldm=newm;
4253: } /* end mult */
4254:
4255: s1=s[mw[mi][i]][i];
4256: s2=s[mw[mi+1][i]][i];
4257: bbh=(double)bh[mi][i]/(double)stepm;
4258: 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 */
4259: ipmx +=1;
4260: sw += weight[i];
4261: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4262: } /* end of wave */
4263: } /* end of individual */
4264: } else if(mle==3){ /* exponential inter-extrapolation */
4265: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4266: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4267: for(mi=1; mi<= wav[i]-1; mi++){
4268: for (ii=1;ii<=nlstate+ndeath;ii++)
4269: for (j=1;j<=nlstate+ndeath;j++){
4270: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4271: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4272: }
4273: for(d=0; d<dh[mi][i]; d++){
4274: newm=savm;
4275: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4276: cov[2]=agexact;
4277: if(nagesqr==1)
4278: cov[3]= agexact*agexact;
4279: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4280: if(!FixedV[Tvar[Tage[kk]]])
4281: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4282: else
1.341 brouard 4283: 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 4284: }
4285: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4286: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4287: savm=oldm;
4288: oldm=newm;
4289: } /* end mult */
4290:
4291: s1=s[mw[mi][i]][i];
4292: s2=s[mw[mi+1][i]][i];
4293: bbh=(double)bh[mi][i]/(double)stepm;
4294: 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 */
4295: ipmx +=1;
4296: sw += weight[i];
4297: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4298: } /* end of wave */
4299: } /* end of individual */
4300: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4301: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4302: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4303: for(mi=1; mi<= wav[i]-1; mi++){
4304: for (ii=1;ii<=nlstate+ndeath;ii++)
4305: for (j=1;j<=nlstate+ndeath;j++){
4306: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4307: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4308: }
4309: for(d=0; d<dh[mi][i]; d++){
4310: newm=savm;
4311: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4312: cov[2]=agexact;
4313: if(nagesqr==1)
4314: cov[3]= agexact*agexact;
4315: for (kk=1; kk<=cptcovage;kk++) {
4316: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4317: }
1.126 brouard 4318:
1.226 brouard 4319: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4320: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4321: savm=oldm;
4322: oldm=newm;
4323: } /* end mult */
4324:
4325: s1=s[mw[mi][i]][i];
4326: s2=s[mw[mi+1][i]][i];
4327: if( s2 > nlstate){
4328: lli=log(out[s1][s2] - savm[s1][s2]);
4329: } else if ( s2==-1 ) { /* alive */
4330: for (j=1,survp=0. ; j<=nlstate; j++)
4331: survp += out[s1][j];
4332: lli= log(survp);
4333: }else{
4334: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4335: }
4336: ipmx +=1;
4337: sw += weight[i];
4338: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4339: /* 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 4340: } /* end of wave */
4341: } /* end of individual */
4342: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4343: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4344: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4345: for(mi=1; mi<= wav[i]-1; mi++){
4346: for (ii=1;ii<=nlstate+ndeath;ii++)
4347: for (j=1;j<=nlstate+ndeath;j++){
4348: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4349: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4350: }
4351: for(d=0; d<dh[mi][i]; d++){
4352: newm=savm;
4353: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4354: cov[2]=agexact;
4355: if(nagesqr==1)
4356: cov[3]= agexact*agexact;
4357: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4358: if(!FixedV[Tvar[Tage[kk]]])
4359: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4360: else
1.341 brouard 4361: 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 4362: }
1.126 brouard 4363:
1.226 brouard 4364: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4365: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4366: savm=oldm;
4367: oldm=newm;
4368: } /* end mult */
4369:
4370: s1=s[mw[mi][i]][i];
4371: s2=s[mw[mi+1][i]][i];
4372: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4373: ipmx +=1;
4374: sw += weight[i];
4375: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4376: /*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]);*/
4377: } /* end of wave */
4378: } /* end of individual */
4379: } /* End of if */
4380: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4381: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4382: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4383: return -l;
1.126 brouard 4384: }
4385:
4386: /*************** log-likelihood *************/
4387: double funcone( double *x)
4388: {
1.228 brouard 4389: /* Same as func but slower because of a lot of printf and if */
1.349 brouard 4390: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4391: int ioffset=0;
1.339 brouard 4392: int ipos=0,iposold=0,ncovv=0;
4393:
1.340 brouard 4394: double cotvarv, cotvarvold;
1.131 brouard 4395: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4396: double **out;
4397: double lli; /* Individual log likelihood */
4398: double llt;
4399: int s1, s2;
1.228 brouard 4400: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4401:
1.126 brouard 4402: double bbh, survp;
1.187 brouard 4403: double agexact;
1.214 brouard 4404: double agebegin, ageend;
1.126 brouard 4405: /*extern weight */
4406: /* We are differentiating ll according to initial status */
4407: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4408: /*for(i=1;i<imx;i++)
4409: printf(" %d\n",s[4][i]);
4410: */
4411: cov[1]=1.;
4412:
4413: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4414: ioffset=0;
4415: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4416: /* Computes the values of the ncovmodel covariates of the model
4417: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4418: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4419: to be observed in j being in i according to the model.
4420: */
1.243 brouard 4421: /* ioffset=2+nagesqr+cptcovage; */
4422: ioffset=2+nagesqr;
1.232 brouard 4423: /* Fixed */
1.224 brouard 4424: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4425: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 4426: 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 4427: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4428: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4429: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4430: 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 4431: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4432: /* cov[2+6]=covar[Tvar[6]][i]; */
4433: /* cov[2+6]=covar[2][i]; V2 */
4434: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4435: /* cov[2+7]=covar[Tvar[7]][i]; */
4436: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4437: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4438: /* cov[2+9]=covar[Tvar[9]][i]; */
4439: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4440: }
1.336 brouard 4441: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4442: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4443: has been calculated etc */
4444: /* For an individual i, wav[i] gives the number of effective waves */
4445: /* We compute the contribution to Likelihood of each effective transition
4446: mw[mi][i] is real wave of the mi th effectve wave */
4447: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4448: s2=s[mw[mi+1][i]][i];
1.341 brouard 4449: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4450: */
4451: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4452: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4453: /* 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?)*\/ */
4454: /* } */
1.231 brouard 4455: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4456: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4457: /* } */
1.225 brouard 4458:
1.233 brouard 4459:
4460: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4461: /* 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 */
4462: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4463: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4464: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4465: /* } */
4466:
4467: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4468: /* model V1+V3+age*V1+age*V3+V1*V3 */
4469: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4470: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4471: /* We need the position of the time varying or product in the model */
4472: /* 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 */
4473: /* TvarVV gives the variable name */
1.340 brouard 4474: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4475: * k= 1 2 3 4 5 6 7 8 9
4476: * varying 1 2 3 4 5
4477: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4478: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4479: * TvarVVind 2 3 7 7 8 8 9 9
4480: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4481: */
1.345 brouard 4482: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 4483: * 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 4484: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 4485: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4486: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
4487: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
4488: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4489: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4490: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4491: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4492: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4493: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4494: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4495: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4496: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4497: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4498: * 12 13 14 15 16
4499: * 17 18 19 20 21
4500: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
4501: * 2 3 4 6 7
4502: * 9 11 12 13 14
4503: * cptcovage=5+5 total of covariates with age
4504: * Tage[cptcovage] age*V2=12 13 14 15 16
4505: *1 17 18 19 20 21 gives the position in model of covariates associated with age
4506: *3 Tage[cptcovage] age*V3*V2=6
4507: *3 age*V2=12 13 14 15 16
4508: *3 age*V6*V3=18 19 20 21
4509: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4510: * 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
4511: * 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
4512: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4513: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4514: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
4515: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
4516: * 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
4517: * Tvar= {2, 3, 4, 6, 7,
4518: * 9, 10, 11, 12, 13, 14,
4519: * Tvar[12]=2, 3, 4, 6, 7,
4520: * Tvar[17]=9, 11, 12, 13, 14}
4521: * Typevar[1]@21 = {0, 0, 0, 0, 0,
4522: * 2, 2, 2, 2, 2, 2,
4523: * 3 3, 2, 2, 2, 2, 2,
4524: * 1, 1, 1, 1, 1,
4525: * 3, 3, 3, 3, 3}
4526: * 3 2, 3, 3, 3, 3}
4527: * 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
4528: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4529: * 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}
4530: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4531: * cptcovprod=11 (6+5)
4532: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
4533: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
4534: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
4535: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
4536: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4537: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4538: * cptcovdageprod=5 for gnuplot printing
4539: * cptcovprodvage=6
4540: * ncova=15 1 2 3 4 5
4541: * 6 7 8 9 10 11 12 13 14 15
4542: * TvarA 2 3 4 6 7
4543: * 6 2 6 7 7 3 6 4 7 4
4544: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4545: * ncovf 1 2 3
1.349 brouard 4546: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4547: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4548: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4549: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4550: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4551: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4552: * 3 1 2 3 4 5 6 7 8 9 10 11 12
4553: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
4554: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
4555: * 3 cptcovprodvage=6
4556: * 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
4557: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
4558: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.354 brouard 4559: *?TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
1.349 brouard 4560: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
4561: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4562: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
4563: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
4564: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
4565: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
4566: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
4567: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4568: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 4569: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
4570: * 2, 3, 4, 6, 7,
4571: * 6, 8, 9, 10, 11}
1.345 brouard 4572: * TvarFind[itv] 0 0 0
4573: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
1.354 brouard 4574: *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0
1.345 brouard 4575: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4576: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4577: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 4578: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4579: */
4580:
1.349 brouard 4581: 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 */
4582: 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 4583: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4584: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4585: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
1.354 brouard 4586: /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.345 brouard 4587: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.354 brouard 4588: /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4589: }else{ /* fixed covariate */
1.345 brouard 4590: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
1.354 brouard 4591: /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.349 brouard 4592: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.354 brouard 4593: /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4594: }
1.339 brouard 4595: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4596: cotvarvold=cotvarv;
4597: }else{ /* A second product */
4598: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4599: }
4600: iposold=ipos;
1.340 brouard 4601: cov[ioffset+ipos]=cotvarv;
1.354 brouard 4602: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
1.339 brouard 4603: /* For products */
4604: }
4605: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4606: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4607: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4608: /* /\* 1 2 3 4 5 *\/ */
4609: /* /\*itv 1 *\/ */
4610: /* /\* TvarVInd[1]= 2 *\/ */
4611: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4612: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4613: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4614: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4615: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4616: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4617: /* /\* 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]); *\/ */
4618: /* } */
1.232 brouard 4619: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4620: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4621: /* /\* 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]); *\/ */
4622: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4623: /* } */
1.126 brouard 4624: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4625: for (j=1;j<=nlstate+ndeath;j++){
4626: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4627: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4628: }
1.214 brouard 4629:
4630: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4631: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4632: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4633: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4634: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4635: and mw[mi+1][i]. dh depends on stepm.*/
4636: newm=savm;
1.247 brouard 4637: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4638: cov[2]=agexact;
4639: if(nagesqr==1)
4640: cov[3]= agexact*agexact;
1.349 brouard 4641: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4642: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4643: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4644: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4645: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4646: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4647: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4648: }else{ /* fixed covariate */
4649: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4650: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4651: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4652: }
4653: if(ipos!=iposold){ /* Not a product or first of a product */
4654: cotvarvold=cotvarv;
4655: }else{ /* A second product */
4656: /* printf("DEBUG * \n"); */
4657: cotvarv=cotvarv*cotvarvold;
4658: }
4659: iposold=ipos;
4660: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4661: cov[ioffset+ipos]=cotvarv*agexact;
4662: /* For products */
1.242 brouard 4663: }
1.349 brouard 4664:
1.242 brouard 4665: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4666: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4667: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4668: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4669: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4670: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4671: savm=oldm;
4672: oldm=newm;
1.126 brouard 4673: } /* end mult */
1.336 brouard 4674: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4675: /* But now since version 0.9 we anticipate for bias at large stepm.
4676: * If stepm is larger than one month (smallest stepm) and if the exact delay
4677: * (in months) between two waves is not a multiple of stepm, we rounded to
4678: * the nearest (and in case of equal distance, to the lowest) interval but now
4679: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4680: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4681: * probability in order to take into account the bias as a fraction of the way
4682: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4683: * -stepm/2 to stepm/2 .
4684: * For stepm=1 the results are the same as for previous versions of Imach.
4685: * For stepm > 1 the results are less biased than in previous versions.
4686: */
1.126 brouard 4687: s1=s[mw[mi][i]][i];
4688: s2=s[mw[mi+1][i]][i];
1.217 brouard 4689: /* if(s2==-1){ */
1.268 brouard 4690: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4691: /* /\* exit(1); *\/ */
4692: /* } */
1.126 brouard 4693: bbh=(double)bh[mi][i]/(double)stepm;
4694: /* bias is positive if real duration
4695: * is higher than the multiple of stepm and negative otherwise.
4696: */
4697: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4698: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4699: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4700: for (j=1,survp=0. ; j<=nlstate; j++)
4701: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4702: lli= log(survp);
1.126 brouard 4703: }else if (mle==1){
1.242 brouard 4704: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4705: } else if(mle==2){
1.242 brouard 4706: 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 4707: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4708: 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 4709: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4710: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4711: } else{ /* mle=0 back to 1 */
1.242 brouard 4712: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4713: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4714: } /* End of if */
4715: ipmx +=1;
4716: sw += weight[i];
4717: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4718: /* Printing covariates values for each contribution for checking */
1.343 brouard 4719: /* 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 4720: if(globpr){
1.246 brouard 4721: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4722: %11.6f %11.6f %11.6f ", \
1.242 brouard 4723: 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 4724: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4725: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4726: /* %11.6f %11.6f %11.6f ", \ */
4727: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4728: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4729: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4730: llt +=ll[k]*gipmx/gsw;
4731: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4732: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4733: }
1.343 brouard 4734: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4735: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4736: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4737: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4738: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4739: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4740: }
4741: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4742: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4743: if(ipos!=iposold){ /* Not a product or first of a product */
4744: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4745: /* printf(" %g",cov[ioffset+ipos]); */
4746: }else{
4747: fprintf(ficresilk,"*");
4748: /* printf("*"); */
1.342 brouard 4749: }
1.343 brouard 4750: iposold=ipos;
4751: }
1.349 brouard 4752: /* for (kk=1; kk<=cptcovage;kk++) { */
4753: /* if(!FixedV[Tvar[Tage[kk]]]){ */
4754: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
4755: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
4756: /* }else{ */
4757: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4758: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
4759: /* } */
4760: /* } */
4761: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4762: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4763: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4764: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4765: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4766: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4767: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4768: }else{ /* fixed covariate */
4769: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4770: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4771: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4772: }
4773: if(ipos!=iposold){ /* Not a product or first of a product */
4774: cotvarvold=cotvarv;
4775: }else{ /* A second product */
4776: /* printf("DEBUG * \n"); */
4777: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4778: }
1.349 brouard 4779: cotvarv=cotvarv*agexact;
4780: fprintf(ficresilk," %g*age",cotvarv);
4781: iposold=ipos;
4782: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4783: cov[ioffset+ipos]=cotvarv;
4784: /* For products */
1.343 brouard 4785: }
4786: /* printf("\n"); */
1.342 brouard 4787: /* } /\* End debugILK *\/ */
4788: fprintf(ficresilk,"\n");
4789: } /* End if globpr */
1.335 brouard 4790: } /* end of wave */
4791: } /* end of individual */
4792: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4793: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4794: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4795: if(globpr==0){ /* First time we count the contributions and weights */
4796: gipmx=ipmx;
4797: gsw=sw;
4798: }
1.343 brouard 4799: return -l;
1.126 brouard 4800: }
4801:
4802:
4803: /*************** function likelione ***********/
1.292 brouard 4804: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4805: {
4806: /* This routine should help understanding what is done with
4807: the selection of individuals/waves and
4808: to check the exact contribution to the likelihood.
4809: Plotting could be done.
1.342 brouard 4810: */
4811: void pstamp(FILE *ficres);
1.343 brouard 4812: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4813:
4814: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4815: strcpy(fileresilk,"ILK_");
1.202 brouard 4816: strcat(fileresilk,fileresu);
1.126 brouard 4817: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4818: printf("Problem with resultfile: %s\n", fileresilk);
4819: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4820: }
1.342 brouard 4821: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4822: 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");
4823: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4824: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4825: for(k=1; k<=nlstate; k++)
4826: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4827: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4828:
4829: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4830: for(kf=1;kf <= ncovf; kf++){
4831: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4832: /* printf("V%d",Tvar[TvarFind[kf]]); */
4833: }
4834: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4835: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4836: if(ipos!=iposold){ /* Not a product or first of a product */
4837: /* printf(" %d",ipos); */
4838: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4839: }else{
4840: /* printf("*"); */
4841: fprintf(ficresilk,"*");
1.343 brouard 4842: }
1.342 brouard 4843: iposold=ipos;
4844: }
4845: for (kk=1; kk<=cptcovage;kk++) {
4846: if(!FixedV[Tvar[Tage[kk]]]){
4847: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4848: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4849: }else{
4850: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4851: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4852: }
4853: }
4854: /* } /\* End if debugILK *\/ */
4855: /* printf("\n"); */
4856: fprintf(ficresilk,"\n");
4857: } /* End glogpri */
1.126 brouard 4858:
1.292 brouard 4859: *fretone=(*func)(p);
1.126 brouard 4860: if(*globpri !=0){
4861: fclose(ficresilk);
1.205 brouard 4862: if (mle ==0)
4863: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4864: else if(mle >=1)
4865: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4866: 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 4867: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4868:
1.207 brouard 4869: 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 4870: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4871: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4872: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4873:
4874: for (k=1; k<= nlstate ; k++) {
4875: 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 \
4876: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4877: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 4878: kvar=Tvar[TvarFind[kf]]; /* variable */
4879: 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]]);
4880: 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);
4881: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 4882: }
4883: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4884: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4885: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4886: /* 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]); */
4887: if(ipos!=iposold){ /* Not a product or first of a product */
4888: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4889: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4890: 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) */
4891: 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> \
4892: <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);
4893: } /* End only for dummies time varying (single?) */
4894: }else{ /* Useless product */
4895: /* printf("*"); */
4896: /* fprintf(ficresilk,"*"); */
4897: }
4898: iposold=ipos;
4899: } /* For each time varying covariate */
4900: } /* End loop on states */
4901:
4902: /* if(debugILK){ */
4903: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4904: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4905: /* for (k=1; k<= nlstate ; k++) { */
4906: /* 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> \ */
4907: /* <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]]); */
4908: /* } */
4909: /* } */
4910: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4911: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4912: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4913: /* /\* 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]); *\/ */
4914: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4915: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4916: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4917: /* 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) *\/ */
4918: /* for (k=1; k<= nlstate ; k++) { */
4919: /* 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> \ */
4920: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4921: /* } /\* End state *\/ */
4922: /* } /\* End only for dummies time varying (single?) *\/ */
4923: /* }else{ /\* Useless product *\/ */
4924: /* /\* printf("*"); *\/ */
4925: /* /\* fprintf(ficresilk,"*"); *\/ */
4926: /* } */
4927: /* iposold=ipos; */
4928: /* } /\* For each time varying covariate *\/ */
4929: /* }/\* End debugILK *\/ */
1.207 brouard 4930: fflush(fichtm);
1.343 brouard 4931: }/* End globpri */
1.126 brouard 4932: return;
4933: }
4934:
4935:
4936: /*********** Maximum Likelihood Estimation ***************/
4937:
4938: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4939: {
1.319 brouard 4940: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4941: double **xi;
4942: double fret;
4943: double fretone; /* Only one call to likelihood */
4944: /* char filerespow[FILENAMELENGTH];*/
1.354 brouard 4945:
4946: double * p1; /* Shifted parameters from 0 instead of 1 */
1.162 brouard 4947: #ifdef NLOPT
4948: int creturn;
4949: nlopt_opt opt;
4950: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4951: double *lb;
4952: double minf; /* the minimum objective value, upon return */
1.354 brouard 4953:
1.162 brouard 4954: myfunc_data dinst, *d = &dinst;
4955: #endif
4956:
4957:
1.126 brouard 4958: xi=matrix(1,npar,1,npar);
4959: for (i=1;i<=npar;i++)
4960: for (j=1;j<=npar;j++)
4961: xi[i][j]=(i==j ? 1.0 : 0.0);
4962: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4963: strcpy(filerespow,"POW_");
1.126 brouard 4964: strcat(filerespow,fileres);
4965: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4966: printf("Problem with resultfile: %s\n", filerespow);
4967: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4968: }
4969: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4970: for (i=1;i<=nlstate;i++)
4971: for(j=1;j<=nlstate+ndeath;j++)
4972: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4973: fprintf(ficrespow,"\n");
1.162 brouard 4974: #ifdef POWELL
1.319 brouard 4975: #ifdef LINMINORIGINAL
4976: #else /* LINMINORIGINAL */
4977:
4978: flatdir=ivector(1,npar);
4979: for (j=1;j<=npar;j++) flatdir[j]=0;
4980: #endif /*LINMINORIGINAL */
4981:
4982: #ifdef FLATSUP
4983: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4984: /* reorganizing p by suppressing flat directions */
4985: for(i=1, jk=1; i <=nlstate; i++){
4986: for(k=1; k <=(nlstate+ndeath); k++){
4987: if (k != i) {
4988: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4989: if(flatdir[jk]==1){
4990: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4991: }
4992: for(j=1; j <=ncovmodel; j++){
4993: printf("%12.7f ",p[jk]);
4994: jk++;
4995: }
4996: printf("\n");
4997: }
4998: }
4999: }
5000: /* skipping */
5001: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
5002: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
5003: for(k=1; k <=(nlstate+ndeath); k++){
5004: if (k != i) {
5005: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
5006: if(flatdir[jk]==1){
5007: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
5008: for(j=1; j <=ncovmodel; jk++,j++){
5009: printf(" p[%d]=%12.7f",jk, p[jk]);
5010: /*q[jjk]=p[jk];*/
5011: }
5012: }else{
5013: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
5014: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
5015: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
5016: /*q[jjk]=p[jk];*/
5017: }
5018: }
5019: printf("\n");
5020: }
5021: fflush(stdout);
5022: }
5023: }
5024: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5025: #else /* FLATSUP */
1.126 brouard 5026: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 5027: #endif /* FLATSUP */
5028:
5029: #ifdef LINMINORIGINAL
5030: #else
5031: free_ivector(flatdir,1,npar);
5032: #endif /* LINMINORIGINAL*/
5033: #endif /* POWELL */
1.126 brouard 5034:
1.162 brouard 5035: #ifdef NLOPT
5036: #ifdef NEWUOA
5037: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
5038: #else
5039: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
5040: #endif
5041: lb=vector(0,npar-1);
5042: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
5043: nlopt_set_lower_bounds(opt, lb);
5044: nlopt_set_initial_step1(opt, 0.1);
5045:
5046: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5047: d->function = func;
5048: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5049: nlopt_set_min_objective(opt, myfunc, d);
5050: nlopt_set_xtol_rel(opt, ftol);
5051: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5052: printf("nlopt failed! %d\n",creturn);
5053: }
5054: else {
5055: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5056: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5057: iter=1; /* not equal */
5058: }
5059: nlopt_destroy(opt);
5060: #endif
1.319 brouard 5061: #ifdef FLATSUP
5062: /* npared = npar -flatd/ncovmodel; */
5063: /* xired= matrix(1,npared,1,npared); */
5064: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5065: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5066: /* free_matrix(xire,1,npared,1,npared); */
5067: #else /* FLATSUP */
5068: #endif /* FLATSUP */
1.126 brouard 5069: free_matrix(xi,1,npar,1,npar);
5070: fclose(ficrespow);
1.203 brouard 5071: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5072: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5073: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5074:
5075: }
5076:
5077: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5078: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5079: {
5080: double **a,**y,*x,pd;
1.203 brouard 5081: /* double **hess; */
1.164 brouard 5082: int i, j;
1.126 brouard 5083: int *indx;
5084:
5085: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5086: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5087: void lubksb(double **a, int npar, int *indx, double b[]) ;
5088: void ludcmp(double **a, int npar, int *indx, double *d) ;
5089: double gompertz(double p[]);
1.203 brouard 5090: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5091:
5092: printf("\nCalculation of the hessian matrix. Wait...\n");
5093: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5094: for (i=1;i<=npar;i++){
1.203 brouard 5095: printf("%d-",i);fflush(stdout);
5096: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5097:
5098: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5099:
5100: /* printf(" %f ",p[i]);
5101: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5102: }
5103:
5104: for (i=1;i<=npar;i++) {
5105: for (j=1;j<=npar;j++) {
5106: if (j>i) {
1.203 brouard 5107: printf(".%d-%d",i,j);fflush(stdout);
5108: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5109: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5110:
5111: hess[j][i]=hess[i][j];
5112: /*printf(" %lf ",hess[i][j]);*/
5113: }
5114: }
5115: }
5116: printf("\n");
5117: fprintf(ficlog,"\n");
5118:
5119: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5120: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5121:
5122: a=matrix(1,npar,1,npar);
5123: y=matrix(1,npar,1,npar);
5124: x=vector(1,npar);
5125: indx=ivector(1,npar);
5126: for (i=1;i<=npar;i++)
5127: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5128: ludcmp(a,npar,indx,&pd);
5129:
5130: for (j=1;j<=npar;j++) {
5131: for (i=1;i<=npar;i++) x[i]=0;
5132: x[j]=1;
5133: lubksb(a,npar,indx,x);
5134: for (i=1;i<=npar;i++){
5135: matcov[i][j]=x[i];
5136: }
5137: }
5138:
5139: printf("\n#Hessian matrix#\n");
5140: fprintf(ficlog,"\n#Hessian matrix#\n");
5141: for (i=1;i<=npar;i++) {
5142: for (j=1;j<=npar;j++) {
1.203 brouard 5143: printf("%.6e ",hess[i][j]);
5144: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5145: }
5146: printf("\n");
5147: fprintf(ficlog,"\n");
5148: }
5149:
1.203 brouard 5150: /* printf("\n#Covariance matrix#\n"); */
5151: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5152: /* for (i=1;i<=npar;i++) { */
5153: /* for (j=1;j<=npar;j++) { */
5154: /* printf("%.6e ",matcov[i][j]); */
5155: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5156: /* } */
5157: /* printf("\n"); */
5158: /* fprintf(ficlog,"\n"); */
5159: /* } */
5160:
1.126 brouard 5161: /* Recompute Inverse */
1.203 brouard 5162: /* for (i=1;i<=npar;i++) */
5163: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5164: /* ludcmp(a,npar,indx,&pd); */
5165:
5166: /* printf("\n#Hessian matrix recomputed#\n"); */
5167:
5168: /* for (j=1;j<=npar;j++) { */
5169: /* for (i=1;i<=npar;i++) x[i]=0; */
5170: /* x[j]=1; */
5171: /* lubksb(a,npar,indx,x); */
5172: /* for (i=1;i<=npar;i++){ */
5173: /* y[i][j]=x[i]; */
5174: /* printf("%.3e ",y[i][j]); */
5175: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5176: /* } */
5177: /* printf("\n"); */
5178: /* fprintf(ficlog,"\n"); */
5179: /* } */
5180:
5181: /* Verifying the inverse matrix */
5182: #ifdef DEBUGHESS
5183: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5184:
1.203 brouard 5185: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5186: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5187:
5188: for (j=1;j<=npar;j++) {
5189: for (i=1;i<=npar;i++){
1.203 brouard 5190: printf("%.2f ",y[i][j]);
5191: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5192: }
5193: printf("\n");
5194: fprintf(ficlog,"\n");
5195: }
1.203 brouard 5196: #endif
1.126 brouard 5197:
5198: free_matrix(a,1,npar,1,npar);
5199: free_matrix(y,1,npar,1,npar);
5200: free_vector(x,1,npar);
5201: free_ivector(indx,1,npar);
1.203 brouard 5202: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5203:
5204:
5205: }
5206:
5207: /*************** hessian matrix ****************/
5208: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5209: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5210: int i;
5211: int l=1, lmax=20;
1.203 brouard 5212: double k1,k2, res, fx;
1.132 brouard 5213: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5214: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5215: int k=0,kmax=10;
5216: double l1;
5217:
5218: fx=func(x);
5219: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5220: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5221: l1=pow(10,l);
5222: delts=delt;
5223: for(k=1 ; k <kmax; k=k+1){
5224: delt = delta*(l1*k);
5225: p2[theta]=x[theta] +delt;
1.145 brouard 5226: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5227: p2[theta]=x[theta]-delt;
5228: k2=func(p2)-fx;
5229: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5230: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5231:
1.203 brouard 5232: #ifdef DEBUGHESSII
1.126 brouard 5233: 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);
5234: 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);
5235: #endif
5236: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5237: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5238: k=kmax;
5239: }
5240: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5241: k=kmax; l=lmax*10;
1.126 brouard 5242: }
5243: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5244: delts=delt;
5245: }
1.203 brouard 5246: } /* End loop k */
1.126 brouard 5247: }
5248: delti[theta]=delts;
5249: return res;
5250:
5251: }
5252:
1.203 brouard 5253: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5254: {
5255: int i;
1.164 brouard 5256: int l=1, lmax=20;
1.126 brouard 5257: double k1,k2,k3,k4,res,fx;
1.132 brouard 5258: double p2[MAXPARM+1];
1.203 brouard 5259: int k, kmax=1;
5260: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5261:
5262: int firstime=0;
1.203 brouard 5263:
1.126 brouard 5264: fx=func(x);
1.203 brouard 5265: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5266: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5267: p2[thetai]=x[thetai]+delti[thetai]*k;
5268: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5269: k1=func(p2)-fx;
5270:
1.203 brouard 5271: p2[thetai]=x[thetai]+delti[thetai]*k;
5272: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5273: k2=func(p2)-fx;
5274:
1.203 brouard 5275: p2[thetai]=x[thetai]-delti[thetai]*k;
5276: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5277: k3=func(p2)-fx;
5278:
1.203 brouard 5279: p2[thetai]=x[thetai]-delti[thetai]*k;
5280: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5281: k4=func(p2)-fx;
1.203 brouard 5282: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5283: if(k1*k2*k3*k4 <0.){
1.208 brouard 5284: firstime=1;
1.203 brouard 5285: kmax=kmax+10;
1.208 brouard 5286: }
5287: if(kmax >=10 || firstime ==1){
1.354 brouard 5288: /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */
1.246 brouard 5289: 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);
5290: 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 5291: 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);
5292: 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);
5293: }
5294: #ifdef DEBUGHESSIJ
5295: v1=hess[thetai][thetai];
5296: v2=hess[thetaj][thetaj];
5297: cv12=res;
5298: /* Computing eigen value of Hessian matrix */
5299: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5300: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5301: if ((lc2 <0) || (lc1 <0) ){
5302: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5303: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5304: 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);
5305: 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);
5306: }
1.126 brouard 5307: #endif
5308: }
5309: return res;
5310: }
5311:
1.203 brouard 5312: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5313: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5314: /* { */
5315: /* int i; */
5316: /* int l=1, lmax=20; */
5317: /* double k1,k2,k3,k4,res,fx; */
5318: /* double p2[MAXPARM+1]; */
5319: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5320: /* int k=0,kmax=10; */
5321: /* double l1; */
5322:
5323: /* fx=func(x); */
5324: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5325: /* l1=pow(10,l); */
5326: /* delts=delt; */
5327: /* for(k=1 ; k <kmax; k=k+1){ */
5328: /* delt = delti*(l1*k); */
5329: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5330: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5331: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5332: /* k1=func(p2)-fx; */
5333:
5334: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5335: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5336: /* k2=func(p2)-fx; */
5337:
5338: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5339: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5340: /* k3=func(p2)-fx; */
5341:
5342: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5343: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5344: /* k4=func(p2)-fx; */
5345: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5346: /* #ifdef DEBUGHESSIJ */
5347: /* 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); */
5348: /* 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); */
5349: /* #endif */
5350: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5351: /* k=kmax; */
5352: /* } */
5353: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5354: /* k=kmax; l=lmax*10; */
5355: /* } */
5356: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5357: /* delts=delt; */
5358: /* } */
5359: /* } /\* End loop k *\/ */
5360: /* } */
5361: /* delti[theta]=delts; */
5362: /* return res; */
5363: /* } */
5364:
5365:
1.126 brouard 5366: /************** Inverse of matrix **************/
5367: void ludcmp(double **a, int n, int *indx, double *d)
5368: {
5369: int i,imax,j,k;
5370: double big,dum,sum,temp;
5371: double *vv;
5372:
5373: vv=vector(1,n);
5374: *d=1.0;
5375: for (i=1;i<=n;i++) {
5376: big=0.0;
5377: for (j=1;j<=n;j++)
5378: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5379: if (big == 0.0){
5380: printf(" Singular Hessian matrix at row %d:\n",i);
5381: for (j=1;j<=n;j++) {
5382: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5383: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5384: }
5385: fflush(ficlog);
5386: fclose(ficlog);
5387: nrerror("Singular matrix in routine ludcmp");
5388: }
1.126 brouard 5389: vv[i]=1.0/big;
5390: }
5391: for (j=1;j<=n;j++) {
5392: for (i=1;i<j;i++) {
5393: sum=a[i][j];
5394: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5395: a[i][j]=sum;
5396: }
5397: big=0.0;
5398: for (i=j;i<=n;i++) {
5399: sum=a[i][j];
5400: for (k=1;k<j;k++)
5401: sum -= a[i][k]*a[k][j];
5402: a[i][j]=sum;
5403: if ( (dum=vv[i]*fabs(sum)) >= big) {
5404: big=dum;
5405: imax=i;
5406: }
5407: }
5408: if (j != imax) {
5409: for (k=1;k<=n;k++) {
5410: dum=a[imax][k];
5411: a[imax][k]=a[j][k];
5412: a[j][k]=dum;
5413: }
5414: *d = -(*d);
5415: vv[imax]=vv[j];
5416: }
5417: indx[j]=imax;
5418: if (a[j][j] == 0.0) a[j][j]=TINY;
5419: if (j != n) {
5420: dum=1.0/(a[j][j]);
5421: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5422: }
5423: }
5424: free_vector(vv,1,n); /* Doesn't work */
5425: ;
5426: }
5427:
5428: void lubksb(double **a, int n, int *indx, double b[])
5429: {
5430: int i,ii=0,ip,j;
5431: double sum;
5432:
5433: for (i=1;i<=n;i++) {
5434: ip=indx[i];
5435: sum=b[ip];
5436: b[ip]=b[i];
5437: if (ii)
5438: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5439: else if (sum) ii=i;
5440: b[i]=sum;
5441: }
5442: for (i=n;i>=1;i--) {
5443: sum=b[i];
5444: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5445: b[i]=sum/a[i][i];
5446: }
5447: }
5448:
5449: void pstamp(FILE *fichier)
5450: {
1.196 brouard 5451: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5452: }
5453:
1.297 brouard 5454: void date2dmy(double date,double *day, double *month, double *year){
5455: double yp=0., yp1=0., yp2=0.;
5456:
5457: yp1=modf(date,&yp);/* extracts integral of date in yp and
5458: fractional in yp1 */
5459: *year=yp;
5460: yp2=modf((yp1*12),&yp);
5461: *month=yp;
5462: yp1=modf((yp2*30.5),&yp);
5463: *day=yp;
5464: if(*day==0) *day=1;
5465: if(*month==0) *month=1;
5466: }
5467:
1.253 brouard 5468:
5469:
1.126 brouard 5470: /************ Frequencies ********************/
1.251 brouard 5471: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5472: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5473: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5474: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5475: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5476: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5477: int iind=0, iage=0;
5478: int mi; /* Effective wave */
5479: int first;
5480: double ***freq; /* Frequencies */
1.268 brouard 5481: 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 */
5482: 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 5483: double *meanq, *stdq, *idq;
1.226 brouard 5484: double **meanqt;
5485: double *pp, **prop, *posprop, *pospropt;
5486: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5487: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5488: double agebegin, ageend;
5489:
5490: pp=vector(1,nlstate);
1.251 brouard 5491: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5492: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5493: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5494: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5495: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5496: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5497: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5498: meanqt=matrix(1,lastpass,1,nqtveff);
5499: strcpy(fileresp,"P_");
5500: strcat(fileresp,fileresu);
5501: /*strcat(fileresphtm,fileresu);*/
5502: if((ficresp=fopen(fileresp,"w"))==NULL) {
5503: printf("Problem with prevalence resultfile: %s\n", fileresp);
5504: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5505: exit(0);
5506: }
1.240 brouard 5507:
1.226 brouard 5508: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5509: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5510: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5511: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5512: fflush(ficlog);
5513: exit(70);
5514: }
5515: else{
5516: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 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: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5520: }
1.319 brouard 5521: 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 5522:
1.226 brouard 5523: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5524: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5525: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5526: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5527: fflush(ficlog);
5528: exit(70);
1.240 brouard 5529: } else{
1.226 brouard 5530: 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 5531: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5532: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5533: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5534: }
1.319 brouard 5535: 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 5536:
1.253 brouard 5537: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5538: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5539: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5540: j1=0;
1.126 brouard 5541:
1.227 brouard 5542: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5543: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5544: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5545: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5546:
5547:
1.226 brouard 5548: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5549: reference=low_education V1=0,V2=0
5550: med_educ V1=1 V2=0,
5551: high_educ V1=0 V2=1
1.330 brouard 5552: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5553: */
1.249 brouard 5554: dateintsum=0;
5555: k2cpt=0;
5556:
1.253 brouard 5557: if(cptcoveff == 0 )
1.265 brouard 5558: nl=1; /* Constant and age model only */
1.253 brouard 5559: else
5560: nl=2;
1.265 brouard 5561:
5562: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5563: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5564: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5565: * freq[s1][s2][iage] =0.
5566: * Loop on iind
5567: * ++freq[s1][s2][iage] weighted
5568: * end iind
5569: * if covariate and j!0
5570: * headers Variable on one line
5571: * endif cov j!=0
5572: * header of frequency table by age
5573: * Loop on age
5574: * pp[s1]+=freq[s1][s2][iage] weighted
5575: * pos+=freq[s1][s2][iage] weighted
5576: * Loop on s1 initial state
5577: * fprintf(ficresp
5578: * end s1
5579: * end age
5580: * if j!=0 computes starting values
5581: * end compute starting values
5582: * end j1
5583: * end nl
5584: */
1.253 brouard 5585: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5586: if(nj==1)
5587: j=0; /* First pass for the constant */
1.265 brouard 5588: else{
1.335 brouard 5589: 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 5590: }
1.251 brouard 5591: first=1;
1.332 brouard 5592: 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 5593: posproptt=0.;
1.330 brouard 5594: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5595: scanf("%d", i);*/
5596: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5597: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5598: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5599: freq[i][s2][m]=0;
1.251 brouard 5600:
5601: for (i=1; i<=nlstate; i++) {
1.240 brouard 5602: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5603: prop[i][m]=0;
5604: posprop[i]=0;
5605: pospropt[i]=0;
5606: }
1.283 brouard 5607: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5608: idq[z1]=0.;
5609: meanq[z1]=0.;
5610: stdq[z1]=0.;
1.283 brouard 5611: }
5612: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5613: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5614: /* meanqt[m][z1]=0.; */
5615: /* } */
5616: /* } */
1.251 brouard 5617: /* dateintsum=0; */
5618: /* k2cpt=0; */
5619:
1.265 brouard 5620: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5621: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5622: bool=1;
5623: if(j !=0){
5624: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5625: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5626: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5627: /* if(Tvaraff[z1] ==-20){ */
5628: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5629: /* }else if(Tvaraff[z1] ==-10){ */
5630: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5631: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5632: /* 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); */
5633: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5634: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5635: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5636: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5637: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5638: /* 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", */
5639: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5640: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5641: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5642: } /* Onlyf fixed */
5643: } /* end z1 */
1.335 brouard 5644: } /* cptcoveff > 0 */
1.251 brouard 5645: } /* end any */
5646: }/* end j==0 */
1.265 brouard 5647: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5648: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5649: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5650: m=mw[mi][iind];
5651: if(j!=0){
5652: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5653: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5654: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5655: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5656: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5657: 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 5658: value is -1, we don't select. It differs from the
5659: constant and age model which counts them. */
5660: bool=0; /* not selected */
5661: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5662: /* i1=Tvaraff[z1]; */
5663: /* i2=TnsdVar[i1]; */
5664: /* i3=nbcode[i1][i2]; */
5665: /* i4=covar[i1][iind]; */
5666: /* if(i4 != i3){ */
5667: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5668: bool=0;
5669: }
5670: }
5671: }
5672: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5673: } /* end j==0 */
5674: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5675: if(bool==1){ /*Selected */
1.251 brouard 5676: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5677: and mw[mi+1][iind]. dh depends on stepm. */
5678: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5679: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5680: if(m >=firstpass && m <=lastpass){
5681: k2=anint[m][iind]+(mint[m][iind]/12.);
5682: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5683: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5684: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5685: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5686: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5687: if (m<lastpass) {
5688: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5689: /* 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]); */
5690: if(s[m][iind]==-1)
5691: 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.));
5692: 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 5693: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5694: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5695: idq[z1]=idq[z1]+weight[iind];
5696: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5697: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5698: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5699: }
1.284 brouard 5700: }
1.251 brouard 5701: /* if((int)agev[m][iind] == 55) */
5702: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5703: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5704: 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 5705: }
1.251 brouard 5706: } /* end if between passes */
5707: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5708: dateintsum=dateintsum+k2; /* on all covariates ?*/
5709: k2cpt++;
5710: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5711: }
1.251 brouard 5712: }else{
5713: bool=1;
5714: }/* end bool 2 */
5715: } /* end m */
1.284 brouard 5716: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5717: /* idq[z1]=idq[z1]+weight[iind]; */
5718: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5719: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5720: /* } */
1.251 brouard 5721: } /* end bool */
5722: } /* end iind = 1 to imx */
1.319 brouard 5723: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5724: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5725:
5726:
5727: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5728: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5729: pstamp(ficresp);
1.335 brouard 5730: if (cptcoveff>0 && j!=0){
1.265 brouard 5731: pstamp(ficresp);
1.251 brouard 5732: printf( "\n#********** Variable ");
5733: fprintf(ficresp, "\n#********** Variable ");
5734: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5735: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5736: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5737: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5738: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5739: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5740: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5741: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5742: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5743: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5744: }else{
1.330 brouard 5745: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5746: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5747: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5748: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5749: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5750: }
5751: }
5752: printf( "**********\n#");
5753: fprintf(ficresp, "**********\n#");
5754: fprintf(ficresphtm, "**********</h3>\n");
5755: fprintf(ficresphtmfr, "**********</h3>\n");
5756: fprintf(ficlog, "**********\n");
5757: }
1.284 brouard 5758: /*
5759: Printing means of quantitative variables if any
5760: */
5761: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5762: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5763: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5764: if(weightopt==1){
5765: printf(" Weighted mean and standard deviation of");
5766: fprintf(ficlog," Weighted mean and standard deviation of");
5767: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5768: }
1.311 brouard 5769: /* mu = \frac{w x}{\sum w}
5770: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5771: */
5772: 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]));
5773: 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]));
5774: 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 5775: }
5776: /* for (z1=1; z1<= nqtveff; z1++) { */
5777: /* for(m=1;m<=lastpass;m++){ */
5778: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5779: /* } */
5780: /* } */
1.283 brouard 5781:
1.251 brouard 5782: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5783: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5784: fprintf(ficresp, " Age");
1.335 brouard 5785: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5786: 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]]);
5787: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5788: }
1.251 brouard 5789: for(i=1; i<=nlstate;i++) {
1.335 brouard 5790: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5791: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5792: }
1.335 brouard 5793: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5794: fprintf(ficresphtm, "\n");
5795:
5796: /* Header of frequency table by age */
5797: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5798: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5799: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5800: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5801: if(s2!=0 && m!=0)
5802: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5803: }
1.226 brouard 5804: }
1.251 brouard 5805: fprintf(ficresphtmfr, "\n");
5806:
5807: /* For each age */
5808: for(iage=iagemin; iage <= iagemax+3; iage++){
5809: fprintf(ficresphtm,"<tr>");
5810: if(iage==iagemax+1){
5811: fprintf(ficlog,"1");
5812: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5813: }else if(iage==iagemax+2){
5814: fprintf(ficlog,"0");
5815: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5816: }else if(iage==iagemax+3){
5817: fprintf(ficlog,"Total");
5818: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5819: }else{
1.240 brouard 5820: if(first==1){
1.251 brouard 5821: first=0;
5822: printf("See log file for details...\n");
5823: }
5824: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5825: fprintf(ficlog,"Age %d", iage);
5826: }
1.265 brouard 5827: for(s1=1; s1 <=nlstate ; s1++){
5828: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5829: pp[s1] += freq[s1][m][iage];
1.251 brouard 5830: }
1.265 brouard 5831: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5832: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5833: pos += freq[s1][m][iage];
5834: if(pp[s1]>=1.e-10){
1.251 brouard 5835: if(first==1){
1.265 brouard 5836: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5837: }
1.265 brouard 5838: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5839: }else{
5840: if(first==1)
1.265 brouard 5841: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5842: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5843: }
5844: }
5845:
1.265 brouard 5846: for(s1=1; s1 <=nlstate ; s1++){
5847: /* posprop[s1]=0; */
5848: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5849: pp[s1] += freq[s1][m][iage];
5850: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5851:
5852: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5853: pos += pp[s1]; /* pos is the total number of transitions until this age */
5854: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5855: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5856: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5857: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5858: }
5859:
5860: /* Writing ficresp */
1.335 brouard 5861: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5862: if( iage <= iagemax){
5863: fprintf(ficresp," %d",iage);
5864: }
5865: }else if( nj==2){
5866: if( iage <= iagemax){
5867: fprintf(ficresp," %d",iage);
1.335 brouard 5868: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5869: }
1.240 brouard 5870: }
1.265 brouard 5871: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5872: if(pos>=1.e-5){
1.251 brouard 5873: if(first==1)
1.265 brouard 5874: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5875: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5876: }else{
5877: if(first==1)
1.265 brouard 5878: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5879: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5880: }
5881: if( iage <= iagemax){
5882: if(pos>=1.e-5){
1.335 brouard 5883: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5884: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5885: }else if( nj==2){
5886: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5887: }
5888: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5889: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5890: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5891: } else{
1.335 brouard 5892: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5893: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5894: }
1.240 brouard 5895: }
1.265 brouard 5896: pospropt[s1] +=posprop[s1];
5897: } /* end loop s1 */
1.251 brouard 5898: /* pospropt=0.; */
1.265 brouard 5899: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5900: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5901: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5902: if(first==1){
1.265 brouard 5903: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5904: }
1.265 brouard 5905: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5906: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5907: }
1.265 brouard 5908: if(s1!=0 && m!=0)
5909: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5910: }
1.265 brouard 5911: } /* end loop s1 */
1.251 brouard 5912: posproptt=0.;
1.265 brouard 5913: for(s1=1; s1 <=nlstate; s1++){
5914: posproptt += pospropt[s1];
1.251 brouard 5915: }
5916: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5917: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5918: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5919: if(iage <= iagemax)
5920: fprintf(ficresp,"\n");
1.240 brouard 5921: }
1.251 brouard 5922: if(first==1)
5923: printf("Others in log...\n");
5924: fprintf(ficlog,"\n");
5925: } /* end loop age iage */
1.265 brouard 5926:
1.251 brouard 5927: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5928: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5929: if(posproptt < 1.e-5){
1.265 brouard 5930: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5931: }else{
1.265 brouard 5932: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5933: }
1.226 brouard 5934: }
1.251 brouard 5935: fprintf(ficresphtm,"</tr>\n");
5936: fprintf(ficresphtm,"</table>\n");
5937: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5938: if(posproptt < 1.e-5){
1.251 brouard 5939: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5940: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5941: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5942: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5943: invalidvarcomb[j1]=1;
1.226 brouard 5944: }else{
1.338 brouard 5945: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5946: invalidvarcomb[j1]=0;
1.226 brouard 5947: }
1.251 brouard 5948: fprintf(ficresphtmfr,"</table>\n");
5949: fprintf(ficlog,"\n");
5950: if(j!=0){
5951: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5952: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5953: for(k=1; k <=(nlstate+ndeath); k++){
5954: if (k != i) {
1.265 brouard 5955: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5956: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5957: if(j1==1){ /* All dummy covariates to zero */
5958: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5959: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5960: printf("%d%d ",i,k);
5961: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5962: 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]));
5963: 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]));
5964: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5965: }
1.253 brouard 5966: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5967: for(iage=iagemin; iage <= iagemax+3; iage++){
5968: x[iage]= (double)iage;
5969: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5970: /* 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 5971: }
1.268 brouard 5972: /* Some are not finite, but linreg will ignore these ages */
5973: no=0;
1.253 brouard 5974: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5975: pstart[s1]=b;
5976: pstart[s1-1]=a;
1.252 brouard 5977: }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 */
5978: 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]);
5979: 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 5980: 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 5981: printf("%d%d ",i,k);
5982: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5983: 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 5984: }else{ /* Other cases, like quantitative fixed or varying covariates */
5985: ;
5986: }
5987: /* printf("%12.7f )", param[i][jj][k]); */
5988: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5989: s1++;
1.251 brouard 5990: } /* end jj */
5991: } /* end k!= i */
5992: } /* end k */
1.265 brouard 5993: } /* end i, s1 */
1.251 brouard 5994: } /* end j !=0 */
5995: } /* end selected combination of covariate j1 */
5996: if(j==0){ /* We can estimate starting values from the occurences in each case */
5997: printf("#Freqsummary: Starting values for the constants:\n");
5998: fprintf(ficlog,"\n");
1.265 brouard 5999: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 6000: for(k=1; k <=(nlstate+ndeath); k++){
6001: if (k != i) {
6002: printf("%d%d ",i,k);
6003: fprintf(ficlog,"%d%d ",i,k);
6004: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 6005: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 6006: if(jj==1){ /* Age has to be done */
1.265 brouard 6007: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
6008: 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]));
6009: 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 6010: }
6011: /* printf("%12.7f )", param[i][jj][k]); */
6012: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 6013: s1++;
1.250 brouard 6014: }
1.251 brouard 6015: printf("\n");
6016: fprintf(ficlog,"\n");
1.250 brouard 6017: }
6018: }
1.284 brouard 6019: } /* end of state i */
1.251 brouard 6020: printf("#Freqsummary\n");
6021: fprintf(ficlog,"\n");
1.265 brouard 6022: for(s1=-1; s1 <=nlstate+ndeath; s1++){
6023: for(s2=-1; s2 <=nlstate+ndeath; s2++){
6024: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
6025: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6026: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6027: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
6028: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
6029: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 6030: /* } */
6031: }
1.265 brouard 6032: } /* end loop s1 */
1.251 brouard 6033:
6034: printf("\n");
6035: fprintf(ficlog,"\n");
6036: } /* end j=0 */
1.249 brouard 6037: } /* end j */
1.252 brouard 6038:
1.253 brouard 6039: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 6040: for(i=1, jk=1; i <=nlstate; i++){
6041: for(j=1; j <=nlstate+ndeath; j++){
6042: if(j!=i){
6043: /*ca[0]= k+'a'-1;ca[1]='\0';*/
6044: printf("%1d%1d",i,j);
6045: fprintf(ficparo,"%1d%1d",i,j);
6046: for(k=1; k<=ncovmodel;k++){
6047: /* printf(" %lf",param[i][j][k]); */
6048: /* fprintf(ficparo," %lf",param[i][j][k]); */
6049: p[jk]=pstart[jk];
6050: printf(" %f ",pstart[jk]);
6051: fprintf(ficparo," %f ",pstart[jk]);
6052: jk++;
6053: }
6054: printf("\n");
6055: fprintf(ficparo,"\n");
6056: }
6057: }
6058: }
6059: } /* end mle=-2 */
1.226 brouard 6060: dateintmean=dateintsum/k2cpt;
1.296 brouard 6061: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6062:
1.226 brouard 6063: fclose(ficresp);
6064: fclose(ficresphtm);
6065: fclose(ficresphtmfr);
1.283 brouard 6066: free_vector(idq,1,nqfveff);
1.226 brouard 6067: free_vector(meanq,1,nqfveff);
1.284 brouard 6068: free_vector(stdq,1,nqfveff);
1.226 brouard 6069: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6070: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6071: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6072: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6073: free_vector(pospropt,1,nlstate);
6074: free_vector(posprop,1,nlstate);
1.251 brouard 6075: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6076: free_vector(pp,1,nlstate);
6077: /* End of freqsummary */
6078: }
1.126 brouard 6079:
1.268 brouard 6080: /* Simple linear regression */
6081: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6082:
6083: /* y=a+bx regression */
6084: double sumx = 0.0; /* sum of x */
6085: double sumx2 = 0.0; /* sum of x**2 */
6086: double sumxy = 0.0; /* sum of x * y */
6087: double sumy = 0.0; /* sum of y */
6088: double sumy2 = 0.0; /* sum of y**2 */
6089: double sume2 = 0.0; /* sum of square or residuals */
6090: double yhat;
6091:
6092: double denom=0;
6093: int i;
6094: int ne=*no;
6095:
6096: for ( i=ifi, ne=0;i<=ila;i++) {
6097: if(!isfinite(x[i]) || !isfinite(y[i])){
6098: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6099: continue;
6100: }
6101: ne=ne+1;
6102: sumx += x[i];
6103: sumx2 += x[i]*x[i];
6104: sumxy += x[i] * y[i];
6105: sumy += y[i];
6106: sumy2 += y[i]*y[i];
6107: denom = (ne * sumx2 - sumx*sumx);
6108: /* 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); */
6109: }
6110:
6111: denom = (ne * sumx2 - sumx*sumx);
6112: if (denom == 0) {
6113: // vertical, slope m is infinity
6114: *b = INFINITY;
6115: *a = 0;
6116: if (r) *r = 0;
6117: return 1;
6118: }
6119:
6120: *b = (ne * sumxy - sumx * sumy) / denom;
6121: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6122: if (r!=NULL) {
6123: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6124: sqrt((sumx2 - sumx*sumx/ne) *
6125: (sumy2 - sumy*sumy/ne));
6126: }
6127: *no=ne;
6128: for ( i=ifi, ne=0;i<=ila;i++) {
6129: if(!isfinite(x[i]) || !isfinite(y[i])){
6130: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6131: continue;
6132: }
6133: ne=ne+1;
6134: yhat = y[i] - *a -*b* x[i];
6135: sume2 += yhat * yhat ;
6136:
6137: denom = (ne * sumx2 - sumx*sumx);
6138: /* 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); */
6139: }
6140: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6141: *sa= *sb * sqrt(sumx2/ne);
6142:
6143: return 0;
6144: }
6145:
1.126 brouard 6146: /************ Prevalence ********************/
1.227 brouard 6147: 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)
6148: {
6149: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6150: in each health status at the date of interview (if between dateprev1 and dateprev2).
6151: We still use firstpass and lastpass as another selection.
6152: */
1.126 brouard 6153:
1.227 brouard 6154: int i, m, jk, j1, bool, z1,j, iv;
6155: int mi; /* Effective wave */
6156: int iage;
6157: double agebegin, ageend;
6158:
6159: double **prop;
6160: double posprop;
6161: double y2; /* in fractional years */
6162: int iagemin, iagemax;
6163: int first; /** to stop verbosity which is redirected to log file */
6164:
6165: iagemin= (int) agemin;
6166: iagemax= (int) agemax;
6167: /*pp=vector(1,nlstate);*/
1.251 brouard 6168: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6169: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6170: j1=0;
1.222 brouard 6171:
1.227 brouard 6172: /*j=cptcoveff;*/
6173: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6174:
1.288 brouard 6175: first=0;
1.335 brouard 6176: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6177: for (i=1; i<=nlstate; i++)
1.251 brouard 6178: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6179: prop[i][iage]=0.0;
6180: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6181: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6182: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6183:
6184: for (i=1; i<=imx; i++) { /* Each individual */
6185: bool=1;
6186: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6187: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6188: m=mw[mi][i];
6189: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6190: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6191: for (z1=1; z1<=cptcoveff; z1++){
6192: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6193: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6194: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6195: bool=0;
6196: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6197: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6198: bool=0;
6199: }
6200: }
6201: if(bool==1){ /* Otherwise we skip that wave/person */
6202: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6203: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6204: if(m >=firstpass && m <=lastpass){
6205: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6206: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6207: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6208: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6209: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6210: 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);
6211: exit(1);
6212: }
6213: if (s[m][i]>0 && s[m][i]<=nlstate) {
6214: /*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]]);*/
6215: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6216: prop[s[m][i]][iagemax+3] += weight[i];
6217: } /* end valid statuses */
6218: } /* end selection of dates */
6219: } /* end selection of waves */
6220: } /* end bool */
6221: } /* end wave */
6222: } /* end individual */
6223: for(i=iagemin; i <= iagemax+3; i++){
6224: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6225: posprop += prop[jk][i];
6226: }
6227:
6228: for(jk=1; jk <=nlstate ; jk++){
6229: if( i <= iagemax){
6230: if(posprop>=1.e-5){
6231: probs[i][jk][j1]= prop[jk][i]/posprop;
6232: } else{
1.288 brouard 6233: if(!first){
6234: first=1;
1.266 brouard 6235: 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]);
6236: }else{
1.288 brouard 6237: 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 6238: }
6239: }
6240: }
6241: }/* end jk */
6242: }/* end i */
1.222 brouard 6243: /*} *//* end i1 */
1.227 brouard 6244: } /* end j1 */
1.222 brouard 6245:
1.227 brouard 6246: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6247: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6248: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6249: } /* End of prevalence */
1.126 brouard 6250:
6251: /************* Waves Concatenation ***************/
6252:
6253: 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)
6254: {
1.298 brouard 6255: /* 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 6256: Death is a valid wave (if date is known).
6257: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6258: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6259: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6260: */
1.126 brouard 6261:
1.224 brouard 6262: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6263: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6264: double sum=0., jmean=0.;*/
1.224 brouard 6265: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6266: int j, k=0,jk, ju, jl;
6267: double sum=0.;
6268: first=0;
1.214 brouard 6269: firstwo=0;
1.217 brouard 6270: firsthree=0;
1.218 brouard 6271: firstfour=0;
1.164 brouard 6272: jmin=100000;
1.126 brouard 6273: jmax=-1;
6274: jmean=0.;
1.224 brouard 6275:
6276: /* Treating live states */
1.214 brouard 6277: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6278: mi=0; /* First valid wave */
1.227 brouard 6279: mli=0; /* Last valid wave */
1.309 brouard 6280: m=firstpass; /* Loop on waves */
6281: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6282: 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 */
6283: mli=m-1;/* mw[++mi][i]=m-1; */
6284: }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 6285: 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 6286: mli=m;
1.224 brouard 6287: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6288: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6289: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6290: }
1.309 brouard 6291: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6292: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6293: break;
1.224 brouard 6294: #else
1.317 brouard 6295: 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 6296: if(firsthree == 0){
1.302 brouard 6297: 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 6298: firsthree=1;
1.317 brouard 6299: }else if(firsthree >=1 && firsthree < 10){
6300: 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);
6301: firsthree++;
6302: }else if(firsthree == 10){
6303: printf("Information, too many Information flags: no more reported to log either\n");
6304: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6305: firsthree++;
6306: }else{
6307: firsthree++;
1.227 brouard 6308: }
1.309 brouard 6309: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6310: mli=m;
6311: }
6312: if(s[m][i]==-2){ /* Vital status is really unknown */
6313: nbwarn++;
1.309 brouard 6314: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6315: 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);
6316: 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);
6317: }
6318: break;
6319: }
6320: break;
1.224 brouard 6321: #endif
1.227 brouard 6322: }/* End m >= lastpass */
1.126 brouard 6323: }/* end while */
1.224 brouard 6324:
1.227 brouard 6325: /* 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 6326: /* After last pass */
1.224 brouard 6327: /* Treating death states */
1.214 brouard 6328: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6329: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6330: /* } */
1.126 brouard 6331: mi++; /* Death is another wave */
6332: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6333: /* Only death is a correct wave */
1.126 brouard 6334: mw[mi][i]=m;
1.257 brouard 6335: } /* else not in a death state */
1.224 brouard 6336: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6337: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6338: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6339: 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 6340: nbwarn++;
6341: if(firstfiv==0){
1.309 brouard 6342: 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 6343: firstfiv=1;
6344: }else{
1.309 brouard 6345: 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 6346: }
1.309 brouard 6347: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6348: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6349: nberr++;
6350: if(firstwo==0){
1.309 brouard 6351: 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 6352: firstwo=1;
6353: }
1.309 brouard 6354: 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 6355: }
1.257 brouard 6356: }else{ /* if date of interview is unknown */
1.227 brouard 6357: /* death is known but not confirmed by death status at any wave */
6358: if(firstfour==0){
1.309 brouard 6359: 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 6360: firstfour=1;
6361: }
1.309 brouard 6362: 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 6363: }
1.224 brouard 6364: } /* end if date of death is known */
6365: #endif
1.309 brouard 6366: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6367: /* wav[i]=mw[mi][i]; */
1.126 brouard 6368: if(mi==0){
6369: nbwarn++;
6370: if(first==0){
1.227 brouard 6371: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6372: first=1;
1.126 brouard 6373: }
6374: if(first==1){
1.227 brouard 6375: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6376: }
6377: } /* end mi==0 */
6378: } /* End individuals */
1.214 brouard 6379: /* wav and mw are no more changed */
1.223 brouard 6380:
1.317 brouard 6381: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6382: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6383:
6384:
1.126 brouard 6385: for(i=1; i<=imx; i++){
6386: for(mi=1; mi<wav[i];mi++){
6387: if (stepm <=0)
1.227 brouard 6388: dh[mi][i]=1;
1.126 brouard 6389: else{
1.260 brouard 6390: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6391: if (agedc[i] < 2*AGESUP) {
6392: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6393: if(j==0) j=1; /* Survives at least one month after exam */
6394: else if(j<0){
6395: nberr++;
6396: 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]);
6397: j=1; /* Temporary Dangerous patch */
6398: 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);
6399: 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]);
6400: 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);
6401: }
6402: k=k+1;
6403: if (j >= jmax){
6404: jmax=j;
6405: ijmax=i;
6406: }
6407: if (j <= jmin){
6408: jmin=j;
6409: ijmin=i;
6410: }
6411: sum=sum+j;
6412: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6413: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6414: }
6415: }
6416: else{
6417: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6418: /* 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 6419:
1.227 brouard 6420: k=k+1;
6421: if (j >= jmax) {
6422: jmax=j;
6423: ijmax=i;
6424: }
6425: else if (j <= jmin){
6426: jmin=j;
6427: ijmin=i;
6428: }
6429: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6430: /*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]);*/
6431: if(j<0){
6432: nberr++;
6433: 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]);
6434: 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]);
6435: }
6436: sum=sum+j;
6437: }
6438: jk= j/stepm;
6439: jl= j -jk*stepm;
6440: ju= j -(jk+1)*stepm;
6441: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6442: if(jl==0){
6443: dh[mi][i]=jk;
6444: bh[mi][i]=0;
6445: }else{ /* We want a negative bias in order to only have interpolation ie
6446: * to avoid the price of an extra matrix product in likelihood */
6447: dh[mi][i]=jk+1;
6448: bh[mi][i]=ju;
6449: }
6450: }else{
6451: if(jl <= -ju){
6452: dh[mi][i]=jk;
6453: bh[mi][i]=jl; /* bias is positive if real duration
6454: * is higher than the multiple of stepm and negative otherwise.
6455: */
6456: }
6457: else{
6458: dh[mi][i]=jk+1;
6459: bh[mi][i]=ju;
6460: }
6461: if(dh[mi][i]==0){
6462: dh[mi][i]=1; /* At least one step */
6463: bh[mi][i]=ju; /* At least one step */
6464: /* 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);*/
6465: }
6466: } /* end if mle */
1.126 brouard 6467: }
6468: } /* end wave */
6469: }
6470: jmean=sum/k;
6471: 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 6472: 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 6473: }
1.126 brouard 6474:
6475: /*********** Tricode ****************************/
1.220 brouard 6476: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6477: {
6478: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6479: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6480: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6481: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6482: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6483: */
1.130 brouard 6484:
1.242 brouard 6485: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6486: int modmaxcovj=0; /* Modality max of covariates j */
6487: int cptcode=0; /* Modality max of covariates j */
6488: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6489:
6490:
1.242 brouard 6491: /* cptcoveff=0; */
6492: /* *cptcov=0; */
1.126 brouard 6493:
1.242 brouard 6494: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6495: for (k=1; k <= maxncov; k++)
6496: for(j=1; j<=2; j++)
6497: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6498:
1.242 brouard 6499: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6500: 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 6501: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6502: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 6503: 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 6504: switch(Fixed[k]) {
6505: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6506: modmaxcovj=0;
6507: modmincovj=0;
1.242 brouard 6508: 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 6509: /* 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 6510: ij=(int)(covar[Tvar[k]][i]);
6511: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6512: * If product of Vn*Vm, still boolean *:
6513: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6514: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6515: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6516: modality of the nth covariate of individual i. */
6517: if (ij > modmaxcovj)
6518: modmaxcovj=ij;
6519: else if (ij < modmincovj)
6520: modmincovj=ij;
1.287 brouard 6521: if (ij <0 || ij >1 ){
1.311 brouard 6522: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6523: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6524: fflush(ficlog);
6525: exit(1);
1.287 brouard 6526: }
6527: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6528: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6529: exit(1);
6530: }else
6531: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6532: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6533: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6534: /* getting the maximum value of the modality of the covariate
6535: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6536: female ies 1, then modmaxcovj=1.
6537: */
6538: } /* end for loop on individuals i */
6539: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6540: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6541: cptcode=modmaxcovj;
6542: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6543: /*for (i=0; i<=cptcode; i++) {*/
6544: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6545: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6546: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6547: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6548: if( j != -1){
6549: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6550: covariate for which somebody answered excluding
6551: undefined. Usually 2: 0 and 1. */
6552: }
6553: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6554: covariate for which somebody answered including
6555: undefined. Usually 3: -1, 0 and 1. */
6556: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6557: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6558: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6559:
1.242 brouard 6560: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6561: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6562: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6563: /* modmincovj=3; modmaxcovj = 7; */
6564: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6565: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6566: /* defining two dummy variables: variables V1_1 and V1_2.*/
6567: /* nbcode[Tvar[j]][ij]=k; */
6568: /* nbcode[Tvar[j]][1]=0; */
6569: /* nbcode[Tvar[j]][2]=1; */
6570: /* nbcode[Tvar[j]][3]=2; */
6571: /* To be continued (not working yet). */
6572: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6573:
6574: /* 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*/
6575: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6576: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6577: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6578: /*, could be restored in the future */
6579: 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 6580: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6581: break;
6582: }
6583: ij++;
1.287 brouard 6584: 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 6585: cptcode = ij; /* New max modality for covar j */
6586: } /* end of loop on modality i=-1 to 1 or more */
6587: break;
6588: case 1: /* Testing on varying covariate, could be simple and
6589: * should look at waves or product of fixed *
6590: * varying. No time to test -1, assuming 0 and 1 only */
6591: ij=0;
6592: for(i=0; i<=1;i++){
6593: nbcode[Tvar[k]][++ij]=i;
6594: }
6595: break;
6596: default:
6597: break;
6598: } /* end switch */
6599: } /* end dummy test */
1.349 brouard 6600: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6601: 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 6602: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6603: printf("Error k=%d \n",k);
6604: exit(1);
6605: }
1.311 brouard 6606: if(isnan(covar[Tvar[k]][i])){
6607: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6608: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6609: fflush(ficlog);
6610: exit(1);
6611: }
6612: }
1.335 brouard 6613: } /* end Quanti */
1.287 brouard 6614: } /* 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 6615:
6616: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6617: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6618: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6619: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6620: 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 */
6621: 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 */
6622: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6623: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6624:
6625: ij=0;
6626: /* 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 6627: 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 */
6628: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6629: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6630: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6631: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6632: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6633: /* 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 6634: /* If product not in single variable we don't print results */
6635: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6636: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6637: /* k= 1 2 3 4 5 6 7 8 9 */
6638: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6639: /* ij 1 2 3 */
6640: /* Tvaraff[ij]= 4 3 1 */
6641: /* Tmodelind[ij]=2 3 9 */
6642: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6643: 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*/
6644: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6645: 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 */
6646: if(Fixed[k]!=0)
6647: anyvaryingduminmodel=1;
6648: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6649: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6650: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6651: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6652: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6653: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6654: }
6655: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6656: /* ij--; */
6657: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6658: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6659: * because they can be excluded from the model and real
6660: * if in the model but excluded because missing values, but how to get k from ij?*/
6661: for(j=ij+1; j<= cptcovt; j++){
6662: Tvaraff[j]=0;
6663: Tmodelind[j]=0;
6664: }
6665: for(j=ntveff+1; j<= cptcovt; j++){
6666: TmodelInvind[j]=0;
6667: }
6668: /* To be sorted */
6669: ;
6670: }
1.126 brouard 6671:
1.145 brouard 6672:
1.126 brouard 6673: /*********** Health Expectancies ****************/
6674:
1.235 brouard 6675: 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 6676:
6677: {
6678: /* Health expectancies, no variances */
1.329 brouard 6679: /* cij is the combination in the list of combination of dummy covariates */
6680: /* strstart is a string of time at start of computing */
1.164 brouard 6681: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6682: int nhstepma, nstepma; /* Decreasing with age */
6683: double age, agelim, hf;
6684: double ***p3mat;
6685: double eip;
6686:
1.238 brouard 6687: /* pstamp(ficreseij); */
1.126 brouard 6688: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6689: fprintf(ficreseij,"# Age");
6690: for(i=1; i<=nlstate;i++){
6691: for(j=1; j<=nlstate;j++){
6692: fprintf(ficreseij," e%1d%1d ",i,j);
6693: }
6694: fprintf(ficreseij," e%1d. ",i);
6695: }
6696: fprintf(ficreseij,"\n");
6697:
6698:
6699: if(estepm < stepm){
6700: printf ("Problem %d lower than %d\n",estepm, stepm);
6701: }
6702: else hstepm=estepm;
6703: /* We compute the life expectancy from trapezoids spaced every estepm months
6704: * This is mainly to measure the difference between two models: for example
6705: * if stepm=24 months pijx are given only every 2 years and by summing them
6706: * we are calculating an estimate of the Life Expectancy assuming a linear
6707: * progression in between and thus overestimating or underestimating according
6708: * to the curvature of the survival function. If, for the same date, we
6709: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6710: * to compare the new estimate of Life expectancy with the same linear
6711: * hypothesis. A more precise result, taking into account a more precise
6712: * curvature will be obtained if estepm is as small as stepm. */
6713:
6714: /* For example we decided to compute the life expectancy with the smallest unit */
6715: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6716: nhstepm is the number of hstepm from age to agelim
6717: nstepm is the number of stepm from age to agelin.
1.270 brouard 6718: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6719: and note for a fixed period like estepm months */
6720: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6721: survival function given by stepm (the optimization length). Unfortunately it
6722: means that if the survival funtion is printed only each two years of age and if
6723: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6724: results. So we changed our mind and took the option of the best precision.
6725: */
6726: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6727:
6728: agelim=AGESUP;
6729: /* If stepm=6 months */
6730: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6731: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6732:
6733: /* nhstepm age range expressed in number of stepm */
6734: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6735: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6736: /* if (stepm >= YEARM) hstepm=1;*/
6737: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6738: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6739:
6740: for (age=bage; age<=fage; age ++){
6741: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6742: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6743: /* if (stepm >= YEARM) hstepm=1;*/
6744: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6745:
6746: /* If stepm=6 months */
6747: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6748: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6749: /* 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 6750: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6751:
6752: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6753:
6754: printf("%d|",(int)age);fflush(stdout);
6755: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6756:
6757: /* Computing expectancies */
6758: for(i=1; i<=nlstate;i++)
6759: for(j=1; j<=nlstate;j++)
6760: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6761: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6762:
6763: /* 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]);*/
6764:
6765: }
6766:
6767: fprintf(ficreseij,"%3.0f",age );
6768: for(i=1; i<=nlstate;i++){
6769: eip=0;
6770: for(j=1; j<=nlstate;j++){
6771: eip +=eij[i][j][(int)age];
6772: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6773: }
6774: fprintf(ficreseij,"%9.4f", eip );
6775: }
6776: fprintf(ficreseij,"\n");
6777:
6778: }
6779: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6780: printf("\n");
6781: fprintf(ficlog,"\n");
6782:
6783: }
6784:
1.235 brouard 6785: 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 6786:
6787: {
6788: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6789: to initial status i, ei. .
1.126 brouard 6790: */
1.336 brouard 6791: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6792: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6793: int nhstepma, nstepma; /* Decreasing with age */
6794: double age, agelim, hf;
6795: double ***p3matp, ***p3matm, ***varhe;
6796: double **dnewm,**doldm;
6797: double *xp, *xm;
6798: double **gp, **gm;
6799: double ***gradg, ***trgradg;
6800: int theta;
6801:
6802: double eip, vip;
6803:
6804: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6805: xp=vector(1,npar);
6806: xm=vector(1,npar);
6807: dnewm=matrix(1,nlstate*nlstate,1,npar);
6808: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6809:
6810: pstamp(ficresstdeij);
6811: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6812: fprintf(ficresstdeij,"# Age");
6813: for(i=1; i<=nlstate;i++){
6814: for(j=1; j<=nlstate;j++)
6815: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6816: fprintf(ficresstdeij," e%1d. ",i);
6817: }
6818: fprintf(ficresstdeij,"\n");
6819:
6820: pstamp(ficrescveij);
6821: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6822: fprintf(ficrescveij,"# Age");
6823: for(i=1; i<=nlstate;i++)
6824: for(j=1; j<=nlstate;j++){
6825: cptj= (j-1)*nlstate+i;
6826: for(i2=1; i2<=nlstate;i2++)
6827: for(j2=1; j2<=nlstate;j2++){
6828: cptj2= (j2-1)*nlstate+i2;
6829: if(cptj2 <= cptj)
6830: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6831: }
6832: }
6833: fprintf(ficrescveij,"\n");
6834:
6835: if(estepm < stepm){
6836: printf ("Problem %d lower than %d\n",estepm, stepm);
6837: }
6838: else hstepm=estepm;
6839: /* We compute the life expectancy from trapezoids spaced every estepm months
6840: * This is mainly to measure the difference between two models: for example
6841: * if stepm=24 months pijx are given only every 2 years and by summing them
6842: * we are calculating an estimate of the Life Expectancy assuming a linear
6843: * progression in between and thus overestimating or underestimating according
6844: * to the curvature of the survival function. If, for the same date, we
6845: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6846: * to compare the new estimate of Life expectancy with the same linear
6847: * hypothesis. A more precise result, taking into account a more precise
6848: * curvature will be obtained if estepm is as small as stepm. */
6849:
6850: /* For example we decided to compute the life expectancy with the smallest unit */
6851: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6852: nhstepm is the number of hstepm from age to agelim
6853: nstepm is the number of stepm from age to agelin.
6854: Look at hpijx to understand the reason of that which relies in memory size
6855: and note for a fixed period like estepm months */
6856: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6857: survival function given by stepm (the optimization length). Unfortunately it
6858: means that if the survival funtion is printed only each two years of age and if
6859: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6860: results. So we changed our mind and took the option of the best precision.
6861: */
6862: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6863:
6864: /* If stepm=6 months */
6865: /* nhstepm age range expressed in number of stepm */
6866: agelim=AGESUP;
6867: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6868: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6869: /* if (stepm >= YEARM) hstepm=1;*/
6870: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6871:
6872: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6873: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6874: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6875: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6876: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6877: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6878:
6879: for (age=bage; age<=fage; age ++){
6880: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6881: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6882: /* if (stepm >= YEARM) hstepm=1;*/
6883: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6884:
1.126 brouard 6885: /* If stepm=6 months */
6886: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6887: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6888:
6889: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6890:
1.126 brouard 6891: /* Computing Variances of health expectancies */
6892: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6893: decrease memory allocation */
6894: for(theta=1; theta <=npar; theta++){
6895: for(i=1; i<=npar; i++){
1.222 brouard 6896: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6897: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6898: }
1.235 brouard 6899: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6900: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6901:
1.126 brouard 6902: for(j=1; j<= nlstate; j++){
1.222 brouard 6903: for(i=1; i<=nlstate; i++){
6904: for(h=0; h<=nhstepm-1; h++){
6905: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6906: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6907: }
6908: }
1.126 brouard 6909: }
1.218 brouard 6910:
1.126 brouard 6911: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6912: for(h=0; h<=nhstepm-1; h++){
6913: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6914: }
1.126 brouard 6915: }/* End theta */
6916:
6917:
6918: for(h=0; h<=nhstepm-1; h++)
6919: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6920: for(theta=1; theta <=npar; theta++)
6921: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6922:
1.218 brouard 6923:
1.222 brouard 6924: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6925: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6926: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6927:
1.222 brouard 6928: printf("%d|",(int)age);fflush(stdout);
6929: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6930: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6931: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6932: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6933: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6934: for(ij=1;ij<=nlstate*nlstate;ij++)
6935: for(ji=1;ji<=nlstate*nlstate;ji++)
6936: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6937: }
6938: }
1.320 brouard 6939: /* if((int)age ==50){ */
6940: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6941: /* } */
1.126 brouard 6942: /* Computing expectancies */
1.235 brouard 6943: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6944: for(i=1; i<=nlstate;i++)
6945: for(j=1; j<=nlstate;j++)
1.222 brouard 6946: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6947: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6948:
1.222 brouard 6949: /* 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 6950:
1.222 brouard 6951: }
1.269 brouard 6952:
6953: /* Standard deviation of expectancies ij */
1.126 brouard 6954: fprintf(ficresstdeij,"%3.0f",age );
6955: for(i=1; i<=nlstate;i++){
6956: eip=0.;
6957: vip=0.;
6958: for(j=1; j<=nlstate;j++){
1.222 brouard 6959: eip += eij[i][j][(int)age];
6960: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6961: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6962: 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 6963: }
6964: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6965: }
6966: fprintf(ficresstdeij,"\n");
1.218 brouard 6967:
1.269 brouard 6968: /* Variance of expectancies ij */
1.126 brouard 6969: fprintf(ficrescveij,"%3.0f",age );
6970: for(i=1; i<=nlstate;i++)
6971: for(j=1; j<=nlstate;j++){
1.222 brouard 6972: cptj= (j-1)*nlstate+i;
6973: for(i2=1; i2<=nlstate;i2++)
6974: for(j2=1; j2<=nlstate;j2++){
6975: cptj2= (j2-1)*nlstate+i2;
6976: if(cptj2 <= cptj)
6977: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6978: }
1.126 brouard 6979: }
6980: fprintf(ficrescveij,"\n");
1.218 brouard 6981:
1.126 brouard 6982: }
6983: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6984: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6985: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6986: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6987: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6988: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6989: printf("\n");
6990: fprintf(ficlog,"\n");
1.218 brouard 6991:
1.126 brouard 6992: free_vector(xm,1,npar);
6993: free_vector(xp,1,npar);
6994: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6995: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6996: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6997: }
1.218 brouard 6998:
1.126 brouard 6999: /************ Variance ******************/
1.235 brouard 7000: 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 7001: {
1.279 brouard 7002: /** Variance of health expectancies
7003: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
7004: * double **newm;
7005: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
7006: */
1.218 brouard 7007:
7008: /* int movingaverage(); */
7009: double **dnewm,**doldm;
7010: double **dnewmp,**doldmp;
7011: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 7012: int first=0;
1.218 brouard 7013: int k;
7014: double *xp;
1.279 brouard 7015: double **gp, **gm; /**< for var eij */
7016: double ***gradg, ***trgradg; /**< for var eij */
7017: double **gradgp, **trgradgp; /**< for var p point j */
7018: double *gpp, *gmp; /**< for var p point j */
7019: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 7020: double ***p3mat;
7021: double age,agelim, hf;
7022: /* double ***mobaverage; */
7023: int theta;
7024: char digit[4];
7025: char digitp[25];
7026:
7027: char fileresprobmorprev[FILENAMELENGTH];
7028:
7029: if(popbased==1){
7030: if(mobilav!=0)
7031: strcpy(digitp,"-POPULBASED-MOBILAV_");
7032: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
7033: }
7034: else
7035: strcpy(digitp,"-STABLBASED_");
1.126 brouard 7036:
1.218 brouard 7037: /* if (mobilav!=0) { */
7038: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7039: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
7040: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
7041: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
7042: /* } */
7043: /* } */
7044:
7045: strcpy(fileresprobmorprev,"PRMORPREV-");
7046: sprintf(digit,"%-d",ij);
7047: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7048: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7049: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7050: strcat(fileresprobmorprev,fileresu);
7051: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7052: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7053: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7054: }
7055: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7056: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7057: pstamp(ficresprobmorprev);
7058: 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 7059: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7060:
7061: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7062: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7063: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7064: /* } */
7065: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7066: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7067: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7068: }
1.337 brouard 7069: /* for(j=1;j<=cptcoveff;j++) */
7070: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7071: fprintf(ficresprobmorprev,"\n");
7072:
1.218 brouard 7073: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7074: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7075: fprintf(ficresprobmorprev," p.%-d SE",j);
7076: for(i=1; i<=nlstate;i++)
7077: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7078: }
7079: fprintf(ficresprobmorprev,"\n");
7080:
7081: fprintf(ficgp,"\n# Routine varevsij");
7082: fprintf(ficgp,"\nunset title \n");
7083: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7084: 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");
7085: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7086:
1.218 brouard 7087: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7088: pstamp(ficresvij);
7089: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7090: if(popbased==1)
7091: 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);
7092: else
7093: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7094: fprintf(ficresvij,"# Age");
7095: for(i=1; i<=nlstate;i++)
7096: for(j=1; j<=nlstate;j++)
7097: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7098: fprintf(ficresvij,"\n");
7099:
7100: xp=vector(1,npar);
7101: dnewm=matrix(1,nlstate,1,npar);
7102: doldm=matrix(1,nlstate,1,nlstate);
7103: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7104: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7105:
7106: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7107: gpp=vector(nlstate+1,nlstate+ndeath);
7108: gmp=vector(nlstate+1,nlstate+ndeath);
7109: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7110:
1.218 brouard 7111: if(estepm < stepm){
7112: printf ("Problem %d lower than %d\n",estepm, stepm);
7113: }
7114: else hstepm=estepm;
7115: /* For example we decided to compute the life expectancy with the smallest unit */
7116: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7117: nhstepm is the number of hstepm from age to agelim
7118: nstepm is the number of stepm from age to agelim.
7119: Look at function hpijx to understand why because of memory size limitations,
7120: we decided (b) to get a life expectancy respecting the most precise curvature of the
7121: survival function given by stepm (the optimization length). Unfortunately it
7122: means that if the survival funtion is printed every two years of age and if
7123: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7124: results. So we changed our mind and took the option of the best precision.
7125: */
7126: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7127: agelim = AGESUP;
7128: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7129: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7130: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7131: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7132: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7133: gp=matrix(0,nhstepm,1,nlstate);
7134: gm=matrix(0,nhstepm,1,nlstate);
7135:
7136:
7137: for(theta=1; theta <=npar; theta++){
7138: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7139: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7140: }
1.279 brouard 7141: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7142: * returns into prlim .
1.288 brouard 7143: */
1.242 brouard 7144: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7145:
7146: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7147: if (popbased==1) {
7148: if(mobilav ==0){
7149: for(i=1; i<=nlstate;i++)
7150: prlim[i][i]=probs[(int)age][i][ij];
7151: }else{ /* mobilav */
7152: for(i=1; i<=nlstate;i++)
7153: prlim[i][i]=mobaverage[(int)age][i][ij];
7154: }
7155: }
1.295 brouard 7156: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7157: */
7158: 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 7159: /**< 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 7160: * at horizon h in state j including mortality.
7161: */
1.218 brouard 7162: for(j=1; j<= nlstate; j++){
7163: for(h=0; h<=nhstepm; h++){
7164: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7165: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7166: }
7167: }
1.279 brouard 7168: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7169: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7170: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7171: */
7172: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7173: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7174: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7175: }
7176:
7177: /* Again with minus shift */
1.218 brouard 7178:
7179: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7180: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7181:
1.242 brouard 7182: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7183:
7184: if (popbased==1) {
7185: if(mobilav ==0){
7186: for(i=1; i<=nlstate;i++)
7187: prlim[i][i]=probs[(int)age][i][ij];
7188: }else{ /* mobilav */
7189: for(i=1; i<=nlstate;i++)
7190: prlim[i][i]=mobaverage[(int)age][i][ij];
7191: }
7192: }
7193:
1.235 brouard 7194: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7195:
7196: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7197: for(h=0; h<=nhstepm; h++){
7198: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7199: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7200: }
7201: }
7202: /* This for computing probability of death (h=1 means
7203: computed over hstepm matrices product = hstepm*stepm months)
7204: as a weighted average of prlim.
7205: */
7206: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7207: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7208: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7209: }
1.279 brouard 7210: /* end shifting computations */
7211:
7212: /**< Computing gradient matrix at horizon h
7213: */
1.218 brouard 7214: for(j=1; j<= nlstate; j++) /* vareij */
7215: for(h=0; h<=nhstepm; h++){
7216: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7217: }
1.279 brouard 7218: /**< Gradient of overall mortality p.3 (or p.j)
7219: */
7220: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7221: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7222: }
7223:
7224: } /* End theta */
1.279 brouard 7225:
7226: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7227: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7228:
7229: for(h=0; h<=nhstepm; h++) /* veij */
7230: for(j=1; j<=nlstate;j++)
7231: for(theta=1; theta <=npar; theta++)
7232: trgradg[h][j][theta]=gradg[h][theta][j];
7233:
7234: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7235: for(theta=1; theta <=npar; theta++)
7236: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7237: /**< as well as its transposed matrix
7238: */
1.218 brouard 7239:
7240: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7241: for(i=1;i<=nlstate;i++)
7242: for(j=1;j<=nlstate;j++)
7243: vareij[i][j][(int)age] =0.;
1.279 brouard 7244:
7245: /* Computing trgradg by matcov by gradg at age and summing over h
7246: * and k (nhstepm) formula 15 of article
7247: * Lievre-Brouard-Heathcote
7248: */
7249:
1.218 brouard 7250: for(h=0;h<=nhstepm;h++){
7251: for(k=0;k<=nhstepm;k++){
7252: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7253: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7254: for(i=1;i<=nlstate;i++)
7255: for(j=1;j<=nlstate;j++)
7256: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7257: }
7258: }
7259:
1.279 brouard 7260: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7261: * p.j overall mortality formula 49 but computed directly because
7262: * we compute the grad (wix pijx) instead of grad (pijx),even if
7263: * wix is independent of theta.
7264: */
1.218 brouard 7265: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7266: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7267: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7268: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7269: varppt[j][i]=doldmp[j][i];
7270: /* end ppptj */
7271: /* x centered again */
7272:
1.242 brouard 7273: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7274:
7275: if (popbased==1) {
7276: if(mobilav ==0){
7277: for(i=1; i<=nlstate;i++)
7278: prlim[i][i]=probs[(int)age][i][ij];
7279: }else{ /* mobilav */
7280: for(i=1; i<=nlstate;i++)
7281: prlim[i][i]=mobaverage[(int)age][i][ij];
7282: }
7283: }
7284:
7285: /* This for computing probability of death (h=1 means
7286: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7287: as a weighted average of prlim.
7288: */
1.235 brouard 7289: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7290: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7291: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7292: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7293: }
7294: /* end probability of death */
7295:
7296: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7297: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7298: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7299: for(i=1; i<=nlstate;i++){
7300: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7301: }
7302: }
7303: fprintf(ficresprobmorprev,"\n");
7304:
7305: fprintf(ficresvij,"%.0f ",age );
7306: for(i=1; i<=nlstate;i++)
7307: for(j=1; j<=nlstate;j++){
7308: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7309: }
7310: fprintf(ficresvij,"\n");
7311: free_matrix(gp,0,nhstepm,1,nlstate);
7312: free_matrix(gm,0,nhstepm,1,nlstate);
7313: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7314: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7315: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7316: } /* End age */
7317: free_vector(gpp,nlstate+1,nlstate+ndeath);
7318: free_vector(gmp,nlstate+1,nlstate+ndeath);
7319: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7320: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7321: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7322: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7323: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7324: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7325: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7326: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7327: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7328: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7329: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7330: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7331: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7332: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7333: 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);
7334: /* 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 7335: */
1.218 brouard 7336: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7337: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7338:
1.218 brouard 7339: free_vector(xp,1,npar);
7340: free_matrix(doldm,1,nlstate,1,nlstate);
7341: free_matrix(dnewm,1,nlstate,1,npar);
7342: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7343: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7344: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7345: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7346: fclose(ficresprobmorprev);
7347: fflush(ficgp);
7348: fflush(fichtm);
7349: } /* end varevsij */
1.126 brouard 7350:
7351: /************ Variance of prevlim ******************/
1.269 brouard 7352: 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 7353: {
1.205 brouard 7354: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7355: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7356:
1.268 brouard 7357: double **dnewmpar,**doldm;
1.126 brouard 7358: int i, j, nhstepm, hstepm;
7359: double *xp;
7360: double *gp, *gm;
7361: double **gradg, **trgradg;
1.208 brouard 7362: double **mgm, **mgp;
1.126 brouard 7363: double age,agelim;
7364: int theta;
7365:
7366: pstamp(ficresvpl);
1.288 brouard 7367: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7368: fprintf(ficresvpl,"# Age ");
7369: if(nresult >=1)
7370: fprintf(ficresvpl," Result# ");
1.126 brouard 7371: for(i=1; i<=nlstate;i++)
7372: fprintf(ficresvpl," %1d-%1d",i,i);
7373: fprintf(ficresvpl,"\n");
7374:
7375: xp=vector(1,npar);
1.268 brouard 7376: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7377: doldm=matrix(1,nlstate,1,nlstate);
7378:
7379: hstepm=1*YEARM; /* Every year of age */
7380: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7381: agelim = AGESUP;
7382: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7383: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7384: if (stepm >= YEARM) hstepm=1;
7385: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7386: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7387: mgp=matrix(1,npar,1,nlstate);
7388: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7389: gp=vector(1,nlstate);
7390: gm=vector(1,nlstate);
7391:
7392: for(theta=1; theta <=npar; theta++){
7393: for(i=1; i<=npar; i++){ /* Computes gradient */
7394: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7395: }
1.288 brouard 7396: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7397: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7398: /* else */
7399: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7400: for(i=1;i<=nlstate;i++){
1.126 brouard 7401: gp[i] = prlim[i][i];
1.208 brouard 7402: mgp[theta][i] = prlim[i][i];
7403: }
1.126 brouard 7404: for(i=1; i<=npar; i++) /* Computes gradient */
7405: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7406: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7407: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7408: /* else */
7409: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7410: for(i=1;i<=nlstate;i++){
1.126 brouard 7411: gm[i] = prlim[i][i];
1.208 brouard 7412: mgm[theta][i] = prlim[i][i];
7413: }
1.126 brouard 7414: for(i=1;i<=nlstate;i++)
7415: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7416: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7417: } /* End theta */
7418:
7419: trgradg =matrix(1,nlstate,1,npar);
7420:
7421: for(j=1; j<=nlstate;j++)
7422: for(theta=1; theta <=npar; theta++)
7423: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7424: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7425: /* printf("\nmgm mgp %d ",(int)age); */
7426: /* for(j=1; j<=nlstate;j++){ */
7427: /* printf(" %d ",j); */
7428: /* for(theta=1; theta <=npar; theta++) */
7429: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7430: /* printf("\n "); */
7431: /* } */
7432: /* } */
7433: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7434: /* printf("\n gradg %d ",(int)age); */
7435: /* for(j=1; j<=nlstate;j++){ */
7436: /* printf("%d ",j); */
7437: /* for(theta=1; theta <=npar; theta++) */
7438: /* printf("%d %lf ",theta,gradg[theta][j]); */
7439: /* printf("\n "); */
7440: /* } */
7441: /* } */
1.126 brouard 7442:
7443: for(i=1;i<=nlstate;i++)
7444: varpl[i][(int)age] =0.;
1.209 brouard 7445: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7446: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7447: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7448: }else{
1.268 brouard 7449: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7450: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7451: }
1.126 brouard 7452: for(i=1;i<=nlstate;i++)
7453: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7454:
7455: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7456: if(nresult >=1)
7457: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7458: for(i=1; i<=nlstate;i++){
1.126 brouard 7459: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7460: /* for(j=1;j<=nlstate;j++) */
7461: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7462: }
1.126 brouard 7463: fprintf(ficresvpl,"\n");
7464: free_vector(gp,1,nlstate);
7465: free_vector(gm,1,nlstate);
1.208 brouard 7466: free_matrix(mgm,1,npar,1,nlstate);
7467: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7468: free_matrix(gradg,1,npar,1,nlstate);
7469: free_matrix(trgradg,1,nlstate,1,npar);
7470: } /* End age */
7471:
7472: free_vector(xp,1,npar);
7473: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7474: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7475:
7476: }
7477:
7478:
7479: /************ Variance of backprevalence limit ******************/
1.269 brouard 7480: 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 7481: {
7482: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7483: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7484:
7485: double **dnewmpar,**doldm;
7486: int i, j, nhstepm, hstepm;
7487: double *xp;
7488: double *gp, *gm;
7489: double **gradg, **trgradg;
7490: double **mgm, **mgp;
7491: double age,agelim;
7492: int theta;
7493:
7494: pstamp(ficresvbl);
7495: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7496: fprintf(ficresvbl,"# Age ");
7497: if(nresult >=1)
7498: fprintf(ficresvbl," Result# ");
7499: for(i=1; i<=nlstate;i++)
7500: fprintf(ficresvbl," %1d-%1d",i,i);
7501: fprintf(ficresvbl,"\n");
7502:
7503: xp=vector(1,npar);
7504: dnewmpar=matrix(1,nlstate,1,npar);
7505: doldm=matrix(1,nlstate,1,nlstate);
7506:
7507: hstepm=1*YEARM; /* Every year of age */
7508: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7509: agelim = AGEINF;
7510: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7511: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7512: if (stepm >= YEARM) hstepm=1;
7513: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7514: gradg=matrix(1,npar,1,nlstate);
7515: mgp=matrix(1,npar,1,nlstate);
7516: mgm=matrix(1,npar,1,nlstate);
7517: gp=vector(1,nlstate);
7518: gm=vector(1,nlstate);
7519:
7520: for(theta=1; theta <=npar; theta++){
7521: for(i=1; i<=npar; i++){ /* Computes gradient */
7522: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7523: }
7524: if(mobilavproj > 0 )
7525: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7526: else
7527: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7528: for(i=1;i<=nlstate;i++){
7529: gp[i] = bprlim[i][i];
7530: mgp[theta][i] = bprlim[i][i];
7531: }
7532: for(i=1; i<=npar; i++) /* Computes gradient */
7533: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7534: if(mobilavproj > 0 )
7535: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7536: else
7537: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7538: for(i=1;i<=nlstate;i++){
7539: gm[i] = bprlim[i][i];
7540: mgm[theta][i] = bprlim[i][i];
7541: }
7542: for(i=1;i<=nlstate;i++)
7543: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7544: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7545: } /* End theta */
7546:
7547: trgradg =matrix(1,nlstate,1,npar);
7548:
7549: for(j=1; j<=nlstate;j++)
7550: for(theta=1; theta <=npar; theta++)
7551: trgradg[j][theta]=gradg[theta][j];
7552: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7553: /* printf("\nmgm mgp %d ",(int)age); */
7554: /* for(j=1; j<=nlstate;j++){ */
7555: /* printf(" %d ",j); */
7556: /* for(theta=1; theta <=npar; theta++) */
7557: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7558: /* printf("\n "); */
7559: /* } */
7560: /* } */
7561: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7562: /* printf("\n gradg %d ",(int)age); */
7563: /* for(j=1; j<=nlstate;j++){ */
7564: /* printf("%d ",j); */
7565: /* for(theta=1; theta <=npar; theta++) */
7566: /* printf("%d %lf ",theta,gradg[theta][j]); */
7567: /* printf("\n "); */
7568: /* } */
7569: /* } */
7570:
7571: for(i=1;i<=nlstate;i++)
7572: varbpl[i][(int)age] =0.;
7573: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7574: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7575: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7576: }else{
7577: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7578: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7579: }
7580: for(i=1;i<=nlstate;i++)
7581: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7582:
7583: fprintf(ficresvbl,"%.0f ",age );
7584: if(nresult >=1)
7585: fprintf(ficresvbl,"%d ",nres );
7586: for(i=1; i<=nlstate;i++)
7587: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7588: fprintf(ficresvbl,"\n");
7589: free_vector(gp,1,nlstate);
7590: free_vector(gm,1,nlstate);
7591: free_matrix(mgm,1,npar,1,nlstate);
7592: free_matrix(mgp,1,npar,1,nlstate);
7593: free_matrix(gradg,1,npar,1,nlstate);
7594: free_matrix(trgradg,1,nlstate,1,npar);
7595: } /* End age */
7596:
7597: free_vector(xp,1,npar);
7598: free_matrix(doldm,1,nlstate,1,npar);
7599: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7600:
7601: }
7602:
7603: /************ Variance of one-step probabilities ******************/
7604: 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 7605: {
7606: int i, j=0, k1, l1, tj;
7607: int k2, l2, j1, z1;
7608: int k=0, l;
7609: int first=1, first1, first2;
1.326 brouard 7610: int nres=0; /* New */
1.222 brouard 7611: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7612: double **dnewm,**doldm;
7613: double *xp;
7614: double *gp, *gm;
7615: double **gradg, **trgradg;
7616: double **mu;
7617: double age, cov[NCOVMAX+1];
7618: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7619: int theta;
7620: char fileresprob[FILENAMELENGTH];
7621: char fileresprobcov[FILENAMELENGTH];
7622: char fileresprobcor[FILENAMELENGTH];
7623: double ***varpij;
7624:
7625: strcpy(fileresprob,"PROB_");
7626: strcat(fileresprob,fileres);
7627: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7628: printf("Problem with resultfile: %s\n", fileresprob);
7629: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7630: }
7631: strcpy(fileresprobcov,"PROBCOV_");
7632: strcat(fileresprobcov,fileresu);
7633: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7634: printf("Problem with resultfile: %s\n", fileresprobcov);
7635: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7636: }
7637: strcpy(fileresprobcor,"PROBCOR_");
7638: strcat(fileresprobcor,fileresu);
7639: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7640: printf("Problem with resultfile: %s\n", fileresprobcor);
7641: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7642: }
7643: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7644: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7645: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7646: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7647: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7648: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7649: pstamp(ficresprob);
7650: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7651: fprintf(ficresprob,"# Age");
7652: pstamp(ficresprobcov);
7653: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7654: fprintf(ficresprobcov,"# Age");
7655: pstamp(ficresprobcor);
7656: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7657: fprintf(ficresprobcor,"# Age");
1.126 brouard 7658:
7659:
1.222 brouard 7660: for(i=1; i<=nlstate;i++)
7661: for(j=1; j<=(nlstate+ndeath);j++){
7662: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7663: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7664: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7665: }
7666: /* fprintf(ficresprob,"\n");
7667: fprintf(ficresprobcov,"\n");
7668: fprintf(ficresprobcor,"\n");
7669: */
7670: xp=vector(1,npar);
7671: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7672: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7673: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7674: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7675: first=1;
7676: fprintf(ficgp,"\n# Routine varprob");
7677: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7678: fprintf(fichtm,"\n");
7679:
1.288 brouard 7680: 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 7681: 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);
7682: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7683: and drawn. It helps understanding how is the covariance between two incidences.\
7684: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7685: 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 7686: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7687: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7688: standard deviations wide on each axis. <br>\
7689: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7690: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7691: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7692:
1.222 brouard 7693: cov[1]=1;
7694: /* tj=cptcoveff; */
1.225 brouard 7695: tj = (int) pow(2,cptcoveff);
1.222 brouard 7696: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7697: j1=0;
1.332 brouard 7698:
7699: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7700: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7701: /* 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 7702: if(tj != 1 && TKresult[nres]!= j1)
7703: continue;
7704:
7705: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7706: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7707: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7708: if (cptcovn>0) {
1.334 brouard 7709: fprintf(ficresprob, "\n#********** Variable ");
7710: fprintf(ficresprobcov, "\n#********** Variable ");
7711: fprintf(ficgp, "\n#********** Variable ");
7712: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7713: fprintf(ficresprobcor, "\n#********** Variable ");
7714:
7715: /* Including quantitative variables of the resultline to be done */
7716: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7717: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7718: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7719: /* 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 7720: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7721: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7722: 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 */
7723: 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 */
7724: 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 */
7725: 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 */
7726: 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 */
7727: fprintf(ficresprob,"fixed ");
7728: fprintf(ficresprobcov,"fixed ");
7729: fprintf(ficgp,"fixed ");
7730: fprintf(fichtmcov,"fixed ");
7731: fprintf(ficresprobcor,"fixed ");
7732: }else{
7733: fprintf(ficresprob,"varyi ");
7734: fprintf(ficresprobcov,"varyi ");
7735: fprintf(ficgp,"varyi ");
7736: fprintf(fichtmcov,"varyi ");
7737: fprintf(ficresprobcor,"varyi ");
7738: }
7739: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7740: /* For each selected (single) quantitative value */
1.337 brouard 7741: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7742: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7743: fprintf(ficresprob,"fixed ");
7744: fprintf(ficresprobcov,"fixed ");
7745: fprintf(ficgp,"fixed ");
7746: fprintf(fichtmcov,"fixed ");
7747: fprintf(ficresprobcor,"fixed ");
7748: }else{
7749: fprintf(ficresprob,"varyi ");
7750: fprintf(ficresprobcov,"varyi ");
7751: fprintf(ficgp,"varyi ");
7752: fprintf(fichtmcov,"varyi ");
7753: fprintf(ficresprobcor,"varyi ");
7754: }
7755: }else{
7756: 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 */
7757: 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 */
7758: exit(1);
7759: }
7760: } /* End loop on variable of this resultline */
7761: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7762: fprintf(ficresprob, "**********\n#\n");
7763: fprintf(ficresprobcov, "**********\n#\n");
7764: fprintf(ficgp, "**********\n#\n");
7765: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7766: fprintf(ficresprobcor, "**********\n#");
7767: if(invalidvarcomb[j1]){
7768: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7769: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7770: continue;
7771: }
7772: }
7773: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7774: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7775: gp=vector(1,(nlstate)*(nlstate+ndeath));
7776: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7777: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7778: cov[2]=age;
7779: if(nagesqr==1)
7780: cov[3]= age*age;
1.334 brouard 7781: /* New code end of combination but for each resultline */
7782: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 7783: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7784: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7785: }else{
1.334 brouard 7786: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7787: }
1.334 brouard 7788: }/* End of loop on model equation */
7789: /* Old code */
7790: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7791: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7792: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7793: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7794: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7795: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7796: /* * 1 1 1 1 1 */
7797: /* * 2 2 1 1 1 */
7798: /* * 3 1 2 1 1 */
7799: /* *\/ */
7800: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7801: /* } */
7802: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7803: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7804: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7805: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7806: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7807: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7808: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7809: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7810: /* 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]); */
7811: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7812: /* /\* exit(1); *\/ */
7813: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7814: /* } */
7815: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7816: /* } */
7817: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7818: /* if(Dummy[Tvard[k][1]]==0){ */
7819: /* if(Dummy[Tvard[k][2]]==0){ */
7820: /* 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]])]; */
7821: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7822: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7823: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7824: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7825: /* } */
7826: /* }else{ */
7827: /* if(Dummy[Tvard[k][2]]==0){ */
7828: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7829: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7830: /* }else{ */
7831: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7832: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7833: /* } */
7834: /* } */
7835: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7836: /* } */
1.326 brouard 7837: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7838: for(theta=1; theta <=npar; theta++){
7839: for(i=1; i<=npar; i++)
7840: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7841:
1.222 brouard 7842: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7843:
1.222 brouard 7844: k=0;
7845: for(i=1; i<= (nlstate); i++){
7846: for(j=1; j<=(nlstate+ndeath);j++){
7847: k=k+1;
7848: gp[k]=pmmij[i][j];
7849: }
7850: }
1.220 brouard 7851:
1.222 brouard 7852: for(i=1; i<=npar; i++)
7853: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7854:
1.222 brouard 7855: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7856: k=0;
7857: for(i=1; i<=(nlstate); i++){
7858: for(j=1; j<=(nlstate+ndeath);j++){
7859: k=k+1;
7860: gm[k]=pmmij[i][j];
7861: }
7862: }
1.220 brouard 7863:
1.222 brouard 7864: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7865: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7866: }
1.126 brouard 7867:
1.222 brouard 7868: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7869: for(theta=1; theta <=npar; theta++)
7870: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7871:
1.222 brouard 7872: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7873: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7874:
1.222 brouard 7875: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7876:
1.222 brouard 7877: k=0;
7878: for(i=1; i<=(nlstate); i++){
7879: for(j=1; j<=(nlstate+ndeath);j++){
7880: k=k+1;
7881: mu[k][(int) age]=pmmij[i][j];
7882: }
7883: }
7884: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7885: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7886: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7887:
1.222 brouard 7888: /*printf("\n%d ",(int)age);
7889: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7890: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7891: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7892: }*/
1.220 brouard 7893:
1.222 brouard 7894: fprintf(ficresprob,"\n%d ",(int)age);
7895: fprintf(ficresprobcov,"\n%d ",(int)age);
7896: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7897:
1.222 brouard 7898: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7899: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7900: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7901: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7902: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7903: }
7904: i=0;
7905: for (k=1; k<=(nlstate);k++){
7906: for (l=1; l<=(nlstate+ndeath);l++){
7907: i++;
7908: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7909: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7910: for (j=1; j<=i;j++){
7911: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7912: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7913: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7914: }
7915: }
7916: }/* end of loop for state */
7917: } /* end of loop for age */
7918: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7919: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7920: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7921: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7922:
7923: /* Confidence intervalle of pij */
7924: /*
7925: fprintf(ficgp,"\nunset parametric;unset label");
7926: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7927: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7928: 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);
7929: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7930: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7931: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7932: */
7933:
7934: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7935: first1=1;first2=2;
7936: for (k2=1; k2<=(nlstate);k2++){
7937: for (l2=1; l2<=(nlstate+ndeath);l2++){
7938: if(l2==k2) continue;
7939: j=(k2-1)*(nlstate+ndeath)+l2;
7940: for (k1=1; k1<=(nlstate);k1++){
7941: for (l1=1; l1<=(nlstate+ndeath);l1++){
7942: if(l1==k1) continue;
7943: i=(k1-1)*(nlstate+ndeath)+l1;
7944: if(i<=j) continue;
7945: for (age=bage; age<=fage; age ++){
7946: if ((int)age %5==0){
7947: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7948: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7949: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7950: mu1=mu[i][(int) age]/stepm*YEARM ;
7951: mu2=mu[j][(int) age]/stepm*YEARM;
7952: c12=cv12/sqrt(v1*v2);
7953: /* Computing eigen value of matrix of covariance */
7954: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7955: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7956: if ((lc2 <0) || (lc1 <0) ){
7957: if(first2==1){
7958: first1=0;
7959: 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);
7960: }
7961: 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);
7962: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7963: /* lc2=fabs(lc2); */
7964: }
1.220 brouard 7965:
1.222 brouard 7966: /* Eigen vectors */
1.280 brouard 7967: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7968: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7969: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7970: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7971: }else
7972: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7973: /*v21=sqrt(1.-v11*v11); *//* error */
7974: v21=(lc1-v1)/cv12*v11;
7975: v12=-v21;
7976: v22=v11;
7977: tnalp=v21/v11;
7978: if(first1==1){
7979: first1=0;
7980: 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);
7981: }
7982: 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);
7983: /*printf(fignu*/
7984: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7985: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7986: if(first==1){
7987: first=0;
7988: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7989: fprintf(ficgp,"\nset parametric;unset label");
7990: 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);
7991: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7992: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7993: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7994: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7995: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7996: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7997: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7998: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7999: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8000: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
8001: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
8002: 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 8003: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
8004: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 8005: }else{
8006: first=0;
8007: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
8008: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
8009: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
8010: 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 8011: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
8012: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 8013: }/* if first */
8014: } /* age mod 5 */
8015: } /* end loop age */
8016: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8017: first=1;
8018: } /*l12 */
8019: } /* k12 */
8020: } /*l1 */
8021: }/* k1 */
1.332 brouard 8022: } /* loop on combination of covariates j1 */
1.326 brouard 8023: } /* loop on nres */
1.222 brouard 8024: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
8025: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
8026: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
8027: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
8028: free_vector(xp,1,npar);
8029: fclose(ficresprob);
8030: fclose(ficresprobcov);
8031: fclose(ficresprobcor);
8032: fflush(ficgp);
8033: fflush(fichtmcov);
8034: }
1.126 brouard 8035:
8036:
8037: /******************* Printing html file ***********/
1.201 brouard 8038: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8039: int lastpass, int stepm, int weightopt, char model[],\
8040: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 8041: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
8042: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
8043: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 8044: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 8045: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8046: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8047: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8048: </ul>");
1.319 brouard 8049: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8050: /* </ul>", model); */
1.214 brouard 8051: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8052: 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",
8053: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8054: 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 8055: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8056: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8057: fprintf(fichtm,"\
8058: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8059: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8060: fprintf(fichtm,"\
1.217 brouard 8061: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8062: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8063: fprintf(fichtm,"\
1.288 brouard 8064: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8065: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8066: fprintf(fichtm,"\
1.288 brouard 8067: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8068: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8069: fprintf(fichtm,"\
1.211 brouard 8070: - (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 8071: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8072: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8073: if(prevfcast==1){
8074: fprintf(fichtm,"\
8075: - Prevalence projections by age and states: \
1.201 brouard 8076: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8077: }
1.126 brouard 8078:
8079:
1.225 brouard 8080: m=pow(2,cptcoveff);
1.222 brouard 8081: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8082:
1.317 brouard 8083: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8084:
8085: jj1=0;
8086:
8087: fprintf(fichtm," \n<ul>");
1.337 brouard 8088: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8089: /* k1=nres; */
1.338 brouard 8090: k1=TKresult[nres];
8091: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8092: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8093: /* if(m != 1 && TKresult[nres]!= k1) */
8094: /* continue; */
1.264 brouard 8095: jj1++;
8096: if (cptcovn > 0) {
8097: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8098: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8099: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8100: }
1.337 brouard 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: fprintf(fichtm,"\">");
8108:
8109: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8110: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8111: for (cpt=1; cpt<=cptcovs;cpt++){
8112: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8113: }
1.337 brouard 8114: /* fprintf(fichtm,"************ Results for covariates"); */
8115: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8116: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8117: /* } */
8118: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8119: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8120: /* } */
1.264 brouard 8121: if(invalidvarcomb[k1]){
8122: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8123: continue;
8124: }
8125: fprintf(fichtm,"</a></li>");
8126: } /* cptcovn >0 */
8127: }
1.317 brouard 8128: fprintf(fichtm," \n</ul>");
1.264 brouard 8129:
1.222 brouard 8130: jj1=0;
1.237 brouard 8131:
1.337 brouard 8132: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8133: /* k1=nres; */
1.338 brouard 8134: k1=TKresult[nres];
8135: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8136: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8137: /* if(m != 1 && TKresult[nres]!= k1) */
8138: /* continue; */
1.220 brouard 8139:
1.222 brouard 8140: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8141: jj1++;
8142: if (cptcovn > 0) {
1.264 brouard 8143: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8144: for (cpt=1; cpt<=cptcovs;cpt++){
8145: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8146: }
1.337 brouard 8147: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8148: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8149: /* } */
1.264 brouard 8150: fprintf(fichtm,"\"</a>");
8151:
1.222 brouard 8152: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8153: for (cpt=1; cpt<=cptcovs;cpt++){
8154: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8155: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8156: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8157: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8158: }
1.230 brouard 8159: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8160: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8161: if(invalidvarcomb[k1]){
8162: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8163: printf("\nCombination (%d) ignored because no cases \n",k1);
8164: continue;
8165: }
8166: }
8167: /* aij, bij */
1.259 brouard 8168: 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 8169: <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 8170: /* Pij */
1.241 brouard 8171: 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> \
8172: <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 8173: /* Quasi-incidences */
8174: 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 8175: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8176: 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 8177: 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> \
8178: <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 8179: /* Survival functions (period) in state j */
8180: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8181: 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);
8182: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8183: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8184: }
8185: /* State specific survival functions (period) */
8186: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8187: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8188: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8189: <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);
8190: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8191: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8192: }
1.288 brouard 8193: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8194: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8195: 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 8196: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8197: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8198: }
1.296 brouard 8199: if(prevbcast==1){
1.288 brouard 8200: /* Backward prevalence in each health state */
1.222 brouard 8201: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8202: 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);
8203: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8204: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8205: }
1.217 brouard 8206: }
1.222 brouard 8207: if(prevfcast==1){
1.288 brouard 8208: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8209: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8210: 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);
8211: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8212: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8213: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8214: }
8215: }
1.296 brouard 8216: if(prevbcast==1){
1.268 brouard 8217: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8218: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8219: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8220: 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 \
8221: 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 8222: 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);
8223: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8224: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8225: }
8226: }
1.220 brouard 8227:
1.222 brouard 8228: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8229: 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);
8230: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8231: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8232: }
8233: /* } /\* end i1 *\/ */
1.337 brouard 8234: }/* End k1=nres */
1.222 brouard 8235: fprintf(fichtm,"</ul>");
1.126 brouard 8236:
1.222 brouard 8237: fprintf(fichtm,"\
1.126 brouard 8238: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8239: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8240: - 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 8241: But because parameters are usually highly correlated (a higher incidence of disability \
8242: and a higher incidence of recovery can give very close observed transition) it might \
8243: be very useful to look not only at linear confidence intervals estimated from the \
8244: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8245: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8246: covariance matrix of the one-step probabilities. \
8247: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8248:
1.222 brouard 8249: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8250: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8251: fprintf(fichtm,"\
1.126 brouard 8252: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8253: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8254:
1.222 brouard 8255: fprintf(fichtm,"\
1.126 brouard 8256: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8257: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8258: fprintf(fichtm,"\
1.126 brouard 8259: - 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): \
8260: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8261: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8262: fprintf(fichtm,"\
1.126 brouard 8263: - (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): \
8264: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8265: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8266: fprintf(fichtm,"\
1.288 brouard 8267: - 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 8268: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8269: fprintf(fichtm,"\
1.128 brouard 8270: - 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 8271: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8272: fprintf(fichtm,"\
1.288 brouard 8273: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8274: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8275:
8276: /* if(popforecast==1) fprintf(fichtm,"\n */
8277: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8278: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8279: /* <br>",fileres,fileres,fileres,fileres); */
8280: /* else */
1.338 brouard 8281: /* 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 8282: fflush(fichtm);
1.126 brouard 8283:
1.225 brouard 8284: m=pow(2,cptcoveff);
1.222 brouard 8285: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8286:
1.317 brouard 8287: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8288:
8289: jj1=0;
8290:
8291: fprintf(fichtm," \n<ul>");
1.337 brouard 8292: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8293: /* k1=nres; */
1.338 brouard 8294: k1=TKresult[nres];
1.337 brouard 8295: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8296: /* if(m != 1 && TKresult[nres]!= k1) */
8297: /* continue; */
1.317 brouard 8298: jj1++;
8299: if (cptcovn > 0) {
8300: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8301: for (cpt=1; cpt<=cptcovs;cpt++){
8302: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8303: }
8304: fprintf(fichtm,"\">");
8305:
8306: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8307: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8308: for (cpt=1; cpt<=cptcovs;cpt++){
8309: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8310: }
8311: if(invalidvarcomb[k1]){
8312: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8313: continue;
8314: }
8315: fprintf(fichtm,"</a></li>");
8316: } /* cptcovn >0 */
1.337 brouard 8317: } /* End nres */
1.317 brouard 8318: fprintf(fichtm," \n</ul>");
8319:
1.222 brouard 8320: jj1=0;
1.237 brouard 8321:
1.241 brouard 8322: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8323: /* k1=nres; */
1.338 brouard 8324: k1=TKresult[nres];
8325: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8326: /* for(k1=1; k1<=m;k1++){ */
8327: /* if(m != 1 && TKresult[nres]!= k1) */
8328: /* continue; */
1.222 brouard 8329: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8330: jj1++;
1.126 brouard 8331: if (cptcovn > 0) {
1.317 brouard 8332: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8333: for (cpt=1; cpt<=cptcovs;cpt++){
8334: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8335: }
8336: fprintf(fichtm,"\"</a>");
8337:
1.126 brouard 8338: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8339: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8340: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8341: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8342: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8343: }
1.237 brouard 8344:
1.338 brouard 8345: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8346:
1.222 brouard 8347: if(invalidvarcomb[k1]){
8348: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8349: continue;
8350: }
1.337 brouard 8351: } /* If cptcovn >0 */
1.126 brouard 8352: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8353: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8354: 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);
8355: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8356: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8357: }
8358: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8359: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8360: true period expectancies (those weighted with period prevalences are also\
8361: drawn in addition to the population based expectancies computed using\
1.314 brouard 8362: 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);
8363: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8364: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8365: /* } /\* end i1 *\/ */
1.241 brouard 8366: }/* End nres */
1.222 brouard 8367: fprintf(fichtm,"</ul>");
8368: fflush(fichtm);
1.126 brouard 8369: }
8370:
8371: /******************* Gnuplot file **************/
1.296 brouard 8372: 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 8373:
1.354 brouard 8374: char dirfileres[256],optfileres[256];
8375: char gplotcondition[256], gplotlabel[256];
1.343 brouard 8376: 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 8377: int lv=0, vlv=0, kl=0;
1.130 brouard 8378: int ng=0;
1.201 brouard 8379: int vpopbased;
1.223 brouard 8380: int ioffset; /* variable offset for columns */
1.270 brouard 8381: int iyearc=1; /* variable column for year of projection */
8382: int iagec=1; /* variable column for age of projection */
1.235 brouard 8383: int nres=0; /* Index of resultline */
1.266 brouard 8384: int istart=1; /* For starting graphs in projections */
1.219 brouard 8385:
1.126 brouard 8386: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8387: /* printf("Problem with file %s",optionfilegnuplot); */
8388: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8389: /* } */
8390:
8391: /*#ifdef windows */
8392: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8393: /*#endif */
1.225 brouard 8394: m=pow(2,cptcoveff);
1.126 brouard 8395:
1.274 brouard 8396: /* diagram of the model */
8397: fprintf(ficgp,"\n#Diagram of the model \n");
8398: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8399: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8400: 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);
8401:
1.343 brouard 8402: 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 8403: fprintf(ficgp,"\n#show arrow\nunset label\n");
8404: 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);
8405: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8406: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8407: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8408: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8409:
1.202 brouard 8410: /* Contribution to likelihood */
8411: /* Plot the probability implied in the likelihood */
1.223 brouard 8412: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8413: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8414: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8415: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8416: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8417: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8418: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8419: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8420: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8421: 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));
8422: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8423: 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));
8424: for (i=1; i<= nlstate ; i ++) {
8425: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8426: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8427: 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);
8428: for (j=2; j<= nlstate+ndeath ; j ++) {
8429: 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);
8430: }
8431: fprintf(ficgp,";\nset out; unset ylabel;\n");
8432: }
8433: /* 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 */
8434: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8435: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8436: fprintf(ficgp,"\nset out;unset log\n");
8437: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8438:
1.343 brouard 8439: /* Plot the probability implied in the likelihood by covariate value */
8440: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8441: /* if(debugILK==1){ */
8442: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8443: kvar=Tvar[TvarFind[kf]]; /* variable name */
8444: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 8445: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
1.355 ! brouard 8446: /* k=19+nlstate+kf;/\*offset because there are 19 columns in the ILK_ file *\/ */
! 8447: k=16+nlstate+kf;/*offset because there are 19 columns in the ILK_ file, first cov Vn on col 21 with 4 living states */
1.343 brouard 8448: for (i=1; i<= nlstate ; i ++) {
8449: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8450: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8451: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8452: 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);
8453: for (j=2; j<= nlstate+ndeath ; j ++) {
8454: 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);
8455: }
8456: }else{
8457: 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);
8458: for (j=2; j<= nlstate+ndeath ; j ++) {
8459: 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);
8460: }
1.343 brouard 8461: }
8462: fprintf(ficgp,";\nset out; unset ylabel;\n");
8463: }
8464: } /* End of each covariate dummy */
8465: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8466: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8467: * kmodel = 1 2 3 4 5 6 7 8 9
8468: * varying 1 2 3 4 5
8469: * ncovv 1 2 3 4 5 6 7 8
8470: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8471: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8472: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8473: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8474: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8475: */
8476: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8477: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8478: /* 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]); */
8479: if(ipos!=iposold){ /* Not a product or first of a product */
8480: /* printf(" %d",ipos); */
8481: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8482: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8483: kk++; /* Position of the ncovv column in ILK_ */
8484: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8485: 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) */
8486: for (i=1; i<= nlstate ; i ++) {
8487: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8488: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8489:
1.348 brouard 8490: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8491: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8492: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8493: 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);
8494: for (j=2; j<= nlstate+ndeath ; j ++) {
8495: 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);
8496: }
8497: }else{
8498: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8499: 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);
8500: for (j=2; j<= nlstate+ndeath ; j ++) {
8501: 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);
8502: }
8503: }
8504: fprintf(ficgp,";\nset out; unset ylabel;\n");
8505: }
8506: }/* End if dummy varying */
8507: }else{ /*Product */
8508: /* printf("*"); */
8509: /* fprintf(ficresilk,"*"); */
8510: }
8511: iposold=ipos;
8512: } /* For each time varying covariate */
8513: /* } /\* debugILK==1 *\/ */
8514: /* 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 */
8515: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8516: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8517: fprintf(ficgp,"\nset out;unset log\n");
8518: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8519:
8520:
8521:
1.126 brouard 8522: strcpy(dirfileres,optionfilefiname);
8523: strcpy(optfileres,"vpl");
1.223 brouard 8524: /* 1eme*/
1.238 brouard 8525: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8526: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8527: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8528: k1=TKresult[nres];
1.338 brouard 8529: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8530: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8531: /* if(m != 1 && TKresult[nres]!= k1) */
8532: /* continue; */
1.238 brouard 8533: /* We are interested in selected combination by the resultline */
1.246 brouard 8534: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8535: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8536: strcpy(gplotlabel,"(");
1.337 brouard 8537: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8538: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8539: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8540:
8541: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8542: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8543: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8544: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8545: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8546: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8547: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8548: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8549: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8550: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8551: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8552: /* } */
8553: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8554: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8555: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8556: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8557: }
8558: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8559: /* printf("\n#\n"); */
1.238 brouard 8560: fprintf(ficgp,"\n#\n");
8561: if(invalidvarcomb[k1]){
1.260 brouard 8562: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8563: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8564: continue;
8565: }
1.235 brouard 8566:
1.241 brouard 8567: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8568: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8569: /* 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 8570: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8571: 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);
8572: /* 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); */
8573: /* k1-1 error should be nres-1*/
1.238 brouard 8574: for (i=1; i<= nlstate ; i ++) {
8575: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8576: else fprintf(ficgp," %%*lf (%%*lf)");
8577: }
1.288 brouard 8578: 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 8579: for (i=1; i<= nlstate ; i ++) {
8580: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8581: else fprintf(ficgp," %%*lf (%%*lf)");
8582: }
1.260 brouard 8583: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8584: for (i=1; i<= nlstate ; i ++) {
8585: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8586: else fprintf(ficgp," %%*lf (%%*lf)");
8587: }
1.265 brouard 8588: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8589:
8590: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8591: if(cptcoveff ==0){
1.271 brouard 8592: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8593: }else{
8594: kl=0;
8595: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8596: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8597: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8598: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8599: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8600: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8601: vlv= nbcode[Tvaraff[k]][lv];
8602: kl++;
8603: /* 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 *\/ */
8604: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8605: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8606: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8607: if(k==cptcoveff){
8608: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8609: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8610: }else{
8611: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8612: kl++;
8613: }
8614: } /* end covariate */
8615: } /* end if no covariate */
8616:
1.296 brouard 8617: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8618: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8619: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8620: if(cptcoveff ==0){
1.245 brouard 8621: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8622: }else{
8623: kl=0;
8624: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8625: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8626: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8627: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8628: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8629: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8630: /* vlv= nbcode[Tvaraff[k]][lv]; */
8631: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8632: kl++;
1.238 brouard 8633: /* 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 *\/ */
8634: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8635: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8636: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8637: if(k==cptcoveff){
1.245 brouard 8638: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8639: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8640: }else{
1.332 brouard 8641: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8642: kl++;
8643: }
8644: } /* end covariate */
8645: } /* end if no covariate */
1.296 brouard 8646: if(prevbcast == 1){
1.268 brouard 8647: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8648: /* k1-1 error should be nres-1*/
8649: for (i=1; i<= nlstate ; i ++) {
8650: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8651: else fprintf(ficgp," %%*lf (%%*lf)");
8652: }
1.271 brouard 8653: 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 8654: for (i=1; i<= nlstate ; i ++) {
8655: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8656: else fprintf(ficgp," %%*lf (%%*lf)");
8657: }
1.276 brouard 8658: 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 8659: for (i=1; i<= nlstate ; i ++) {
8660: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8661: else fprintf(ficgp," %%*lf (%%*lf)");
8662: }
1.274 brouard 8663: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8664: } /* end if backprojcast */
1.296 brouard 8665: } /* end if prevbcast */
1.276 brouard 8666: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8667: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8668: } /* nres */
1.337 brouard 8669: /* } /\* k1 *\/ */
1.201 brouard 8670: } /* cpt */
1.235 brouard 8671:
8672:
1.126 brouard 8673: /*2 eme*/
1.337 brouard 8674: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8675: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8676: k1=TKresult[nres];
1.338 brouard 8677: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8678: /* if(m != 1 && TKresult[nres]!= k1) */
8679: /* continue; */
1.238 brouard 8680: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8681: strcpy(gplotlabel,"(");
1.337 brouard 8682: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8683: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8684: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8685: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8686: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8687: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8688: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8689: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8690: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8691: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8692: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8693: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8694: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8695: /* } */
8696: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8697: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8698: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8699: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8700: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8701: }
1.264 brouard 8702: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8703: fprintf(ficgp,"\n#\n");
1.223 brouard 8704: if(invalidvarcomb[k1]){
8705: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8706: continue;
8707: }
1.219 brouard 8708:
1.241 brouard 8709: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8710: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8711: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8712: if(vpopbased==0){
1.238 brouard 8713: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8714: }else
1.238 brouard 8715: fprintf(ficgp,"\nreplot ");
8716: for (i=1; i<= nlstate+1 ; i ++) {
8717: k=2*i;
1.261 brouard 8718: 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 8719: for (j=1; j<= nlstate+1 ; j ++) {
8720: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8721: else fprintf(ficgp," %%*lf (%%*lf)");
8722: }
8723: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8724: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8725: 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 8726: for (j=1; j<= nlstate+1 ; j ++) {
8727: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8728: else fprintf(ficgp," %%*lf (%%*lf)");
8729: }
8730: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8731: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4+$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
1.238 brouard 8732: for (j=1; j<= nlstate+1 ; j ++) {
8733: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8734: else fprintf(ficgp," %%*lf (%%*lf)");
8735: }
8736: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8737: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8738: } /* state */
8739: } /* vpopbased */
1.264 brouard 8740: 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 8741: } /* end nres */
1.337 brouard 8742: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8743:
8744:
8745: /*3eme*/
1.337 brouard 8746: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8747: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8748: k1=TKresult[nres];
1.338 brouard 8749: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8750: /* if(m != 1 && TKresult[nres]!= k1) */
8751: /* continue; */
1.238 brouard 8752:
1.332 brouard 8753: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8754: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8755: strcpy(gplotlabel,"(");
1.337 brouard 8756: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8757: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8758: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8759: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8760: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8761: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8762: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8763: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8764: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8765: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8766: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8767: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8768: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8769: /* } */
8770: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8771: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8772: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8773: }
1.264 brouard 8774: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8775: fprintf(ficgp,"\n#\n");
8776: if(invalidvarcomb[k1]){
8777: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8778: continue;
8779: }
8780:
8781: /* k=2+nlstate*(2*cpt-2); */
8782: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8783: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8784: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8785: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8786: 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 8787: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8788: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8789: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8790: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8791: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8792: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8793:
1.238 brouard 8794: */
8795: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8796: 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 8797: /* 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 8798:
1.238 brouard 8799: }
1.261 brouard 8800: 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 8801: }
1.264 brouard 8802: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8803: } /* end nres */
1.337 brouard 8804: /* } /\* end kl 3eme *\/ */
1.126 brouard 8805:
1.223 brouard 8806: /* 4eme */
1.201 brouard 8807: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8808: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8809: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8810: k1=TKresult[nres];
1.338 brouard 8811: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8812: /* if(m != 1 && TKresult[nres]!= k1) */
8813: /* continue; */
1.238 brouard 8814: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8815: strcpy(gplotlabel,"(");
1.337 brouard 8816: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8817: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8818: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8819: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8820: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8821: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8822: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8823: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8824: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8825: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8826: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8827: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8828: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8829: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8830: /* } */
8831: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8832: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8833: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8834: }
1.264 brouard 8835: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8836: fprintf(ficgp,"\n#\n");
8837: if(invalidvarcomb[k1]){
8838: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8839: continue;
1.223 brouard 8840: }
1.238 brouard 8841:
1.241 brouard 8842: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8843: 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 8844: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8845: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8846: k=3;
8847: for (i=1; i<= nlstate ; i ++){
8848: if(i==1){
8849: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8850: }else{
8851: fprintf(ficgp,", '' ");
8852: }
8853: l=(nlstate+ndeath)*(i-1)+1;
8854: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8855: for (j=2; j<= nlstate+ndeath ; j ++)
8856: fprintf(ficgp,"+$%d",k+l+j-1);
8857: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8858: } /* nlstate */
1.264 brouard 8859: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8860: } /* end cpt state*/
8861: } /* end nres */
1.337 brouard 8862: /* } /\* end covariate k1 *\/ */
1.238 brouard 8863:
1.220 brouard 8864: /* 5eme */
1.201 brouard 8865: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8866: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8867: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8868: k1=TKresult[nres];
1.338 brouard 8869: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8870: /* if(m != 1 && TKresult[nres]!= k1) */
8871: /* continue; */
1.238 brouard 8872: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8873: strcpy(gplotlabel,"(");
1.238 brouard 8874: 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 8875: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8876: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8877: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8878: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8879: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8880: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8881: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8882: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8883: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8884: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8885: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8886: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8887: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8888: /* } */
8889: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8890: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8891: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8892: }
1.264 brouard 8893: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8894: fprintf(ficgp,"\n#\n");
8895: if(invalidvarcomb[k1]){
8896: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8897: continue;
8898: }
1.227 brouard 8899:
1.241 brouard 8900: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8901: 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 8902: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8903: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8904: k=3;
8905: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8906: if(j==1)
8907: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8908: else
8909: fprintf(ficgp,", '' ");
8910: l=(nlstate+ndeath)*(cpt-1) +j;
8911: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8912: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8913: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8914: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8915: } /* nlstate */
8916: fprintf(ficgp,", '' ");
8917: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8918: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8919: l=(nlstate+ndeath)*(cpt-1) +j;
8920: if(j < nlstate)
8921: fprintf(ficgp,"$%d +",k+l);
8922: else
8923: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8924: }
1.264 brouard 8925: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8926: } /* end cpt state*/
1.337 brouard 8927: /* } /\* end covariate *\/ */
1.238 brouard 8928: } /* end nres */
1.227 brouard 8929:
1.220 brouard 8930: /* 6eme */
1.202 brouard 8931: /* CV preval stable (period) for each covariate */
1.337 brouard 8932: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8933: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8934: k1=TKresult[nres];
1.338 brouard 8935: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8936: /* if(m != 1 && TKresult[nres]!= k1) */
8937: /* continue; */
1.255 brouard 8938: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8939: strcpy(gplotlabel,"(");
1.288 brouard 8940: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8941: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8942: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8943: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8944: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8945: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8946: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8947: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8948: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8949: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8950: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8951: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8952: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8953: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8954: /* } */
8955: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8956: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8957: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8958: }
1.264 brouard 8959: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8960: fprintf(ficgp,"\n#\n");
1.223 brouard 8961: if(invalidvarcomb[k1]){
1.227 brouard 8962: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8963: continue;
1.223 brouard 8964: }
1.227 brouard 8965:
1.241 brouard 8966: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8967: 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 8968: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8969: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8970: k=3; /* Offset */
1.255 brouard 8971: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8972: if(i==1)
8973: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8974: else
8975: fprintf(ficgp,", '' ");
1.255 brouard 8976: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8977: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8978: for (j=2; j<= nlstate ; j ++)
8979: fprintf(ficgp,"+$%d",k+l+j-1);
8980: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8981: } /* nlstate */
1.264 brouard 8982: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8983: } /* end cpt state*/
8984: } /* end covariate */
1.227 brouard 8985:
8986:
1.220 brouard 8987: /* 7eme */
1.296 brouard 8988: if(prevbcast == 1){
1.288 brouard 8989: /* CV backward prevalence for each covariate */
1.337 brouard 8990: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8991: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8992: k1=TKresult[nres];
1.338 brouard 8993: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8994: /* if(m != 1 && TKresult[nres]!= k1) */
8995: /* continue; */
1.268 brouard 8996: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8997: strcpy(gplotlabel,"(");
1.288 brouard 8998: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8999: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9000: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9001: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9002: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
9003: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
9004: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9005: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9006: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9007: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9008: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9009: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9010: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9011: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9012: /* } */
9013: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9014: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9015: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9016: }
1.264 brouard 9017: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9018: fprintf(ficgp,"\n#\n");
9019: if(invalidvarcomb[k1]){
9020: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9021: continue;
9022: }
9023:
1.241 brouard 9024: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 9025: 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 9026: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 9027: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 9028: k=3; /* Offset */
1.268 brouard 9029: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 9030: if(i==1)
9031: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
9032: else
9033: fprintf(ficgp,", '' ");
9034: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 9035: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 9036: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
9037: /* 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 9038: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 9039: /* for (j=2; j<= nlstate ; j ++) */
9040: /* fprintf(ficgp,"+$%d",k+l+j-1); */
9041: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 9042: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 9043: } /* nlstate */
1.264 brouard 9044: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 9045: } /* end cpt state*/
9046: } /* end covariate */
1.296 brouard 9047: } /* End if prevbcast */
1.218 brouard 9048:
1.223 brouard 9049: /* 8eme */
1.218 brouard 9050: if(prevfcast==1){
1.288 brouard 9051: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9052:
1.337 brouard 9053: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9054: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9055: k1=TKresult[nres];
1.338 brouard 9056: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9057: /* if(m != 1 && TKresult[nres]!= k1) */
9058: /* continue; */
1.211 brouard 9059: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9060: strcpy(gplotlabel,"(");
1.288 brouard 9061: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9062: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9063: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9064: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9065: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9066: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9067: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9068: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9069: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9070: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9071: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9072: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9073: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9074: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9075: /* } */
9076: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9077: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9078: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9079: }
1.264 brouard 9080: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9081: fprintf(ficgp,"\n#\n");
9082: if(invalidvarcomb[k1]){
9083: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9084: continue;
9085: }
9086:
9087: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9088: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9089: 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 9090: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9091: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9092:
9093: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9094: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9095: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9096: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9097: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9098: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9099: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9100: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9101: if(i==istart){
1.227 brouard 9102: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9103: }else{
9104: fprintf(ficgp,",\\\n '' ");
9105: }
9106: if(cptcoveff ==0){ /* No covariate */
9107: ioffset=2; /* Age is in 2 */
9108: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9109: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9110: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9111: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9112: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9113: if(i==nlstate+1){
1.270 brouard 9114: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9115: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9116: fprintf(ficgp,",\\\n '' ");
9117: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9118: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9119: offyear, \
1.268 brouard 9120: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9121: }else
1.227 brouard 9122: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9123: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9124: }else{ /* more than 2 covariates */
1.270 brouard 9125: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9126: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9127: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9128: iyearc=ioffset-1;
9129: iagec=ioffset;
1.227 brouard 9130: fprintf(ficgp," u %d:(",ioffset);
9131: kl=0;
9132: strcpy(gplotcondition,"(");
1.351 brouard 9133: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 9134: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 9135: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9136: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9137: lv=Tvresult[nres][k];
9138: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 9139: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9140: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9141: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9142: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 9143: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 9144: kl++;
1.351 brouard 9145: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9146: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 9147: kl++;
1.351 brouard 9148: if(k <cptcovs && cptcovs>1)
1.227 brouard 9149: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9150: }
9151: strcpy(gplotcondition+strlen(gplotcondition),")");
9152: /* 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 *\/ */
9153: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9154: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9155: /* '' 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*/
9156: if(i==nlstate+1){
1.270 brouard 9157: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9158: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9159: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9160: fprintf(ficgp," u %d:(",iagec);
9161: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9162: iyearc, iagec, offyear, \
9163: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9164: /* '' 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 9165: }else{
9166: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9167: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9168: }
9169: } /* end if covariate */
9170: } /* nlstate */
1.264 brouard 9171: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9172: } /* end cpt state*/
9173: } /* end covariate */
9174: } /* End if prevfcast */
1.227 brouard 9175:
1.296 brouard 9176: if(prevbcast==1){
1.268 brouard 9177: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9178:
1.337 brouard 9179: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9180: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9181: k1=TKresult[nres];
1.338 brouard 9182: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9183: /* if(m != 1 && TKresult[nres]!= k1) */
9184: /* continue; */
1.268 brouard 9185: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9186: strcpy(gplotlabel,"(");
9187: 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 9188: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9189: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9190: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9191: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9192: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9193: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9194: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9195: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9196: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9197: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9198: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9199: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9200: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9201: /* } */
9202: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9203: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9204: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9205: }
9206: strcpy(gplotlabel+strlen(gplotlabel),")");
9207: fprintf(ficgp,"\n#\n");
9208: if(invalidvarcomb[k1]){
9209: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9210: continue;
9211: }
9212:
9213: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9214: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9215: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9216: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9217: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9218:
9219: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9220: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9221: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9222: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9223: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9224: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9225: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9226: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9227: if(i==istart){
9228: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9229: }else{
9230: fprintf(ficgp,",\\\n '' ");
9231: }
1.351 brouard 9232: /* if(cptcoveff ==0){ /\* No covariate *\/ */
9233: if(cptcovs ==0){ /* No covariate */
1.268 brouard 9234: ioffset=2; /* Age is in 2 */
9235: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9236: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9237: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9238: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9239: fprintf(ficgp," u %d:(", ioffset);
9240: if(i==nlstate+1){
1.270 brouard 9241: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9242: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9243: fprintf(ficgp,",\\\n '' ");
9244: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9245: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9246: offbyear, \
9247: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9248: }else
9249: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9250: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9251: }else{ /* more than 2 covariates */
1.270 brouard 9252: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9253: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9254: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9255: iyearc=ioffset-1;
9256: iagec=ioffset;
1.268 brouard 9257: fprintf(ficgp," u %d:(",ioffset);
9258: kl=0;
9259: strcpy(gplotcondition,"(");
1.337 brouard 9260: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9261: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9262: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9263: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9264: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9265: lv=Tvresult[nres][k];
9266: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9267: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9268: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9269: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9270: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9271: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9272: kl++;
9273: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9274: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9275: kl++;
1.338 brouard 9276: if(k <cptcovs && cptcovs>1)
1.337 brouard 9277: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9278: }
1.268 brouard 9279: }
9280: strcpy(gplotcondition+strlen(gplotcondition),")");
9281: /* 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 *\/ */
9282: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9283: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9284: /* '' 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*/
9285: if(i==nlstate+1){
1.270 brouard 9286: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9287: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9288: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9289: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9290: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9291: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9292: iyearc,iagec,offbyear, \
9293: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9294: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9295: }else{
9296: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9297: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9298: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9299: }
9300: } /* end if covariate */
9301: } /* nlstate */
9302: fprintf(ficgp,"\nset out; unset label;\n");
9303: } /* end cpt state*/
9304: } /* end covariate */
1.296 brouard 9305: } /* End if prevbcast */
1.268 brouard 9306:
1.227 brouard 9307:
1.238 brouard 9308: /* 9eme writing MLE parameters */
9309: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9310: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9311: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9312: for(k=1; k <=(nlstate+ndeath); k++){
9313: if (k != i) {
1.227 brouard 9314: fprintf(ficgp,"# current state %d\n",k);
9315: for(j=1; j <=ncovmodel; j++){
9316: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9317: jk++;
9318: }
9319: fprintf(ficgp,"\n");
1.126 brouard 9320: }
9321: }
1.223 brouard 9322: }
1.187 brouard 9323: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9324:
1.145 brouard 9325: /*goto avoid;*/
1.238 brouard 9326: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9327: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9328: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9329: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9330: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9331: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9332: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9333: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9334: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9335: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9336: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9337: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9338: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9339: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9340: fprintf(ficgp,"#\n");
1.223 brouard 9341: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9342: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9343: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9344: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 9345: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
9346: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 9347: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9348: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9349: /* k1=nres; */
1.338 brouard 9350: k1=TKresult[nres];
9351: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9352: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9353: strcpy(gplotlabel,"(");
1.276 brouard 9354: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9355: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9356: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9357: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9358: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9359: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9360: }
9361: /* if(m != 1 && TKresult[nres]!= k1) */
9362: /* continue; */
9363: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9364: /* strcpy(gplotlabel,"("); */
9365: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9366: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9367: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9368: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9369: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9370: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9371: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9372: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9373: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9374: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9375: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9376: /* } */
9377: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9378: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9379: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9380: /* } */
1.264 brouard 9381: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9382: fprintf(ficgp,"\n#\n");
1.264 brouard 9383: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9384: fprintf(ficgp,"\nset key outside ");
9385: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9386: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9387: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9388: if (ng==1){
9389: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9390: fprintf(ficgp,"\nunset log y");
9391: }else if (ng==2){
9392: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9393: fprintf(ficgp,"\nset log y");
9394: }else if (ng==3){
9395: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9396: fprintf(ficgp,"\nset log y");
9397: }else
9398: fprintf(ficgp,"\nunset title ");
9399: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9400: i=1;
9401: for(k2=1; k2<=nlstate; k2++) {
9402: k3=i;
9403: for(k=1; k<=(nlstate+ndeath); k++) {
9404: if (k != k2){
9405: switch( ng) {
9406: case 1:
9407: if(nagesqr==0)
9408: fprintf(ficgp," p%d+p%d*x",i,i+1);
9409: else /* nagesqr =1 */
9410: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9411: break;
9412: case 2: /* ng=2 */
9413: if(nagesqr==0)
9414: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9415: else /* nagesqr =1 */
9416: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9417: break;
9418: case 3:
9419: if(nagesqr==0)
9420: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9421: else /* nagesqr =1 */
9422: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9423: break;
9424: }
9425: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9426: ijp=1; /* product no age */
9427: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9428: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9429: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9430: switch(Typevar[j]){
9431: case 1:
9432: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9433: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9434: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9435: if(DummyV[j]==0){/* Bug valgrind */
9436: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9437: }else{ /* quantitative */
9438: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9439: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9440: }
9441: ij++;
1.268 brouard 9442: }
1.237 brouard 9443: }
1.329 brouard 9444: }
9445: break;
9446: case 2:
9447: if(cptcovprod >0){
9448: if(j==Tprod[ijp]) { /* */
9449: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9450: if(ijp <=cptcovprod) { /* Product */
9451: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9452: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9453: /* 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)]); */
9454: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9455: }else{ /* Vn is dummy and Vm is quanti */
9456: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9457: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9458: }
9459: }else{ /* Vn*Vm Vn is quanti */
9460: if(DummyV[Tvard[ijp][2]]==0){
9461: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9462: }else{ /* Both quanti */
9463: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9464: }
1.268 brouard 9465: }
1.329 brouard 9466: ijp++;
1.237 brouard 9467: }
1.329 brouard 9468: } /* end Tprod */
9469: }
9470: break;
1.349 brouard 9471: case 3:
9472: if(cptcovdageprod >0){
9473: /* if(j==Tprod[ijp]) { */ /* not necessary */
9474: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 9475: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
9476: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9477: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9478: /* 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)]); */
9479: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9480: }else{ /* Vn is dummy and Vm is quanti */
9481: /* 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 9482: 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 9483: }
1.350 brouard 9484: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 9485: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 9486: 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 9487: }else{ /* Both quanti */
1.350 brouard 9488: 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 9489: }
9490: }
9491: ijp++;
9492: }
9493: /* } */ /* end Tprod */
9494: }
9495: break;
1.329 brouard 9496: case 0:
9497: /* simple covariate */
1.264 brouard 9498: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9499: if(Dummy[j]==0){
9500: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9501: }else{ /* quantitative */
9502: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9503: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9504: }
1.329 brouard 9505: /* end simple */
9506: break;
9507: default:
9508: break;
9509: } /* end switch */
1.237 brouard 9510: } /* end j */
1.329 brouard 9511: }else{ /* k=k2 */
9512: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9513: fprintf(ficgp," (1.");i=i-ncovmodel;
9514: }else
9515: i=i-ncovmodel;
1.223 brouard 9516: }
1.227 brouard 9517:
1.223 brouard 9518: if(ng != 1){
9519: fprintf(ficgp,")/(1");
1.227 brouard 9520:
1.264 brouard 9521: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9522: if(nagesqr==0)
1.264 brouard 9523: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9524: else /* nagesqr =1 */
1.264 brouard 9525: 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 9526:
1.223 brouard 9527: ij=1;
1.329 brouard 9528: ijp=1;
9529: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9530: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9531: switch(Typevar[j]){
9532: case 1:
9533: if(cptcovage >0){
9534: if(j==Tage[ij]) { /* Bug valgrind */
9535: if(ij <=cptcovage) { /* Bug valgrind */
9536: if(DummyV[j]==0){/* Bug valgrind */
9537: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9538: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9539: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9540: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9541: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9542: }else{ /* quantitative */
9543: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9544: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9545: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9546: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9547: }
9548: ij++;
9549: }
9550: }
9551: }
9552: break;
9553: case 2:
9554: if(cptcovprod >0){
9555: if(j==Tprod[ijp]) { /* */
9556: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9557: if(ijp <=cptcovprod) { /* Product */
9558: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9559: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9560: /* 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)]); */
9561: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9562: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9563: }else{ /* Vn is dummy and Vm is quanti */
9564: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9565: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9566: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9567: }
9568: }else{ /* Vn*Vm Vn is quanti */
9569: if(DummyV[Tvard[ijp][2]]==0){
9570: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9571: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9572: }else{ /* Both quanti */
9573: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9574: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9575: }
9576: }
9577: ijp++;
9578: }
9579: } /* end Tprod */
9580: } /* end if */
9581: break;
1.349 brouard 9582: case 3:
9583: if(cptcovdageprod >0){
9584: /* if(j==Tprod[ijp]) { /\* *\/ */
9585: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9586: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 9587: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9588: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9589: /* 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 9590: 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 9591: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9592: }else{ /* Vn is dummy and Vm is quanti */
9593: /* 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 9594: 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 9595: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9596: }
9597: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 9598: if(DummyV[Tvardk[ijp][2]]==0){
9599: 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 9600: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9601: }else{ /* Both quanti */
1.350 brouard 9602: 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 9603: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9604: }
9605: }
9606: ijp++;
9607: }
9608: /* } /\* end Tprod *\/ */
9609: } /* end if */
9610: break;
1.329 brouard 9611: case 0:
9612: /* simple covariate */
9613: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9614: if(Dummy[j]==0){
9615: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9616: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9617: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9618: }else{ /* quantitative */
9619: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9620: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9621: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9622: }
9623: /* end simple */
9624: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9625: break;
9626: default:
9627: break;
9628: } /* end switch */
1.223 brouard 9629: }
9630: fprintf(ficgp,")");
9631: }
9632: fprintf(ficgp,")");
9633: if(ng ==2)
1.276 brouard 9634: 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 9635: else /* ng= 3 */
1.276 brouard 9636: 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 9637: }else{ /* end ng <> 1 */
1.223 brouard 9638: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9639: 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 9640: }
9641: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9642: fprintf(ficgp,",");
9643: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9644: fprintf(ficgp,",");
9645: i=i+ncovmodel;
9646: } /* end k */
9647: } /* end k2 */
1.276 brouard 9648: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9649: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9650: } /* end resultline */
1.223 brouard 9651: } /* end ng */
9652: /* avoid: */
9653: fflush(ficgp);
1.126 brouard 9654: } /* end gnuplot */
9655:
9656:
9657: /*************** Moving average **************/
1.219 brouard 9658: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9659: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9660:
1.222 brouard 9661: int i, cpt, cptcod;
9662: int modcovmax =1;
9663: int mobilavrange, mob;
9664: int iage=0;
1.288 brouard 9665: int firstA1=0, firstA2=0;
1.222 brouard 9666:
1.266 brouard 9667: double sum=0., sumr=0.;
1.222 brouard 9668: double age;
1.266 brouard 9669: double *sumnewp, *sumnewm, *sumnewmr;
9670: double *agemingood, *agemaxgood;
9671: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9672:
9673:
1.278 brouard 9674: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9675: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9676:
9677: sumnewp = vector(1,ncovcombmax);
9678: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9679: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9680: agemingood = vector(1,ncovcombmax);
1.266 brouard 9681: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9682: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9683: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9684:
9685: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9686: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9687: sumnewp[cptcod]=0.;
1.266 brouard 9688: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9689: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9690: }
9691: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9692:
1.266 brouard 9693: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9694: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9695: else mobilavrange=mobilav;
9696: for (age=bage; age<=fage; age++)
9697: for (i=1; i<=nlstate;i++)
9698: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9699: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9700: /* We keep the original values on the extreme ages bage, fage and for
9701: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9702: we use a 5 terms etc. until the borders are no more concerned.
9703: */
9704: for (mob=3;mob <=mobilavrange;mob=mob+2){
9705: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9706: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9707: sumnewm[cptcod]=0.;
9708: for (i=1; i<=nlstate;i++){
1.222 brouard 9709: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9710: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9711: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9712: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9713: }
9714: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9715: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9716: } /* end i */
9717: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9718: } /* end cptcod */
1.222 brouard 9719: }/* end age */
9720: }/* end mob */
1.266 brouard 9721: }else{
9722: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9723: return -1;
1.266 brouard 9724: }
9725:
9726: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9727: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9728: if(invalidvarcomb[cptcod]){
9729: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9730: continue;
9731: }
1.219 brouard 9732:
1.266 brouard 9733: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9734: sumnewm[cptcod]=0.;
9735: sumnewmr[cptcod]=0.;
9736: for (i=1; i<=nlstate;i++){
9737: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9738: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9739: }
9740: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9741: agemingoodr[cptcod]=age;
9742: }
9743: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9744: agemingood[cptcod]=age;
9745: }
9746: } /* age */
9747: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9748: sumnewm[cptcod]=0.;
1.266 brouard 9749: sumnewmr[cptcod]=0.;
1.222 brouard 9750: for (i=1; i<=nlstate;i++){
9751: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9752: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9753: }
9754: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9755: agemaxgoodr[cptcod]=age;
1.222 brouard 9756: }
9757: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9758: agemaxgood[cptcod]=age;
9759: }
9760: } /* age */
9761: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9762: /* but they will change */
1.288 brouard 9763: firstA1=0;firstA2=0;
1.266 brouard 9764: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9765: sumnewm[cptcod]=0.;
9766: sumnewmr[cptcod]=0.;
9767: for (i=1; i<=nlstate;i++){
9768: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9769: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9770: }
9771: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9772: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9773: agemaxgoodr[cptcod]=age; /* age min */
9774: for (i=1; i<=nlstate;i++)
9775: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9776: }else{ /* bad we change the value with the values of good ages */
9777: for (i=1; i<=nlstate;i++){
9778: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9779: } /* i */
9780: } /* end bad */
9781: }else{
9782: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9783: agemaxgood[cptcod]=age;
9784: }else{ /* bad we change the value with the values of good ages */
9785: for (i=1; i<=nlstate;i++){
9786: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9787: } /* i */
9788: } /* end bad */
9789: }/* end else */
9790: sum=0.;sumr=0.;
9791: for (i=1; i<=nlstate;i++){
9792: sum+=mobaverage[(int)age][i][cptcod];
9793: sumr+=probs[(int)age][i][cptcod];
9794: }
9795: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9796: if(!firstA1){
9797: firstA1=1;
9798: 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);
9799: }
9800: 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 9801: } /* end bad */
9802: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9803: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9804: if(!firstA2){
9805: firstA2=1;
9806: 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);
9807: }
9808: 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 9809: } /* end bad */
9810: }/* age */
1.266 brouard 9811:
9812: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9813: sumnewm[cptcod]=0.;
1.266 brouard 9814: sumnewmr[cptcod]=0.;
1.222 brouard 9815: for (i=1; i<=nlstate;i++){
9816: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9817: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9818: }
9819: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9820: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9821: agemingoodr[cptcod]=age;
9822: for (i=1; i<=nlstate;i++)
9823: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9824: }else{ /* bad we change the value with the values of good ages */
9825: for (i=1; i<=nlstate;i++){
9826: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9827: } /* i */
9828: } /* end bad */
9829: }else{
9830: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9831: agemingood[cptcod]=age;
9832: }else{ /* bad */
9833: for (i=1; i<=nlstate;i++){
9834: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9835: } /* i */
9836: } /* end bad */
9837: }/* end else */
9838: sum=0.;sumr=0.;
9839: for (i=1; i<=nlstate;i++){
9840: sum+=mobaverage[(int)age][i][cptcod];
9841: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9842: }
1.266 brouard 9843: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9844: 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 9845: } /* end bad */
9846: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9847: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9848: 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 9849: } /* end bad */
9850: }/* age */
1.266 brouard 9851:
1.222 brouard 9852:
9853: for (age=bage; age<=fage; age++){
1.235 brouard 9854: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9855: sumnewp[cptcod]=0.;
9856: sumnewm[cptcod]=0.;
9857: for (i=1; i<=nlstate;i++){
9858: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9859: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9860: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9861: }
9862: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9863: }
9864: /* printf("\n"); */
9865: /* } */
1.266 brouard 9866:
1.222 brouard 9867: /* brutal averaging */
1.266 brouard 9868: /* for (i=1; i<=nlstate;i++){ */
9869: /* for (age=1; age<=bage; age++){ */
9870: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9871: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9872: /* } */
9873: /* for (age=fage; age<=AGESUP; age++){ */
9874: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9875: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9876: /* } */
9877: /* } /\* end i status *\/ */
9878: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9879: /* for (age=1; age<=AGESUP; age++){ */
9880: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9881: /* mobaverage[(int)age][i][cptcod]=0.; */
9882: /* } */
9883: /* } */
1.222 brouard 9884: }/* end cptcod */
1.266 brouard 9885: free_vector(agemaxgoodr,1, ncovcombmax);
9886: free_vector(agemaxgood,1, ncovcombmax);
9887: free_vector(agemingood,1, ncovcombmax);
9888: free_vector(agemingoodr,1, ncovcombmax);
9889: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9890: free_vector(sumnewm,1, ncovcombmax);
9891: free_vector(sumnewp,1, ncovcombmax);
9892: return 0;
9893: }/* End movingaverage */
1.218 brouard 9894:
1.126 brouard 9895:
1.296 brouard 9896:
1.126 brouard 9897: /************** Forecasting ******************/
1.296 brouard 9898: /* 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)*/
9899: 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){
9900: /* dateintemean, mean date of interviews
9901: dateprojd, year, month, day of starting projection
9902: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9903: agemin, agemax range of age
9904: dateprev1 dateprev2 range of dates during which prevalence is computed
9905: */
1.296 brouard 9906: /* double anprojd, mprojd, jprojd; */
9907: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9908: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9909: double agec; /* generic age */
1.296 brouard 9910: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9911: double *popeffectif,*popcount;
9912: double ***p3mat;
1.218 brouard 9913: /* double ***mobaverage; */
1.126 brouard 9914: char fileresf[FILENAMELENGTH];
9915:
9916: agelim=AGESUP;
1.211 brouard 9917: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9918: in each health status at the date of interview (if between dateprev1 and dateprev2).
9919: We still use firstpass and lastpass as another selection.
9920: */
1.214 brouard 9921: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9922: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9923:
1.201 brouard 9924: strcpy(fileresf,"F_");
9925: strcat(fileresf,fileresu);
1.126 brouard 9926: if((ficresf=fopen(fileresf,"w"))==NULL) {
9927: printf("Problem with forecast resultfile: %s\n", fileresf);
9928: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9929: }
1.235 brouard 9930: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9931: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9932:
1.225 brouard 9933: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9934:
9935:
9936: stepsize=(int) (stepm+YEARM-1)/YEARM;
9937: if (stepm<=12) stepsize=1;
9938: if(estepm < stepm){
9939: printf ("Problem %d lower than %d\n",estepm, stepm);
9940: }
1.270 brouard 9941: else{
9942: hstepm=estepm;
9943: }
9944: if(estepm > stepm){ /* Yes every two year */
9945: stepsize=2;
9946: }
1.296 brouard 9947: hstepm=hstepm/stepm;
1.126 brouard 9948:
1.296 brouard 9949:
9950: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9951: /* fractional in yp1 *\/ */
9952: /* aintmean=yp; */
9953: /* yp2=modf((yp1*12),&yp); */
9954: /* mintmean=yp; */
9955: /* yp1=modf((yp2*30.5),&yp); */
9956: /* jintmean=yp; */
9957: /* if(jintmean==0) jintmean=1; */
9958: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9959:
1.296 brouard 9960:
9961: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9962: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9963: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 9964: /* i1=pow(2,cptcoveff); */
9965: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 9966:
1.296 brouard 9967: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9968:
9969: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9970:
1.126 brouard 9971: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 9972: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9973: k=TKresult[nres];
9974: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
9975: /* 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) *\/ */
9976: /* if(i1 != 1 && TKresult[nres]!= k) */
9977: /* continue; */
9978: /* if(invalidvarcomb[k]){ */
9979: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
9980: /* continue; */
9981: /* } */
1.227 brouard 9982: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 9983: for(j=1;j<=cptcovs;j++){
9984: /* for(j=1;j<=cptcoveff;j++) { */
9985: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
9986: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9987: /* } */
9988: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9989: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9990: /* } */
9991: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 9992: }
1.351 brouard 9993:
1.227 brouard 9994: fprintf(ficresf," yearproj age");
9995: for(j=1; j<=nlstate+ndeath;j++){
9996: for(i=1; i<=nlstate;i++)
9997: fprintf(ficresf," p%d%d",i,j);
9998: fprintf(ficresf," wp.%d",j);
9999: }
1.296 brouard 10000: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 10001: fprintf(ficresf,"\n");
1.296 brouard 10002: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 10003: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
10004: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 10005: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
10006: nhstepm = nhstepm/hstepm;
10007: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10008: oldm=oldms;savm=savms;
1.268 brouard 10009: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 10010: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 10011: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 10012: for (h=0; h<=nhstepm; h++){
10013: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 10014: break;
10015: }
10016: }
10017: fprintf(ficresf,"\n");
1.351 brouard 10018: /* for(j=1;j<=cptcoveff;j++) */
10019: for(j=1;j<=cptcovs;j++)
10020: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 10021: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 10022: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 10023: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 10024:
10025: for(j=1; j<=nlstate+ndeath;j++) {
10026: ppij=0.;
10027: for(i=1; i<=nlstate;i++) {
1.278 brouard 10028: if (mobilav>=1)
10029: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
10030: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
10031: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
10032: }
1.268 brouard 10033: fprintf(ficresf," %.3f", p3mat[i][j][h]);
10034: } /* end i */
10035: fprintf(ficresf," %.3f", ppij);
10036: }/* end j */
1.227 brouard 10037: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10038: } /* end agec */
1.266 brouard 10039: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
10040: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 10041: } /* end yearp */
10042: } /* end k */
1.219 brouard 10043:
1.126 brouard 10044: fclose(ficresf);
1.215 brouard 10045: printf("End of Computing forecasting \n");
10046: fprintf(ficlog,"End of Computing forecasting\n");
10047:
1.126 brouard 10048: }
10049:
1.269 brouard 10050: /************** Back Forecasting ******************/
1.296 brouard 10051: /* 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){ */
10052: 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){
10053: /* back1, year, month, day of starting backprojection
1.267 brouard 10054: agemin, agemax range of age
10055: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 10056: anback2 year of end of backprojection (same day and month as back1).
10057: prevacurrent and prev are prevalences.
1.267 brouard 10058: */
10059: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
10060: double agec; /* generic age */
1.302 brouard 10061: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10062: double *popeffectif,*popcount;
10063: double ***p3mat;
10064: /* double ***mobaverage; */
10065: char fileresfb[FILENAMELENGTH];
10066:
1.268 brouard 10067: agelim=AGEINF;
1.267 brouard 10068: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10069: in each health status at the date of interview (if between dateprev1 and dateprev2).
10070: We still use firstpass and lastpass as another selection.
10071: */
10072: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10073: /* firstpass, lastpass, stepm, weightopt, model); */
10074:
10075: /*Do we need to compute prevalence again?*/
10076:
10077: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10078:
10079: strcpy(fileresfb,"FB_");
10080: strcat(fileresfb,fileresu);
10081: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10082: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10083: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10084: }
10085: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10086: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10087:
10088: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10089:
10090:
10091: stepsize=(int) (stepm+YEARM-1)/YEARM;
10092: if (stepm<=12) stepsize=1;
10093: if(estepm < stepm){
10094: printf ("Problem %d lower than %d\n",estepm, stepm);
10095: }
1.270 brouard 10096: else{
10097: hstepm=estepm;
10098: }
10099: if(estepm >= stepm){ /* Yes every two year */
10100: stepsize=2;
10101: }
1.267 brouard 10102:
10103: hstepm=hstepm/stepm;
1.296 brouard 10104: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10105: /* fractional in yp1 *\/ */
10106: /* aintmean=yp; */
10107: /* yp2=modf((yp1*12),&yp); */
10108: /* mintmean=yp; */
10109: /* yp1=modf((yp2*30.5),&yp); */
10110: /* jintmean=yp; */
10111: /* if(jintmean==0) jintmean=1; */
10112: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10113:
1.351 brouard 10114: /* i1=pow(2,cptcoveff); */
10115: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 10116:
1.296 brouard 10117: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10118: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10119:
10120: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10121:
1.351 brouard 10122: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10123: k=TKresult[nres];
10124: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
10125: /* for(k=1; k<=i1;k++){ */
10126: /* if(i1 != 1 && TKresult[nres]!= k) */
10127: /* continue; */
10128: /* if(invalidvarcomb[k]){ */
10129: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
10130: /* continue; */
10131: /* } */
1.268 brouard 10132: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 10133: for(j=1;j<=cptcovs;j++){
10134: /* for(j=1;j<=cptcoveff;j++) { */
10135: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10136: /* } */
10137: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 10138: }
1.351 brouard 10139: /* fprintf(ficrespij,"******\n"); */
10140: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10141: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10142: /* } */
1.267 brouard 10143: fprintf(ficresfb," yearbproj age");
10144: for(j=1; j<=nlstate+ndeath;j++){
10145: for(i=1; i<=nlstate;i++)
1.268 brouard 10146: fprintf(ficresfb," b%d%d",i,j);
10147: fprintf(ficresfb," b.%d",j);
1.267 brouard 10148: }
1.296 brouard 10149: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10150: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10151: fprintf(ficresfb,"\n");
1.296 brouard 10152: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10153: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10154: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10155: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10156: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10157: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10158: nhstepm = nhstepm/hstepm;
10159: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10160: oldm=oldms;savm=savms;
1.268 brouard 10161: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10162: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10163: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10164: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10165: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10166: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10167: for (h=0; h<=nhstepm; h++){
1.268 brouard 10168: if (h*hstepm/YEARM*stepm ==-yearp) {
10169: break;
10170: }
10171: }
10172: fprintf(ficresfb,"\n");
1.351 brouard 10173: /* for(j=1;j<=cptcoveff;j++) */
10174: for(j=1;j<=cptcovs;j++)
10175: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10176: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 10177: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10178: for(i=1; i<=nlstate+ndeath;i++) {
10179: ppij=0.;ppi=0.;
10180: for(j=1; j<=nlstate;j++) {
10181: /* if (mobilav==1) */
1.269 brouard 10182: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10183: ppi=ppi+prevacurrent[(int)agec][j][k];
10184: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10185: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10186: /* else { */
10187: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10188: /* } */
1.268 brouard 10189: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10190: } /* end j */
10191: if(ppi <0.99){
10192: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10193: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10194: }
10195: fprintf(ficresfb," %.3f", ppij);
10196: }/* end j */
1.267 brouard 10197: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10198: } /* end agec */
10199: } /* end yearp */
10200: } /* end k */
1.217 brouard 10201:
1.267 brouard 10202: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10203:
1.267 brouard 10204: fclose(ficresfb);
10205: printf("End of Computing Back forecasting \n");
10206: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10207:
1.267 brouard 10208: }
1.217 brouard 10209:
1.269 brouard 10210: /* Variance of prevalence limit: varprlim */
10211: 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 10212: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10213:
10214: char fileresvpl[FILENAMELENGTH];
10215: FILE *ficresvpl;
10216: double **oldm, **savm;
10217: double **varpl; /* Variances of prevalence limits by age */
10218: int i1, k, nres, j ;
10219:
10220: strcpy(fileresvpl,"VPL_");
10221: strcat(fileresvpl,fileresu);
10222: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10223: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10224: exit(0);
10225: }
1.288 brouard 10226: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10227: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10228:
10229: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10230: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10231:
10232: i1=pow(2,cptcoveff);
10233: if (cptcovn < 1){i1=1;}
10234:
1.337 brouard 10235: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10236: k=TKresult[nres];
1.338 brouard 10237: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10238: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10239: if(i1 != 1 && TKresult[nres]!= k)
10240: continue;
10241: fprintf(ficresvpl,"\n#****** ");
10242: printf("\n#****** ");
10243: fprintf(ficlog,"\n#****** ");
1.337 brouard 10244: for(j=1;j<=cptcovs;j++) {
10245: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10246: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10247: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10248: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10249: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10250: }
1.337 brouard 10251: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10252: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10253: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10254: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10255: /* } */
1.269 brouard 10256: fprintf(ficresvpl,"******\n");
10257: printf("******\n");
10258: fprintf(ficlog,"******\n");
10259:
10260: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10261: oldm=oldms;savm=savms;
10262: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10263: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10264: /*}*/
10265: }
10266:
10267: fclose(ficresvpl);
1.288 brouard 10268: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10269: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10270:
10271: }
10272: /* Variance of back prevalence: varbprlim */
10273: 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){
10274: /*------- Variance of back (stable) prevalence------*/
10275:
10276: char fileresvbl[FILENAMELENGTH];
10277: FILE *ficresvbl;
10278:
10279: double **oldm, **savm;
10280: double **varbpl; /* Variances of back prevalence limits by age */
10281: int i1, k, nres, j ;
10282:
10283: strcpy(fileresvbl,"VBL_");
10284: strcat(fileresvbl,fileresu);
10285: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10286: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10287: exit(0);
10288: }
10289: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10290: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10291:
10292:
10293: i1=pow(2,cptcoveff);
10294: if (cptcovn < 1){i1=1;}
10295:
1.337 brouard 10296: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10297: k=TKresult[nres];
1.338 brouard 10298: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10299: /* for(k=1; k<=i1;k++){ */
10300: /* if(i1 != 1 && TKresult[nres]!= k) */
10301: /* continue; */
1.269 brouard 10302: fprintf(ficresvbl,"\n#****** ");
10303: printf("\n#****** ");
10304: fprintf(ficlog,"\n#****** ");
1.337 brouard 10305: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10306: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10307: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10308: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10309: /* for(j=1;j<=cptcoveff;j++) { */
10310: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10311: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10312: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10313: /* } */
10314: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10315: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10316: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10317: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10318: }
10319: fprintf(ficresvbl,"******\n");
10320: printf("******\n");
10321: fprintf(ficlog,"******\n");
10322:
10323: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10324: oldm=oldms;savm=savms;
10325:
10326: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10327: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10328: /*}*/
10329: }
10330:
10331: fclose(ficresvbl);
10332: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10333: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10334:
10335: } /* End of varbprlim */
10336:
1.126 brouard 10337: /************** Forecasting *****not tested NB*************/
1.227 brouard 10338: /* 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 10339:
1.227 brouard 10340: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10341: /* int *popage; */
10342: /* double calagedatem, agelim, kk1, kk2; */
10343: /* double *popeffectif,*popcount; */
10344: /* double ***p3mat,***tabpop,***tabpopprev; */
10345: /* /\* double ***mobaverage; *\/ */
10346: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10347:
1.227 brouard 10348: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10349: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10350: /* agelim=AGESUP; */
10351: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10352:
1.227 brouard 10353: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10354:
10355:
1.227 brouard 10356: /* strcpy(filerespop,"POP_"); */
10357: /* strcat(filerespop,fileresu); */
10358: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10359: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10360: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10361: /* } */
10362: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10363: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10364:
1.227 brouard 10365: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10366:
1.227 brouard 10367: /* /\* if (mobilav!=0) { *\/ */
10368: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10369: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10370: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10371: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10372: /* /\* } *\/ */
10373: /* /\* } *\/ */
1.126 brouard 10374:
1.227 brouard 10375: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10376: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10377:
1.227 brouard 10378: /* agelim=AGESUP; */
1.126 brouard 10379:
1.227 brouard 10380: /* hstepm=1; */
10381: /* hstepm=hstepm/stepm; */
1.218 brouard 10382:
1.227 brouard 10383: /* if (popforecast==1) { */
10384: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10385: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10386: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10387: /* } */
10388: /* popage=ivector(0,AGESUP); */
10389: /* popeffectif=vector(0,AGESUP); */
10390: /* popcount=vector(0,AGESUP); */
1.126 brouard 10391:
1.227 brouard 10392: /* i=1; */
10393: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10394:
1.227 brouard 10395: /* imx=i; */
10396: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10397: /* } */
1.218 brouard 10398:
1.227 brouard 10399: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10400: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10401: /* k=k+1; */
10402: /* fprintf(ficrespop,"\n#******"); */
10403: /* for(j=1;j<=cptcoveff;j++) { */
10404: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10405: /* } */
10406: /* fprintf(ficrespop,"******\n"); */
10407: /* fprintf(ficrespop,"# Age"); */
10408: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10409: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10410:
1.227 brouard 10411: /* for (cpt=0; cpt<=0;cpt++) { */
10412: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10413:
1.227 brouard 10414: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10415: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10416: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10417:
1.227 brouard 10418: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10419: /* oldm=oldms;savm=savms; */
10420: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10421:
1.227 brouard 10422: /* for (h=0; h<=nhstepm; h++){ */
10423: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10424: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10425: /* } */
10426: /* for(j=1; j<=nlstate+ndeath;j++) { */
10427: /* kk1=0.;kk2=0; */
10428: /* for(i=1; i<=nlstate;i++) { */
10429: /* if (mobilav==1) */
10430: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10431: /* else { */
10432: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10433: /* } */
10434: /* } */
10435: /* if (h==(int)(calagedatem+12*cpt)){ */
10436: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10437: /* /\*fprintf(ficrespop," %.3f", kk1); */
10438: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10439: /* } */
10440: /* } */
10441: /* for(i=1; i<=nlstate;i++){ */
10442: /* kk1=0.; */
10443: /* for(j=1; j<=nlstate;j++){ */
10444: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10445: /* } */
10446: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10447: /* } */
1.218 brouard 10448:
1.227 brouard 10449: /* if (h==(int)(calagedatem+12*cpt)) */
10450: /* for(j=1; j<=nlstate;j++) */
10451: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10452: /* } */
10453: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10454: /* } */
10455: /* } */
1.218 brouard 10456:
1.227 brouard 10457: /* /\******\/ */
1.218 brouard 10458:
1.227 brouard 10459: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10460: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10461: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10462: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10463: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10464:
1.227 brouard 10465: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10466: /* oldm=oldms;savm=savms; */
10467: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10468: /* for (h=0; h<=nhstepm; h++){ */
10469: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10470: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10471: /* } */
10472: /* for(j=1; j<=nlstate+ndeath;j++) { */
10473: /* kk1=0.;kk2=0; */
10474: /* for(i=1; i<=nlstate;i++) { */
10475: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10476: /* } */
10477: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10478: /* } */
10479: /* } */
10480: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10481: /* } */
10482: /* } */
10483: /* } */
10484: /* } */
1.218 brouard 10485:
1.227 brouard 10486: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10487:
1.227 brouard 10488: /* if (popforecast==1) { */
10489: /* free_ivector(popage,0,AGESUP); */
10490: /* free_vector(popeffectif,0,AGESUP); */
10491: /* free_vector(popcount,0,AGESUP); */
10492: /* } */
10493: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10494: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10495: /* fclose(ficrespop); */
10496: /* } /\* End of popforecast *\/ */
1.218 brouard 10497:
1.126 brouard 10498: int fileappend(FILE *fichier, char *optionfich)
10499: {
10500: if((fichier=fopen(optionfich,"a"))==NULL) {
10501: printf("Problem with file: %s\n", optionfich);
10502: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10503: return (0);
10504: }
10505: fflush(fichier);
10506: return (1);
10507: }
10508:
10509:
10510: /**************** function prwizard **********************/
10511: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10512: {
10513:
10514: /* Wizard to print covariance matrix template */
10515:
1.164 brouard 10516: char ca[32], cb[32];
10517: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10518: int numlinepar;
10519:
10520: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10521: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10522: for(i=1; i <=nlstate; i++){
10523: jj=0;
10524: for(j=1; j <=nlstate+ndeath; j++){
10525: if(j==i) continue;
10526: jj++;
10527: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10528: printf("%1d%1d",i,j);
10529: fprintf(ficparo,"%1d%1d",i,j);
10530: for(k=1; k<=ncovmodel;k++){
10531: /* printf(" %lf",param[i][j][k]); */
10532: /* fprintf(ficparo," %lf",param[i][j][k]); */
10533: printf(" 0.");
10534: fprintf(ficparo," 0.");
10535: }
10536: printf("\n");
10537: fprintf(ficparo,"\n");
10538: }
10539: }
10540: printf("# Scales (for hessian or gradient estimation)\n");
10541: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10542: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10543: for(i=1; i <=nlstate; i++){
10544: jj=0;
10545: for(j=1; j <=nlstate+ndeath; j++){
10546: if(j==i) continue;
10547: jj++;
10548: fprintf(ficparo,"%1d%1d",i,j);
10549: printf("%1d%1d",i,j);
10550: fflush(stdout);
10551: for(k=1; k<=ncovmodel;k++){
10552: /* printf(" %le",delti3[i][j][k]); */
10553: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10554: printf(" 0.");
10555: fprintf(ficparo," 0.");
10556: }
10557: numlinepar++;
10558: printf("\n");
10559: fprintf(ficparo,"\n");
10560: }
10561: }
10562: printf("# Covariance matrix\n");
10563: /* # 121 Var(a12)\n\ */
10564: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10565: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10566: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10567: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10568: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10569: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10570: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10571: fflush(stdout);
10572: fprintf(ficparo,"# Covariance matrix\n");
10573: /* # 121 Var(a12)\n\ */
10574: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10575: /* # ...\n\ */
10576: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10577:
10578: for(itimes=1;itimes<=2;itimes++){
10579: jj=0;
10580: for(i=1; i <=nlstate; i++){
10581: for(j=1; j <=nlstate+ndeath; j++){
10582: if(j==i) continue;
10583: for(k=1; k<=ncovmodel;k++){
10584: jj++;
10585: ca[0]= k+'a'-1;ca[1]='\0';
10586: if(itimes==1){
10587: printf("#%1d%1d%d",i,j,k);
10588: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10589: }else{
10590: printf("%1d%1d%d",i,j,k);
10591: fprintf(ficparo,"%1d%1d%d",i,j,k);
10592: /* printf(" %.5le",matcov[i][j]); */
10593: }
10594: ll=0;
10595: for(li=1;li <=nlstate; li++){
10596: for(lj=1;lj <=nlstate+ndeath; lj++){
10597: if(lj==li) continue;
10598: for(lk=1;lk<=ncovmodel;lk++){
10599: ll++;
10600: if(ll<=jj){
10601: cb[0]= lk +'a'-1;cb[1]='\0';
10602: if(ll<jj){
10603: if(itimes==1){
10604: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10605: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10606: }else{
10607: printf(" 0.");
10608: fprintf(ficparo," 0.");
10609: }
10610: }else{
10611: if(itimes==1){
10612: printf(" Var(%s%1d%1d)",ca,i,j);
10613: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10614: }else{
10615: printf(" 0.");
10616: fprintf(ficparo," 0.");
10617: }
10618: }
10619: }
10620: } /* end lk */
10621: } /* end lj */
10622: } /* end li */
10623: printf("\n");
10624: fprintf(ficparo,"\n");
10625: numlinepar++;
10626: } /* end k*/
10627: } /*end j */
10628: } /* end i */
10629: } /* end itimes */
10630:
10631: } /* end of prwizard */
10632: /******************* Gompertz Likelihood ******************************/
10633: double gompertz(double x[])
10634: {
1.302 brouard 10635: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10636: int i,n=0; /* n is the size of the sample */
10637:
1.220 brouard 10638: for (i=1;i<=imx ; i++) {
1.126 brouard 10639: sump=sump+weight[i];
10640: /* sump=sump+1;*/
10641: num=num+1;
10642: }
1.302 brouard 10643: L=0.0;
10644: /* agegomp=AGEGOMP; */
1.126 brouard 10645: /* for (i=0; i<=imx; i++)
10646: 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]);*/
10647:
1.302 brouard 10648: for (i=1;i<=imx ; i++) {
10649: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10650: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10651: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10652: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10653: * +
10654: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10655: */
10656: if (wav[i] > 1 || agedc[i] < AGESUP) {
10657: if (cens[i] == 1){
10658: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10659: } else if (cens[i] == 0){
1.126 brouard 10660: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10661: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10662: } else
10663: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10664: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10665: L=L+A*weight[i];
1.126 brouard 10666: /* 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 10667: }
10668: }
1.126 brouard 10669:
1.302 brouard 10670: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10671:
10672: return -2*L*num/sump;
10673: }
10674:
1.136 brouard 10675: #ifdef GSL
10676: /******************* Gompertz_f Likelihood ******************************/
10677: double gompertz_f(const gsl_vector *v, void *params)
10678: {
1.302 brouard 10679: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10680: double *x= (double *) v->data;
10681: int i,n=0; /* n is the size of the sample */
10682:
10683: for (i=0;i<=imx-1 ; i++) {
10684: sump=sump+weight[i];
10685: /* sump=sump+1;*/
10686: num=num+1;
10687: }
10688:
10689:
10690: /* for (i=0; i<=imx; i++)
10691: 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]);*/
10692: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10693: for (i=1;i<=imx ; i++)
10694: {
10695: if (cens[i] == 1 && wav[i]>1)
10696: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10697:
10698: if (cens[i] == 0 && wav[i]>1)
10699: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10700: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10701:
10702: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10703: if (wav[i] > 1 ) { /* ??? */
10704: LL=LL+A*weight[i];
10705: /* 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]);*/
10706: }
10707: }
10708:
10709: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10710: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10711:
10712: return -2*LL*num/sump;
10713: }
10714: #endif
10715:
1.126 brouard 10716: /******************* Printing html file ***********/
1.201 brouard 10717: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10718: int lastpass, int stepm, int weightopt, char model[],\
10719: int imx, double p[],double **matcov,double agemortsup){
10720: int i,k;
10721:
10722: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10723: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10724: for (i=1;i<=2;i++)
10725: 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 10726: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10727: fprintf(fichtm,"</ul>");
10728:
10729: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10730:
10731: 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>");
10732:
10733: for (k=agegomp;k<(agemortsup-2);k++)
10734: 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]);
10735:
10736:
10737: fflush(fichtm);
10738: }
10739:
10740: /******************* Gnuplot file **************/
1.201 brouard 10741: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10742:
10743: char dirfileres[132],optfileres[132];
1.164 brouard 10744:
1.126 brouard 10745: int ng;
10746:
10747:
10748: /*#ifdef windows */
10749: fprintf(ficgp,"cd \"%s\" \n",pathc);
10750: /*#endif */
10751:
10752:
10753: strcpy(dirfileres,optionfilefiname);
10754: strcpy(optfileres,"vpl");
1.199 brouard 10755: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10756: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10757: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10758: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10759: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10760:
10761: }
10762:
1.136 brouard 10763: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10764: {
1.126 brouard 10765:
1.136 brouard 10766: /*-------- data file ----------*/
10767: FILE *fic;
10768: char dummy[]=" ";
1.240 brouard 10769: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10770: int lstra;
1.136 brouard 10771: int linei, month, year,iout;
1.302 brouard 10772: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10773: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10774: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10775: char *stratrunc;
1.223 brouard 10776:
1.349 brouard 10777: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
10778: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10779:
10780: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10781:
1.136 brouard 10782: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10783: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10784: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10785: }
1.126 brouard 10786:
1.302 brouard 10787: /* Is it a BOM UTF-8 Windows file? */
10788: /* First data line */
10789: linei=0;
10790: while(fgets(line, MAXLINE, fic)) {
10791: noffset=0;
10792: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10793: {
10794: noffset=noffset+3;
10795: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10796: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10797: fflush(ficlog); return 1;
10798: }
10799: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10800: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10801: {
10802: noffset=noffset+2;
1.304 brouard 10803: 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);
10804: 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 10805: fflush(ficlog); return 1;
10806: }
10807: else if( line[0] == 0 && line[1] == 0)
10808: {
10809: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10810: noffset=noffset+4;
1.304 brouard 10811: 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);
10812: 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 10813: fflush(ficlog); return 1;
10814: }
10815: } else{
10816: ;/*printf(" Not a BOM file\n");*/
10817: }
10818: /* If line starts with a # it is a comment */
10819: if (line[noffset] == '#') {
10820: linei=linei+1;
10821: break;
10822: }else{
10823: break;
10824: }
10825: }
10826: fclose(fic);
10827: if((fic=fopen(datafile,"r"))==NULL) {
10828: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10829: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10830: }
10831: /* Not a Bom file */
10832:
1.136 brouard 10833: i=1;
10834: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10835: linei=linei+1;
10836: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10837: if(line[j] == '\t')
10838: line[j] = ' ';
10839: }
10840: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10841: ;
10842: };
10843: line[j+1]=0; /* Trims blanks at end of line */
10844: if(line[0]=='#'){
10845: fprintf(ficlog,"Comment line\n%s\n",line);
10846: printf("Comment line\n%s\n",line);
10847: continue;
10848: }
10849: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10850: strcpy(line, linetmp);
1.223 brouard 10851:
10852: /* Loops on waves */
10853: for (j=maxwav;j>=1;j--){
10854: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10855: cutv(stra, strb, line, ' ');
10856: if(strb[0]=='.') { /* Missing value */
10857: lval=-1;
10858: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10859: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10860: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10861: 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);
10862: 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);
10863: return 1;
10864: }
10865: }else{
10866: errno=0;
10867: /* what_kind_of_number(strb); */
10868: dval=strtod(strb,&endptr);
10869: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10870: /* if(strb != endptr && *endptr == '\0') */
10871: /* dval=dlval; */
10872: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10873: if( strb[0]=='\0' || (*endptr != '\0')){
10874: 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);
10875: 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);
10876: return 1;
10877: }
10878: cotqvar[j][iv][i]=dval;
1.341 brouard 10879: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10880: }
10881: strcpy(line,stra);
1.223 brouard 10882: }/* end loop ntqv */
1.225 brouard 10883:
1.223 brouard 10884: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10885: cutv(stra, strb, line, ' ');
10886: if(strb[0]=='.') { /* Missing value */
10887: lval=-1;
10888: }else{
10889: errno=0;
10890: lval=strtol(strb,&endptr,10);
10891: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10892: if( strb[0]=='\0' || (*endptr != '\0')){
10893: 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);
10894: 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);
10895: return 1;
10896: }
10897: }
10898: if(lval <-1 || lval >1){
10899: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10900: 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 10901: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10902: For example, for multinomial values like 1, 2 and 3,\n \
10903: build V1=0 V2=0 for the reference value (1),\n \
10904: V1=1 V2=0 for (2) \n \
1.223 brouard 10905: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10906: output of IMaCh is often meaningless.\n \
1.319 brouard 10907: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10908: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10909: 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 10910: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10911: For example, for multinomial values like 1, 2 and 3,\n \
10912: build V1=0 V2=0 for the reference value (1),\n \
10913: V1=1 V2=0 for (2) \n \
1.223 brouard 10914: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10915: output of IMaCh is often meaningless.\n \
1.319 brouard 10916: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10917: return 1;
10918: }
1.341 brouard 10919: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10920: strcpy(line,stra);
1.223 brouard 10921: }/* end loop ntv */
1.225 brouard 10922:
1.223 brouard 10923: /* Statuses at wave */
1.137 brouard 10924: cutv(stra, strb, line, ' ');
1.223 brouard 10925: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10926: lval=-1;
1.136 brouard 10927: }else{
1.238 brouard 10928: errno=0;
10929: lval=strtol(strb,&endptr,10);
10930: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10931: if( strb[0]=='\0' || (*endptr != '\0' )){
10932: 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);
10933: 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);
10934: return 1;
10935: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10936: 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);
10937: 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 10938: return 1;
10939: }
1.136 brouard 10940: }
1.225 brouard 10941:
1.136 brouard 10942: s[j][i]=lval;
1.225 brouard 10943:
1.223 brouard 10944: /* Date of Interview */
1.136 brouard 10945: strcpy(line,stra);
10946: cutv(stra, strb,line,' ');
1.169 brouard 10947: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10948: }
1.169 brouard 10949: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10950: month=99;
10951: year=9999;
1.136 brouard 10952: }else{
1.225 brouard 10953: 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);
10954: 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);
10955: return 1;
1.136 brouard 10956: }
10957: anint[j][i]= (double) year;
1.302 brouard 10958: mint[j][i]= (double)month;
10959: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10960: /* 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]); */
10961: /* 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]); */
10962: /* } */
1.136 brouard 10963: strcpy(line,stra);
1.223 brouard 10964: } /* End loop on waves */
1.225 brouard 10965:
1.223 brouard 10966: /* Date of death */
1.136 brouard 10967: cutv(stra, strb,line,' ');
1.169 brouard 10968: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10969: }
1.169 brouard 10970: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10971: month=99;
10972: year=9999;
10973: }else{
1.141 brouard 10974: 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 10975: 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);
10976: return 1;
1.136 brouard 10977: }
10978: andc[i]=(double) year;
10979: moisdc[i]=(double) month;
10980: strcpy(line,stra);
10981:
1.223 brouard 10982: /* Date of birth */
1.136 brouard 10983: cutv(stra, strb,line,' ');
1.169 brouard 10984: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10985: }
1.169 brouard 10986: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10987: month=99;
10988: year=9999;
10989: }else{
1.141 brouard 10990: 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);
10991: 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 10992: return 1;
1.136 brouard 10993: }
10994: if (year==9999) {
1.141 brouard 10995: 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);
10996: 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 10997: return 1;
10998:
1.136 brouard 10999: }
11000: annais[i]=(double)(year);
1.302 brouard 11001: moisnais[i]=(double)(month);
11002: for (j=1;j<=maxwav;j++){
11003: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
11004: 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]);
11005: 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]);
11006: }
11007: }
11008:
1.136 brouard 11009: strcpy(line,stra);
1.225 brouard 11010:
1.223 brouard 11011: /* Sample weight */
1.136 brouard 11012: cutv(stra, strb,line,' ');
11013: errno=0;
11014: dval=strtod(strb,&endptr);
11015: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 11016: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
11017: 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 11018: fflush(ficlog);
11019: return 1;
11020: }
11021: weight[i]=dval;
11022: strcpy(line,stra);
1.225 brouard 11023:
1.223 brouard 11024: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
11025: cutv(stra, strb, line, ' ');
11026: if(strb[0]=='.') { /* Missing value */
1.225 brouard 11027: lval=-1;
1.311 brouard 11028: coqvar[iv][i]=NAN;
11029: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 11030: }else{
1.225 brouard 11031: errno=0;
11032: /* what_kind_of_number(strb); */
11033: dval=strtod(strb,&endptr);
11034: /* if(strb != endptr && *endptr == '\0') */
11035: /* dval=dlval; */
11036: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
11037: if( strb[0]=='\0' || (*endptr != '\0')){
11038: 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);
11039: 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);
11040: return 1;
11041: }
11042: coqvar[iv][i]=dval;
1.226 brouard 11043: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 11044: }
11045: strcpy(line,stra);
11046: }/* end loop nqv */
1.136 brouard 11047:
1.223 brouard 11048: /* Covariate values */
1.136 brouard 11049: for (j=ncovcol;j>=1;j--){
11050: cutv(stra, strb,line,' ');
1.223 brouard 11051: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 11052: lval=-1;
1.136 brouard 11053: }else{
1.225 brouard 11054: errno=0;
11055: lval=strtol(strb,&endptr,10);
11056: if( strb[0]=='\0' || (*endptr != '\0')){
11057: 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);
11058: 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);
11059: return 1;
11060: }
1.136 brouard 11061: }
11062: if(lval <-1 || lval >1){
1.225 brouard 11063: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11064: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11065: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11066: For example, for multinomial values like 1, 2 and 3,\n \
11067: build V1=0 V2=0 for the reference value (1),\n \
11068: V1=1 V2=0 for (2) \n \
1.136 brouard 11069: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11070: output of IMaCh is often meaningless.\n \
1.136 brouard 11071: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11072: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11073: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11074: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11075: For example, for multinomial values like 1, 2 and 3,\n \
11076: build V1=0 V2=0 for the reference value (1),\n \
11077: V1=1 V2=0 for (2) \n \
1.136 brouard 11078: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11079: output of IMaCh is often meaningless.\n \
1.136 brouard 11080: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11081: return 1;
1.136 brouard 11082: }
11083: covar[j][i]=(double)(lval);
11084: strcpy(line,stra);
11085: }
11086: lstra=strlen(stra);
1.225 brouard 11087:
1.136 brouard 11088: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11089: stratrunc = &(stra[lstra-9]);
11090: num[i]=atol(stratrunc);
11091: }
11092: else
11093: num[i]=atol(stra);
11094: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11095: 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;}*/
11096:
11097: i=i+1;
11098: } /* End loop reading data */
1.225 brouard 11099:
1.136 brouard 11100: *imax=i-1; /* Number of individuals */
11101: fclose(fic);
1.225 brouard 11102:
1.136 brouard 11103: return (0);
1.164 brouard 11104: /* endread: */
1.225 brouard 11105: printf("Exiting readdata: ");
11106: fclose(fic);
11107: return (1);
1.223 brouard 11108: }
1.126 brouard 11109:
1.234 brouard 11110: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11111: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11112: while (*p2 == ' ')
1.234 brouard 11113: p2++;
11114: /* while ((*p1++ = *p2++) !=0) */
11115: /* ; */
11116: /* do */
11117: /* while (*p2 == ' ') */
11118: /* p2++; */
11119: /* while (*p1++ == *p2++); */
11120: *stri=p2;
1.145 brouard 11121: }
11122:
1.330 brouard 11123: int decoderesult( char resultline[], int nres)
1.230 brouard 11124: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11125: {
1.235 brouard 11126: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11127: char resultsav[MAXLINE];
1.330 brouard 11128: /* int resultmodel[MAXLINE]; */
1.334 brouard 11129: /* int modelresult[MAXLINE]; */
1.230 brouard 11130: char stra[80], strb[80], strc[80], strd[80],stre[80];
11131:
1.234 brouard 11132: removefirstspace(&resultline);
1.332 brouard 11133: printf("decoderesult:%s\n",resultline);
1.230 brouard 11134:
1.332 brouard 11135: strcpy(resultsav,resultline);
1.342 brouard 11136: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11137: if (strlen(resultsav) >1){
1.334 brouard 11138: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11139: }
1.353 brouard 11140: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 11141: TKresult[nres]=0; /* Combination for the nresult and the model */
11142: return (0);
11143: }
1.234 brouard 11144: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 brouard 11145: 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);
11146: 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);
11147: if(j==0)
11148: return 1;
1.234 brouard 11149: }
1.334 brouard 11150: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11151: if(nbocc(resultsav,'=') >1){
1.318 brouard 11152: 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 11153: /* 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 11154: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11155: /* If a blank, then strc="V4=" and strd='\0' */
11156: if(strc[0]=='\0'){
11157: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11158: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11159: return 1;
11160: }
1.234 brouard 11161: }else
11162: cutl(strc,strd,resultsav,'=');
1.318 brouard 11163: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11164:
1.230 brouard 11165: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11166: 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 11167: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11168: /* cptcovsel++; */
11169: if (nbocc(stra,'=') >0)
11170: strcpy(resultsav,stra); /* and analyzes it */
11171: }
1.235 brouard 11172: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11173: /* 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 11174: 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 11175: if(Typevar[k1]==0){ /* Single covariate in model */
11176: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11177: match=0;
1.318 brouard 11178: for(k2=1; k2 <=j;k2++){/* Loop on resultline. 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;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11181: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11182: break;
11183: }
11184: }
11185: if(match == 0){
1.338 brouard 11186: 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]);
11187: 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 11188: return 1;
1.234 brouard 11189: }
1.332 brouard 11190: }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*/
11191: /* We feed resultmodel[k1]=k2; */
11192: match=0;
11193: 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 */
11194: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11195: 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 11196: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11197: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11198: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11199: break;
11200: }
11201: }
11202: if(match == 0){
1.338 brouard 11203: 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]);
11204: 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 11205: return 1;
11206: }
1.349 brouard 11207: }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 11208: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11209: match=0;
1.342 brouard 11210: /* 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 11211: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11212: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11213: /* modelresult[k2]=k1; */
1.342 brouard 11214: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11215: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11216: }
11217: }
11218: if(match == 0){
1.349 brouard 11219: 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);
11220: 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 11221: return 1;
11222: }
11223: match=0;
11224: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11225: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11226: /* modelresult[k2]=k1;*/
1.342 brouard 11227: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11228: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11229: break;
11230: }
11231: }
11232: if(match == 0){
1.349 brouard 11233: 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);
11234: 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 11235: return 1;
11236: }
11237: }/* End of testing */
1.333 brouard 11238: }/* End loop cptcovt */
1.235 brouard 11239: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11240: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11241: 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)
11242: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11243: match=0;
1.318 brouard 11244: 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 11245: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 11246: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11247: 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 11248: 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 11249: ++match;
11250: }
11251: }
11252: }
11253: if(match == 0){
1.338 brouard 11254: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11255: 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 11256: return 1;
1.234 brouard 11257: }else if(match > 1){
1.338 brouard 11258: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11259: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11260: return 1;
1.234 brouard 11261: }
11262: }
1.334 brouard 11263: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11264: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11265: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11266: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11267: /* 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*/
11268: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11269: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11270: /* 1 0 0 0 */
11271: /* 2 1 0 0 */
11272: /* 3 0 1 0 */
1.330 brouard 11273: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11274: /* 5 0 0 1 */
1.330 brouard 11275: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11276: /* 7 0 1 1 */
11277: /* 8 1 1 1 */
1.237 brouard 11278: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11279: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11280: /* V5*age V5 known which value for nres? */
11281: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11282: 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.
11283: * loop on position k1 in the MODEL LINE */
1.331 brouard 11284: /* k counting number of combination of single dummies in the equation model */
11285: /* k4 counting single dummies in the equation model */
11286: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11287: 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 11288: /* 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 11289: /* 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 11290: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11291: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11292: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11293: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11294: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11295: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11296: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11297: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11298: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11299: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11300: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11301: 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 11302: 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 11303: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11304: /* Tinvresult[nres][4]=1 */
1.334 brouard 11305: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11306: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11307: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11308: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11309: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11310: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11311: /* 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 11312: k4++;;
1.331 brouard 11313: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11314: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11315: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11316: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11317: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11318: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11319: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11320: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11321: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11322: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11323: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11324: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11325: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11326: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11327: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11328: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11329: /* 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 11330: k4q++;;
1.350 brouard 11331: }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"*/
11332: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 11333: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 11334: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11335: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11336: /* 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]]); */
11337: }else{
11338: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11339: 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)*/
11340: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
11341: precov[nres][k1]=Tvalsel[k3];
11342: }
1.342 brouard 11343: /* 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 11344: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 11345: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11346: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11347: /* 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]]); */
11348: }else{
11349: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
11350: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
11351: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
11352: precov[nres][k1]=Tvalsel[k3q];
11353: }
1.342 brouard 11354: /* 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 11355: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11356: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11357: /* 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 11358: }else{
1.332 brouard 11359: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11360: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11361: }
11362: }
1.234 brouard 11363:
1.334 brouard 11364: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11365: return (0);
11366: }
1.235 brouard 11367:
1.230 brouard 11368: int decodemodel( char model[], int lastobs)
11369: /**< This routine decodes the model and returns:
1.224 brouard 11370: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11371: * - nagesqr = 1 if age*age in the model, otherwise 0.
11372: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11373: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11374: * - cptcovage number of covariates with age*products =2
11375: * - cptcovs number of simple covariates
1.339 brouard 11376: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11377: * - 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 11378: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11379: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11380: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11381: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11382: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11383: */
1.319 brouard 11384: /* 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 11385: {
1.238 brouard 11386: int i, j, k, ks, v;
1.349 brouard 11387: int n,m;
11388: int j1, k1, k11, k12, k2, k3, k4;
11389: char modelsav[300];
11390: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11391: char *strpt;
1.349 brouard 11392: int **existcomb;
11393:
11394: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
11395: for(i=1;i<=NCOVMAX;i++)
11396: for(j=1;j<=NCOVMAX;j++)
11397: existcomb[i][j]=0;
11398:
1.145 brouard 11399: /*removespace(model);*/
1.136 brouard 11400: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 11401: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11402: if (strstr(model,"AGE") !=0){
1.192 brouard 11403: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11404: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11405: return 1;
11406: }
1.141 brouard 11407: if (strstr(model,"v") !=0){
1.338 brouard 11408: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11409: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11410: return 1;
11411: }
1.187 brouard 11412: strcpy(modelsav,model);
11413: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11414: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11415: if(strpt != model){
1.338 brouard 11416: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11417: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11418: corresponding column of parameters.\n",model);
1.338 brouard 11419: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11420: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11421: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11422: return 1;
1.225 brouard 11423: }
1.187 brouard 11424: nagesqr=1;
11425: if (strstr(model,"+age*age") !=0)
1.234 brouard 11426: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11427: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11428: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11429: else
1.234 brouard 11430: substrchaine(modelsav, model, "age*age");
1.187 brouard 11431: }else
11432: nagesqr=0;
1.349 brouard 11433: 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 11434: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11435: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 11436: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 11437: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11438: * cst, age and age*age
11439: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11440: /* including age products which are counted in cptcovage.
11441: * but the covariates which are products must be treated
11442: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 11443: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
11444: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11445: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 11446: cptcovprodage=0;
11447: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11448:
1.187 brouard 11449: /* Design
11450: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11451: * < ncovcol=8 >
11452: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11453: * k= 1 2 3 4 5 6 7 8
11454: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11455: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11456: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11457: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11458: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11459: * Tage[++cptcovage]=k
1.345 brouard 11460: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11461: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11462: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11463: * 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
11464: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11465: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11466: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11467: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11468: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11469: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11470: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11471: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11472: * p Tprod[1]@2={ 6, 5}
11473: *p Tvard[1][1]@4= {7, 8, 5, 6}
11474: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11475: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11476: *How to reorganize? Tvars(orted)
1.187 brouard 11477: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11478: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11479: * {2, 1, 4, 8, 5, 6, 3, 7}
11480: * Struct []
11481: */
1.225 brouard 11482:
1.187 brouard 11483: /* This loop fills the array Tvar from the string 'model'.*/
11484: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11485: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11486: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11487: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11488: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11489: /* k=1 Tvar[1]=2 (from V2) */
11490: /* k=5 Tvar[5] */
11491: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11492: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11493: /* } */
1.198 brouard 11494: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11495: /*
11496: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11497: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11498: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11499: }
1.187 brouard 11500: cptcovage=0;
1.351 brouard 11501:
11502: /* First loop in order to calculate */
11503: /* for age*VN*Vm
11504: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
11505: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
11506: */
11507: /* Needs FixedV[Tvardk[k][1]] */
11508: /* For others:
11509: * Sets Typevar[k];
11510: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11511: * Tposprod[k]=k11;
11512: * Tprod[k11]=k;
11513: * Tvardk[k][1] =m;
11514: * Needs FixedV[Tvardk[k][1]] == 0
11515: */
11516:
1.319 brouard 11517: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11518: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11519: 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" */
11520: if (nbocc(modelsav,'+')==0)
11521: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11522: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11523: /*scanf("%d",i);*/
1.349 brouard 11524: 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 */
11525: 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 */
11526: 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 */
11527: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
11528: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
11529: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
11530: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
11531: /* We want strb=Vn*Vm */
11532: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
11533: strcpy(strb,strd);
11534: strcat(strb,"*");
11535: strcat(strb,stre);
11536: }else{ /* strf=Vm If strf=V6 then stre=V2 */
11537: strcpy(strb,strf);
11538: strcat(strb,"*");
11539: strcat(strb,stre);
11540: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
11541: }
1.351 brouard 11542: /* 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]]]); */
11543: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 11544: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
11545: strcpy(stre,strb); /* save full b in stre */
11546: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
11547: strcpy(strf,strc); /* save short c in new short f */
11548: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
11549: /* strcpy(strc,stre);*/ /* save full e in c for future */
11550: }
11551: cptcovdageprod++; /* double product with age Which product is it? */
11552: /* 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 *\/ */
11553: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11554: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 11555: n=atoi(stre);
1.234 brouard 11556: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 11557: m=atoi(strc);
11558: cptcovage++; /* Counts the number of covariates which include age as a product */
11559: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
11560: if(existcomb[n][m] == 0){
11561: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
11562: 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);
11563: 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);
11564: fflush(ficlog);
11565: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
11566: k12++;
11567: existcomb[n][m]=k1;
11568: existcomb[m][n]=k1;
11569: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
11570: 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*/
11571: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
11572: Tvard[k1][1] =m; /* m 1 for V1*/
11573: Tvardk[k][1] =m; /* m 1 for V1*/
11574: Tvard[k1][2] =n; /* n 4 for V4*/
11575: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 11576: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 11577: 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 */
11578: for (i=1; i<=lastobs;i++){/* For fixed product */
11579: /* Computes the new covariate which is a product of
11580: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11581: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11582: }
11583: cptcovprodage++; /* Counting the number of fixed covariate with age */
11584: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11585: k12++;
11586: FixedV[ncovcolt+k12]=0;
11587: }else{ /*End of FixedV */
11588: cptcovprodvage++; /* Counting the number of varying covariate with age */
11589: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11590: k12++;
11591: FixedV[ncovcolt+k12]=1;
11592: }
11593: }else{ /* k1 Vn*Vm already exists */
11594: k11=existcomb[n][m];
11595: Tposprod[k]=k11; /* OK */
11596: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
11597: Tvardk[k][1]=m;
11598: Tvardk[k][2]=n;
11599: 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 */
11600: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11601: cptcovprodage++; /* Counting the number of fixed covariate with age */
11602: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11603: Tvar[Tage[cptcovage]]=k1;
11604: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11605: k12++;
11606: FixedV[ncovcolt+k12]=0;
11607: }else{ /* Already exists but time varying (and age) */
11608: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11609: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11610: /* Tvar[Tage[cptcovage]]=k1; */
11611: cptcovprodvage++;
11612: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11613: k12++;
11614: FixedV[ncovcolt+k12]=1;
11615: }
11616: }
11617: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
11618: /* Tvar[k]=k11; /\* HERY *\/ */
11619: } 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 */
11620: cptcovprod++;
11621: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
11622: /* covar is not filled and then is empty */
11623: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
11624: 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 */
11625: Typevar[k]=1; /* 1 for age product */
11626: cptcovage++; /* Counts the number of covariates which include age as a product */
11627: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
11628: if( FixedV[Tvar[k]] == 0){
11629: cptcovprodage++; /* Counting the number of fixed covariate with age */
11630: }else{
11631: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
11632: }
11633: /*printf("stre=%s ", stre);*/
11634: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
11635: cutl(stre,strb,strc,'V');
11636: Tvar[k]=atoi(stre);
11637: Typevar[k]=1; /* 1 for age product */
11638: cptcovage++;
11639: Tage[cptcovage]=k;
11640: if( FixedV[Tvar[k]] == 0){
11641: cptcovprodage++; /* Counting the number of fixed covariate with age */
11642: }else{
11643: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11644: }
1.349 brouard 11645: }else{ /* for product Vn*Vm */
11646: Typevar[k]=2; /* 2 for product Vn*Vm */
11647: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
11648: n=atoi(stre);
11649: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11650: m=atoi(strc);
11651: k1++;
11652: cptcovprodnoage++;
11653: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
11654: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11655: 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]);
11656: fflush(ficlog);
11657: k11=existcomb[n][m];
11658: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11659: Tposprod[k]=k11;
11660: Tprod[k11]=k;
11661: Tvardk[k][1] =m; /* m 1 for V1*/
11662: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
11663: Tvardk[k][2] =n; /* n 4 for V4*/
11664: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
11665: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
11666: existcomb[n][m]=k1;
11667: existcomb[m][n]=k1;
11668: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
11669: because this model-covariate is a construction we invent a new column
11670: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
11671: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
11672: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
11673: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
11674: /* Please remark that the new variables are model dependent */
11675: /* If we have 4 variable but the model uses only 3, like in
11676: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11677: * k= 1 2 3 4 5 6 7 8
11678: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11679: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11680: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11681: */
11682: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
11683: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
11684: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
11685: Tvard[k1][1] =m; /* m 1 for V1*/
11686: Tvardk[k][1] =m; /* m 1 for V1*/
11687: Tvard[k1][2] =n; /* n 4 for V4*/
11688: Tvardk[k][2] =n; /* n 4 for V4*/
11689: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11690: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11691: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
11692: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
11693: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
11694: 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 */
11695: for (i=1; i<=lastobs;i++){/* For fixed product */
11696: /* Computes the new covariate which is a product of
11697: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11698: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11699: }
11700: /* TvarVV[k2]=n; */
11701: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11702: /* TvarVV[k2+1]=m; */
11703: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11704: }else{ /* not FixedV */
11705: /* TvarVV[k2]=n; */
11706: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11707: /* TvarVV[k2+1]=m; */
11708: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11709: }
11710: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
11711: } /* End of product Vn*Vm */
11712: } /* End of age*double product or simple product */
11713: }else { /* not a product */
1.234 brouard 11714: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11715: /* scanf("%d",i);*/
11716: cutl(strd,strc,strb,'V');
11717: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11718: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11719: Tvar[k]=atoi(strd);
11720: Typevar[k]=0; /* 0 for simple covariates */
11721: }
11722: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11723: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11724: scanf("%d",i);*/
1.187 brouard 11725: } /* end of loop + on total covariates */
1.351 brouard 11726:
11727:
1.187 brouard 11728: } /* end if strlen(modelsave == 0) age*age might exist */
11729: } /* end if strlen(model == 0) */
1.349 brouard 11730: 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 */
11731:
1.136 brouard 11732: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11733: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11734:
1.136 brouard 11735: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11736: printf("cptcovprod=%d ", cptcovprod);
11737: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11738: scanf("%d ",i);*/
11739:
11740:
1.230 brouard 11741: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11742: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11743: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11744: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11745: k = 1 2 3 4 5 6 7 8 9
11746: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11747: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11748: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11749: Dummy[k] 1 0 0 0 3 1 1 2 3
11750: Tmodelind[combination of covar]=k;
1.225 brouard 11751: */
11752: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11753: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11754: /* 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 11755: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11756: printf("Model=1+age+%s\n\
1.349 brouard 11757: 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 11758: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11759: 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 11760: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 11761: 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 11762: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11763: 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 11764: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11765: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 11766:
11767:
11768: /* Second loop for calculating Fixed[k], Dummy[k]*/
11769:
11770:
1.349 brouard 11771: 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 11772: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11773: Fixed[k]= 0;
11774: Dummy[k]= 0;
1.225 brouard 11775: ncoveff++;
1.232 brouard 11776: ncovf++;
1.234 brouard 11777: nsd++;
11778: modell[k].maintype= FTYPE;
11779: TvarsD[nsd]=Tvar[k];
11780: TvarsDind[nsd]=k;
1.330 brouard 11781: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11782: TvarF[ncovf]=Tvar[k];
11783: TvarFind[ncovf]=k;
11784: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11785: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11786: /* }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 11787: }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 11788: Fixed[k]= 0;
11789: Dummy[k]= 1;
1.230 brouard 11790: nqfveff++;
1.234 brouard 11791: modell[k].maintype= FTYPE;
11792: modell[k].subtype= FQ;
11793: nsq++;
1.334 brouard 11794: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11795: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11796: ncovf++;
1.234 brouard 11797: TvarF[ncovf]=Tvar[k];
11798: TvarFind[ncovf]=k;
1.231 brouard 11799: 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 11800: 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 11801: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11802: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11803: /* model V1+V3+age*V1+age*V3+V1*V3 */
11804: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11805: ncovvt++;
11806: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11807: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11808:
1.227 brouard 11809: Fixed[k]= 1;
11810: Dummy[k]= 0;
1.225 brouard 11811: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11812: modell[k].maintype= VTYPE;
11813: modell[k].subtype= VD;
11814: nsd++;
11815: TvarsD[nsd]=Tvar[k];
11816: TvarsDind[nsd]=k;
1.330 brouard 11817: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11818: ncovv++; /* Only simple time varying variables */
11819: TvarV[ncovv]=Tvar[k];
1.242 brouard 11820: 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 11821: 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 */
11822: 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 11823: 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);
11824: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11825: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11826: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11827: /* model V1+V3+age*V1+age*V3+V1*V3 */
11828: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11829: ncovvt++;
11830: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11831: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11832:
1.234 brouard 11833: Fixed[k]= 1;
11834: Dummy[k]= 1;
11835: nqtveff++;
11836: modell[k].maintype= VTYPE;
11837: modell[k].subtype= VQ;
11838: ncovv++; /* Only simple time varying variables */
11839: nsq++;
1.334 brouard 11840: 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) */
11841: 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 11842: TvarV[ncovv]=Tvar[k];
1.242 brouard 11843: 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 11844: 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 */
11845: 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 11846: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11847: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 11848: /* 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 11849: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11850: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11851: ncova++;
11852: TvarA[ncova]=Tvar[k];
11853: TvarAind[ncova]=k;
1.349 brouard 11854: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11855: /** 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 11856: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11857: Fixed[k]= 2;
11858: Dummy[k]= 2;
11859: modell[k].maintype= ATYPE;
11860: modell[k].subtype= APFD;
1.349 brouard 11861: ncovta++;
11862: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
11863: TvarAVVAind[ncovta]=k;
1.240 brouard 11864: /* ncoveff++; */
1.227 brouard 11865: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11866: Fixed[k]= 2;
11867: Dummy[k]= 3;
11868: modell[k].maintype= ATYPE;
11869: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 11870: ncovta++;
11871: TvarAVVA[ncovta]=Tvar[k]; /* */
11872: TvarAVVAind[ncovta]=k;
1.240 brouard 11873: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11874: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11875: Fixed[k]= 3;
11876: Dummy[k]= 2;
11877: modell[k].maintype= ATYPE;
11878: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 11879: ncovva++;
11880: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11881: TvarVVAind[ncovva]=k;
11882: ncovta++;
11883: TvarAVVA[ncovta]=Tvar[k]; /* */
11884: TvarAVVAind[ncovta]=k;
1.240 brouard 11885: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11886: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11887: Fixed[k]= 3;
11888: Dummy[k]= 3;
11889: modell[k].maintype= ATYPE;
11890: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 11891: ncovva++;
11892: TvarVVA[ncovva]=Tvar[k]; /* */
11893: TvarVVAind[ncovva]=k;
11894: ncovta++;
11895: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11896: TvarAVVAind[ncovta]=k;
1.240 brouard 11897: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11898: }
1.349 brouard 11899: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
11900: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
11901: 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 */
11902: 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]]);
11903: Fixed[k]= 0;
11904: Dummy[k]= 0;
11905: ncoveff++;
11906: ncovf++;
11907: /* ncovv++; */
11908: /* TvarVV[ncovv]=Tvardk[k][1]; */
11909: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11910: /* ncovv++; */
11911: /* TvarVV[ncovv]=Tvardk[k][2]; */
11912: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11913: modell[k].maintype= FTYPE;
11914: TvarF[ncovf]=Tvar[k];
11915: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
11916: TvarFind[ncovf]=k;
11917: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11918: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11919: }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 */
11920: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11921: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11922: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11923: 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 */
11924: ncovvt++;
11925: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11926: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11927: ncovvt++;
11928: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11929: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11930:
11931: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11932: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
11933:
11934: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11935: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
11936: Fixed[k]= 1;
11937: Dummy[k]= 0;
11938: modell[k].maintype= FTYPE;
11939: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11940: ncovf++; /* Fixed variables without age */
11941: TvarF[ncovf]=Tvar[k];
11942: TvarFind[ncovf]=k;
11943: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11944: Fixed[k]= 0; /* Fixed product */
11945: Dummy[k]= 1;
11946: modell[k].maintype= FTYPE;
11947: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11948: ncovf++; /* Varying variables without age */
11949: TvarF[ncovf]=Tvar[k];
11950: TvarFind[ncovf]=k;
11951: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
11952: Fixed[k]= 1;
11953: Dummy[k]= 0;
11954: modell[k].maintype= VTYPE;
11955: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11956: ncovv++; /* Varying variables without age */
11957: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11958: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11959: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
11960: Fixed[k]= 1;
11961: Dummy[k]= 1;
11962: modell[k].maintype= VTYPE;
11963: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11964: ncovv++; /* Varying variables without age */
11965: TvarV[ncovv]=Tvar[k];
11966: TvarVind[ncovv]=k;
11967: }
11968: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11969: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11970: Fixed[k]= 0; /* Fixed product */
11971: Dummy[k]= 1;
11972: modell[k].maintype= FTYPE;
11973: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11974: ncovf++; /* Fixed variables without age */
11975: TvarF[ncovf]=Tvar[k];
11976: TvarFind[ncovf]=k;
11977: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
11978: Fixed[k]= 1;
11979: Dummy[k]= 1;
11980: modell[k].maintype= VTYPE;
11981: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11982: ncovv++; /* Varying variables without age */
11983: TvarV[ncovv]=Tvar[k];
11984: TvarVind[ncovv]=k;
11985: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
11986: Fixed[k]= 1;
11987: Dummy[k]= 1;
11988: modell[k].maintype= VTYPE;
11989: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11990: ncovv++; /* Varying variables without age */
11991: TvarV[ncovv]=Tvar[k];
11992: TvarVind[ncovv]=k;
11993: ncovv++; /* Varying variables without age */
11994: TvarV[ncovv]=Tvar[k];
11995: TvarVind[ncovv]=k;
11996: }
11997: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
11998: if(Tvard[k1][2] <=ncovcol){
11999: Fixed[k]= 1;
12000: Dummy[k]= 1;
12001: modell[k].maintype= VTYPE;
12002: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
12003: ncovv++; /* Varying variables without age */
12004: TvarV[ncovv]=Tvar[k];
12005: TvarVind[ncovv]=k;
12006: }else if(Tvard[k1][2] <=ncovcol+nqv){
12007: Fixed[k]= 1;
12008: Dummy[k]= 1;
12009: modell[k].maintype= VTYPE;
12010: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
12011: ncovv++; /* Varying variables without age */
12012: TvarV[ncovv]=Tvar[k];
12013: TvarVind[ncovv]=k;
12014: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12015: Fixed[k]= 1;
12016: Dummy[k]= 0;
12017: modell[k].maintype= VTYPE;
12018: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
12019: ncovv++; /* Varying variables without age */
12020: TvarV[ncovv]=Tvar[k];
12021: TvarVind[ncovv]=k;
12022: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12023: Fixed[k]= 1;
12024: Dummy[k]= 1;
12025: modell[k].maintype= VTYPE;
12026: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
12027: ncovv++; /* Varying variables without age */
12028: TvarV[ncovv]=Tvar[k];
12029: TvarVind[ncovv]=k;
12030: }
12031: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
12032: if(Tvard[k1][2] <=ncovcol){
12033: Fixed[k]= 1;
12034: Dummy[k]= 1;
12035: modell[k].maintype= VTYPE;
12036: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
12037: ncovv++; /* Varying variables without age */
12038: TvarV[ncovv]=Tvar[k];
12039: TvarVind[ncovv]=k;
12040: }else if(Tvard[k1][2] <=ncovcol+nqv){
12041: Fixed[k]= 1;
12042: Dummy[k]= 1;
12043: modell[k].maintype= VTYPE;
12044: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
12045: ncovv++; /* Varying variables without age */
12046: TvarV[ncovv]=Tvar[k];
12047: TvarVind[ncovv]=k;
12048: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12049: Fixed[k]= 1;
12050: Dummy[k]= 1;
12051: modell[k].maintype= VTYPE;
12052: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
12053: ncovv++; /* Varying variables without age */
12054: TvarV[ncovv]=Tvar[k];
12055: TvarVind[ncovv]=k;
12056: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12057: Fixed[k]= 1;
12058: Dummy[k]= 1;
12059: modell[k].maintype= VTYPE;
12060: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
12061: ncovv++; /* Varying variables without age */
12062: TvarV[ncovv]=Tvar[k];
12063: TvarVind[ncovv]=k;
12064: }
12065: }else{
12066: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12067: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12068: } /*end k1*/
12069: }
12070: }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 12071: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 12072: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
12073: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
12074: 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 */
12075: ncova++;
12076: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
12077: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
12078: ncova++;
12079: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
12080: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 12081:
1.349 brouard 12082: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
12083: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
12084: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
12085: ncovta++;
12086: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12087: TvarAVVAind[ncovta]=k;
12088: ncovta++;
12089: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12090: TvarAVVAind[ncovta]=k;
12091: }else{
12092: ncovva++; /* HERY reached */
12093: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12094: TvarVVAind[ncovva]=k;
12095: ncovva++;
12096: TvarVVA[ncovva]=Tvard[k1][2]; /* */
12097: TvarVVAind[ncovva]=k;
12098: ncovta++;
12099: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12100: TvarAVVAind[ncovta]=k;
12101: ncovta++;
12102: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12103: TvarAVVAind[ncovta]=k;
12104: }
1.339 brouard 12105: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12106: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 12107: Fixed[k]= 2;
12108: Dummy[k]= 2;
1.240 brouard 12109: modell[k].maintype= FTYPE;
12110: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 12111: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
12112: /* TvarFind[ncova]=k; */
1.339 brouard 12113: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 12114: Fixed[k]= 2; /* Fixed product */
12115: Dummy[k]= 3;
1.240 brouard 12116: modell[k].maintype= FTYPE;
12117: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 12118: /* TvarF[ncova]=Tvar[k]; */
12119: /* TvarFind[ncova]=k; */
1.339 brouard 12120: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 12121: Fixed[k]= 3;
12122: Dummy[k]= 2;
1.240 brouard 12123: modell[k].maintype= VTYPE;
12124: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 12125: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
12126: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12127: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 12128: Fixed[k]= 3;
12129: Dummy[k]= 3;
1.240 brouard 12130: modell[k].maintype= VTYPE;
12131: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 12132: /* ncovv++; /\* Varying variables without age *\/ */
12133: /* TvarV[ncovv]=Tvar[k]; */
12134: /* TvarVind[ncovv]=k; */
1.240 brouard 12135: }
1.339 brouard 12136: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12137: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 12138: Fixed[k]= 2; /* Fixed product */
12139: Dummy[k]= 2;
1.240 brouard 12140: modell[k].maintype= FTYPE;
12141: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 12142: /* ncova++; /\* Fixed variables with age *\/ */
12143: /* TvarF[ncovf]=Tvar[k]; */
12144: /* TvarFind[ncovf]=k; */
1.339 brouard 12145: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 12146: Fixed[k]= 2;
12147: Dummy[k]= 3;
1.240 brouard 12148: modell[k].maintype= VTYPE;
12149: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 12150: /* ncova++; /\* Varying variables with age *\/ */
12151: /* TvarV[ncova]=Tvar[k]; */
12152: /* TvarVind[ncova]=k; */
1.339 brouard 12153: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 12154: Fixed[k]= 3;
12155: Dummy[k]= 2;
1.240 brouard 12156: modell[k].maintype= VTYPE;
12157: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 12158: ncova++; /* Varying variables without age */
12159: TvarV[ncova]=Tvar[k];
12160: TvarVind[ncova]=k;
12161: /* ncova++; /\* Varying variables without age *\/ */
12162: /* TvarV[ncova]=Tvar[k]; */
12163: /* TvarVind[ncova]=k; */
1.240 brouard 12164: }
1.339 brouard 12165: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12166: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12167: Fixed[k]= 2;
12168: Dummy[k]= 2;
1.240 brouard 12169: modell[k].maintype= VTYPE;
12170: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 12171: /* ncova++; /\* Varying variables with age *\/ */
12172: /* TvarV[ncova]=Tvar[k]; */
12173: /* TvarVind[ncova]=k; */
1.240 brouard 12174: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12175: Fixed[k]= 2;
12176: Dummy[k]= 3;
1.240 brouard 12177: modell[k].maintype= VTYPE;
12178: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 12179: /* ncova++; /\* Varying variables with age *\/ */
12180: /* TvarV[ncova]=Tvar[k]; */
12181: /* TvarVind[ncova]=k; */
1.240 brouard 12182: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12183: Fixed[k]= 3;
12184: Dummy[k]= 2;
1.240 brouard 12185: modell[k].maintype= VTYPE;
12186: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 12187: /* ncova++; /\* Varying variables with age *\/ */
12188: /* TvarV[ncova]=Tvar[k]; */
12189: /* TvarVind[ncova]=k; */
1.240 brouard 12190: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12191: Fixed[k]= 3;
12192: Dummy[k]= 3;
1.240 brouard 12193: modell[k].maintype= VTYPE;
12194: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 12195: /* ncova++; /\* Varying variables with age *\/ */
12196: /* TvarV[ncova]=Tvar[k]; */
12197: /* TvarVind[ncova]=k; */
1.240 brouard 12198: }
1.339 brouard 12199: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12200: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12201: Fixed[k]= 2;
12202: Dummy[k]= 2;
1.240 brouard 12203: modell[k].maintype= VTYPE;
12204: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 12205: /* ncova++; /\* Varying variables with age *\/ */
12206: /* TvarV[ncova]=Tvar[k]; */
12207: /* TvarVind[ncova]=k; */
1.240 brouard 12208: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12209: Fixed[k]= 2;
12210: Dummy[k]= 3;
1.240 brouard 12211: modell[k].maintype= VTYPE;
12212: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 12213: /* ncova++; /\* Varying variables with age *\/ */
12214: /* TvarV[ncova]=Tvar[k]; */
12215: /* TvarVind[ncova]=k; */
1.240 brouard 12216: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12217: Fixed[k]= 3;
12218: Dummy[k]= 2;
1.240 brouard 12219: modell[k].maintype= VTYPE;
12220: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 12221: /* ncova++; /\* Varying variables with age *\/ */
12222: /* TvarV[ncova]=Tvar[k]; */
12223: /* TvarVind[ncova]=k; */
1.240 brouard 12224: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12225: Fixed[k]= 3;
12226: Dummy[k]= 3;
1.240 brouard 12227: modell[k].maintype= VTYPE;
12228: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 12229: /* ncova++; /\* Varying variables with age *\/ */
12230: /* TvarV[ncova]=Tvar[k]; */
12231: /* TvarVind[ncova]=k; */
1.240 brouard 12232: }
1.227 brouard 12233: }else{
1.240 brouard 12234: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12235: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12236: } /*end k1*/
1.349 brouard 12237: } else{
1.226 brouard 12238: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12239: 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 12240: }
1.342 brouard 12241: /* 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]); */
12242: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12243: 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]);
12244: }
1.349 brouard 12245: ncovvta=ncovva;
1.227 brouard 12246: /* Searching for doublons in the model */
12247: for(k1=1; k1<= cptcovt;k1++){
12248: for(k2=1; k2 <k1;k2++){
1.285 brouard 12249: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12250: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12251: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12252: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12253: 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]);
12254: 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 12255: return(1);
12256: }
12257: }else if (Typevar[k1] ==2){
12258: k3=Tposprod[k1];
12259: k4=Tposprod[k2];
12260: 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 12261: 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]]);
12262: 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 12263: return(1);
12264: }
12265: }
1.227 brouard 12266: }
12267: }
1.225 brouard 12268: }
12269: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12270: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12271: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12272: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 12273:
12274: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12275: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12276: /*endread:*/
1.225 brouard 12277: printf("Exiting decodemodel: ");
12278: return (1);
1.136 brouard 12279: }
12280:
1.169 brouard 12281: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12282: {/* Check ages at death */
1.136 brouard 12283: int i, m;
1.218 brouard 12284: int firstone=0;
12285:
1.136 brouard 12286: for (i=1; i<=imx; i++) {
12287: for(m=2; (m<= maxwav); m++) {
12288: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12289: anint[m][i]=9999;
1.216 brouard 12290: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12291: s[m][i]=-1;
1.136 brouard 12292: }
12293: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12294: *nberr = *nberr + 1;
1.218 brouard 12295: if(firstone == 0){
12296: firstone=1;
1.260 brouard 12297: 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 12298: }
1.262 brouard 12299: 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 12300: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12301: }
12302: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12303: (*nberr)++;
1.259 brouard 12304: 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 12305: 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 12306: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12307: }
12308: }
12309: }
12310:
12311: for (i=1; i<=imx; i++) {
12312: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12313: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12314: 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 12315: if (s[m][i] >= nlstate+1) {
1.169 brouard 12316: if(agedc[i]>0){
12317: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12318: agev[m][i]=agedc[i];
1.214 brouard 12319: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12320: }else {
1.136 brouard 12321: if ((int)andc[i]!=9999){
12322: nbwarn++;
12323: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12324: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12325: agev[m][i]=-1;
12326: }
12327: }
1.169 brouard 12328: } /* agedc > 0 */
1.214 brouard 12329: } /* end if */
1.136 brouard 12330: else if(s[m][i] !=9){ /* Standard case, age in fractional
12331: years but with the precision of a month */
12332: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12333: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12334: agev[m][i]=1;
12335: else if(agev[m][i] < *agemin){
12336: *agemin=agev[m][i];
12337: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12338: }
12339: else if(agev[m][i] >*agemax){
12340: *agemax=agev[m][i];
1.156 brouard 12341: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12342: }
12343: /*agev[m][i]=anint[m][i]-annais[i];*/
12344: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12345: } /* en if 9*/
1.136 brouard 12346: else { /* =9 */
1.214 brouard 12347: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12348: agev[m][i]=1;
12349: s[m][i]=-1;
12350: }
12351: }
1.214 brouard 12352: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12353: agev[m][i]=1;
1.214 brouard 12354: else{
12355: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12356: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12357: agev[m][i]=0;
12358: }
12359: } /* End for lastpass */
12360: }
1.136 brouard 12361:
12362: for (i=1; i<=imx; i++) {
12363: for(m=firstpass; (m<=lastpass); m++){
12364: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12365: (*nberr)++;
1.136 brouard 12366: 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);
12367: 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);
12368: return 1;
12369: }
12370: }
12371: }
12372:
12373: /*for (i=1; i<=imx; i++){
12374: for (m=firstpass; (m<lastpass); m++){
12375: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12376: }
12377:
12378: }*/
12379:
12380:
1.139 brouard 12381: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12382: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12383:
12384: return (0);
1.164 brouard 12385: /* endread:*/
1.136 brouard 12386: printf("Exiting calandcheckages: ");
12387: return (1);
12388: }
12389:
1.172 brouard 12390: #if defined(_MSC_VER)
12391: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12392: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12393: //#include "stdafx.h"
12394: //#include <stdio.h>
12395: //#include <tchar.h>
12396: //#include <windows.h>
12397: //#include <iostream>
12398: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12399:
12400: LPFN_ISWOW64PROCESS fnIsWow64Process;
12401:
12402: BOOL IsWow64()
12403: {
12404: BOOL bIsWow64 = FALSE;
12405:
12406: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12407: // (HANDLE, PBOOL);
12408:
12409: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12410:
12411: HMODULE module = GetModuleHandle(_T("kernel32"));
12412: const char funcName[] = "IsWow64Process";
12413: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12414: GetProcAddress(module, funcName);
12415:
12416: if (NULL != fnIsWow64Process)
12417: {
12418: if (!fnIsWow64Process(GetCurrentProcess(),
12419: &bIsWow64))
12420: //throw std::exception("Unknown error");
12421: printf("Unknown error\n");
12422: }
12423: return bIsWow64 != FALSE;
12424: }
12425: #endif
1.177 brouard 12426:
1.191 brouard 12427: void syscompilerinfo(int logged)
1.292 brouard 12428: {
12429: #include <stdint.h>
12430:
12431: /* #include "syscompilerinfo.h"*/
1.185 brouard 12432: /* command line Intel compiler 32bit windows, XP compatible:*/
12433: /* /GS /W3 /Gy
12434: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12435: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12436: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12437: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12438: */
12439: /* 64 bits */
1.185 brouard 12440: /*
12441: /GS /W3 /Gy
12442: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12443: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12444: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12445: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12446: /* Optimization are useless and O3 is slower than O2 */
12447: /*
12448: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12449: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12450: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12451: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12452: */
1.186 brouard 12453: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12454: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12455: /PDB:"visual studio
12456: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12457: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12458: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12459: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12460: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12461: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12462: uiAccess='false'"
12463: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12464: /NOLOGO /TLBID:1
12465: */
1.292 brouard 12466:
12467:
1.177 brouard 12468: #if defined __INTEL_COMPILER
1.178 brouard 12469: #if defined(__GNUC__)
12470: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12471: #endif
1.177 brouard 12472: #elif defined(__GNUC__)
1.179 brouard 12473: #ifndef __APPLE__
1.174 brouard 12474: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12475: #endif
1.177 brouard 12476: struct utsname sysInfo;
1.178 brouard 12477: int cross = CROSS;
12478: if (cross){
12479: printf("Cross-");
1.191 brouard 12480: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12481: }
1.174 brouard 12482: #endif
12483:
1.191 brouard 12484: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12485: #if defined(__clang__)
1.191 brouard 12486: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12487: #endif
12488: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12489: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12490: #endif
12491: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12492: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12493: #endif
12494: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12495: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12496: #endif
12497: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12498: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12499: #endif
12500: #if defined(_MSC_VER)
1.191 brouard 12501: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12502: #endif
12503: #if defined(__PGI)
1.191 brouard 12504: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12505: #endif
12506: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12507: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12508: #endif
1.191 brouard 12509: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12510:
1.167 brouard 12511: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12512: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12513: // Windows (x64 and x86)
1.191 brouard 12514: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12515: #elif __unix__ // all unices, not all compilers
12516: // Unix
1.191 brouard 12517: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12518: #elif __linux__
12519: // linux
1.191 brouard 12520: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12521: #elif __APPLE__
1.174 brouard 12522: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12523: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12524: #endif
12525:
12526: /* __MINGW32__ */
12527: /* __CYGWIN__ */
12528: /* __MINGW64__ */
12529: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12530: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12531: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12532: /* _WIN64 // Defined for applications for Win64. */
12533: /* _M_X64 // Defined for compilations that target x64 processors. */
12534: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12535:
1.167 brouard 12536: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12537: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12538: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12539: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12540: #else
1.191 brouard 12541: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12542: #endif
12543:
1.169 brouard 12544: #if defined(__GNUC__)
12545: # if defined(__GNUC_PATCHLEVEL__)
12546: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12547: + __GNUC_MINOR__ * 100 \
12548: + __GNUC_PATCHLEVEL__)
12549: # else
12550: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12551: + __GNUC_MINOR__ * 100)
12552: # endif
1.174 brouard 12553: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12554: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12555:
12556: if (uname(&sysInfo) != -1) {
12557: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12558: 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 12559: }
12560: else
12561: perror("uname() error");
1.179 brouard 12562: //#ifndef __INTEL_COMPILER
12563: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12564: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12565: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12566: #endif
1.169 brouard 12567: #endif
1.172 brouard 12568:
1.286 brouard 12569: // void main ()
1.172 brouard 12570: // {
1.169 brouard 12571: #if defined(_MSC_VER)
1.174 brouard 12572: if (IsWow64()){
1.191 brouard 12573: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12574: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12575: }
12576: else{
1.191 brouard 12577: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12578: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12579: }
1.172 brouard 12580: // printf("\nPress Enter to continue...");
12581: // getchar();
12582: // }
12583:
1.169 brouard 12584: #endif
12585:
1.167 brouard 12586:
1.219 brouard 12587: }
1.136 brouard 12588:
1.219 brouard 12589: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12590: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12591: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12592: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12593: /* double ftolpl = 1.e-10; */
1.180 brouard 12594: double age, agebase, agelim;
1.203 brouard 12595: double tot;
1.180 brouard 12596:
1.202 brouard 12597: strcpy(filerespl,"PL_");
12598: strcat(filerespl,fileresu);
12599: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12600: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12601: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12602: }
1.288 brouard 12603: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12604: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12605: pstamp(ficrespl);
1.288 brouard 12606: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12607: fprintf(ficrespl,"#Age ");
12608: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12609: fprintf(ficrespl,"\n");
1.180 brouard 12610:
1.219 brouard 12611: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12612:
1.219 brouard 12613: agebase=ageminpar;
12614: agelim=agemaxpar;
1.180 brouard 12615:
1.227 brouard 12616: /* i1=pow(2,ncoveff); */
1.234 brouard 12617: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12618: if (cptcovn < 1){i1=1;}
1.180 brouard 12619:
1.337 brouard 12620: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12621: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12622: k=TKresult[nres];
1.338 brouard 12623: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12624: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12625: /* continue; */
1.235 brouard 12626:
1.238 brouard 12627: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12628: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12629: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12630: /* k=k+1; */
12631: /* to clean */
1.332 brouard 12632: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12633: fprintf(ficrespl,"#******");
12634: printf("#******");
12635: fprintf(ficlog,"#******");
1.337 brouard 12636: 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 12637: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12638: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12639: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12640: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12641: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12642: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12643: }
12644: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12645: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12646: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12647: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12648: /* } */
1.238 brouard 12649: fprintf(ficrespl,"******\n");
12650: printf("******\n");
12651: fprintf(ficlog,"******\n");
12652: if(invalidvarcomb[k]){
12653: printf("\nCombination (%d) ignored because no case \n",k);
12654: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12655: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12656: continue;
12657: }
1.219 brouard 12658:
1.238 brouard 12659: fprintf(ficrespl,"#Age ");
1.337 brouard 12660: /* for(j=1;j<=cptcoveff;j++) { */
12661: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12662: /* } */
12663: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12664: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12665: }
12666: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12667: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12668:
1.238 brouard 12669: for (age=agebase; age<=agelim; age++){
12670: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12671: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12672: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12673: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12674: /* for(j=1;j<=cptcoveff;j++) */
12675: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12676: for(j=1;j<=cptcovs;j++)
12677: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12678: tot=0.;
12679: for(i=1; i<=nlstate;i++){
12680: tot += prlim[i][i];
12681: fprintf(ficrespl," %.5f", prlim[i][i]);
12682: }
12683: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12684: } /* Age */
12685: /* was end of cptcod */
1.337 brouard 12686: } /* nres */
12687: /* } /\* for each combination *\/ */
1.219 brouard 12688: return 0;
1.180 brouard 12689: }
12690:
1.218 brouard 12691: 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 12692: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12693:
12694: /* Computes the back prevalence limit for any combination of covariate values
12695: * at any age between ageminpar and agemaxpar
12696: */
1.235 brouard 12697: int i, j, k, i1, nres=0 ;
1.217 brouard 12698: /* double ftolpl = 1.e-10; */
12699: double age, agebase, agelim;
12700: double tot;
1.218 brouard 12701: /* double ***mobaverage; */
12702: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12703:
12704: strcpy(fileresplb,"PLB_");
12705: strcat(fileresplb,fileresu);
12706: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12707: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12708: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12709: }
1.288 brouard 12710: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12711: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12712: pstamp(ficresplb);
1.288 brouard 12713: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12714: fprintf(ficresplb,"#Age ");
12715: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12716: fprintf(ficresplb,"\n");
12717:
1.218 brouard 12718:
12719: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12720:
12721: agebase=ageminpar;
12722: agelim=agemaxpar;
12723:
12724:
1.227 brouard 12725: i1=pow(2,cptcoveff);
1.218 brouard 12726: if (cptcovn < 1){i1=1;}
1.227 brouard 12727:
1.238 brouard 12728: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12729: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12730: k=TKresult[nres];
12731: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12732: /* if(i1 != 1 && TKresult[nres]!= k) */
12733: /* continue; */
12734: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12735: fprintf(ficresplb,"#******");
12736: printf("#******");
12737: fprintf(ficlog,"#******");
1.338 brouard 12738: 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) */
12739: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12740: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12741: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12742: }
1.338 brouard 12743: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12744: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12745: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12746: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12747: /* } */
12748: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12749: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12750: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12751: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12752: /* } */
1.238 brouard 12753: fprintf(ficresplb,"******\n");
12754: printf("******\n");
12755: fprintf(ficlog,"******\n");
12756: if(invalidvarcomb[k]){
12757: printf("\nCombination (%d) ignored because no cases \n",k);
12758: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12759: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12760: continue;
12761: }
1.218 brouard 12762:
1.238 brouard 12763: fprintf(ficresplb,"#Age ");
1.338 brouard 12764: for(j=1;j<=cptcovs;j++) {
12765: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12766: }
12767: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12768: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12769:
12770:
1.238 brouard 12771: for (age=agebase; age<=agelim; age++){
12772: /* for (age=agebase; age<=agebase; age++){ */
12773: if(mobilavproj > 0){
12774: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12775: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12776: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12777: }else if (mobilavproj == 0){
12778: 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);
12779: 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);
12780: exit(1);
12781: }else{
12782: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12783: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12784: /* printf("TOTOT\n"); */
12785: /* exit(1); */
1.238 brouard 12786: }
12787: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12788: for(j=1;j<=cptcovs;j++)
12789: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12790: tot=0.;
12791: for(i=1; i<=nlstate;i++){
12792: tot += bprlim[i][i];
12793: fprintf(ficresplb," %.5f", bprlim[i][i]);
12794: }
12795: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12796: } /* Age */
12797: /* was end of cptcod */
1.255 brouard 12798: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12799: /* } /\* end of any combination *\/ */
1.238 brouard 12800: } /* end of nres */
1.218 brouard 12801: /* hBijx(p, bage, fage); */
12802: /* fclose(ficrespijb); */
12803:
12804: return 0;
1.217 brouard 12805: }
1.218 brouard 12806:
1.180 brouard 12807: int hPijx(double *p, int bage, int fage){
12808: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12809: /* to be optimized with precov */
1.180 brouard 12810: int stepsize;
12811: int agelim;
12812: int hstepm;
12813: int nhstepm;
1.235 brouard 12814: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12815:
12816: double agedeb;
12817: double ***p3mat;
12818:
1.337 brouard 12819: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12820: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12821: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12822: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12823: }
12824: printf("Computing pij: result on file '%s' \n", filerespij);
12825: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12826:
12827: stepsize=(int) (stepm+YEARM-1)/YEARM;
12828: /*if (stepm<=24) stepsize=2;*/
12829:
12830: agelim=AGESUP;
12831: hstepm=stepsize*YEARM; /* Every year of age */
12832: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12833:
12834: /* hstepm=1; aff par mois*/
12835: pstamp(ficrespij);
12836: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12837: i1= pow(2,cptcoveff);
12838: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12839: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12840: /* k=k+1; */
12841: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12842: k=TKresult[nres];
1.338 brouard 12843: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12844: /* for(k=1; k<=i1;k++){ */
12845: /* if(i1 != 1 && TKresult[nres]!= k) */
12846: /* continue; */
12847: fprintf(ficrespij,"\n#****** ");
12848: for(j=1;j<=cptcovs;j++){
12849: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12850: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12851: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12852: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12853: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12854: }
12855: fprintf(ficrespij,"******\n");
12856:
12857: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12858: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12859: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12860:
12861: /* nhstepm=nhstepm*YEARM; aff par mois*/
12862:
12863: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12864: oldm=oldms;savm=savms;
12865: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12866: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12867: for(i=1; i<=nlstate;i++)
12868: for(j=1; j<=nlstate+ndeath;j++)
12869: fprintf(ficrespij," %1d-%1d",i,j);
12870: fprintf(ficrespij,"\n");
12871: for (h=0; h<=nhstepm; h++){
12872: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12873: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12874: for(i=1; i<=nlstate;i++)
12875: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12876: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12877: fprintf(ficrespij,"\n");
12878: }
1.337 brouard 12879: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12880: fprintf(ficrespij,"\n");
1.180 brouard 12881: }
1.337 brouard 12882: }
12883: /*}*/
12884: return 0;
1.180 brouard 12885: }
1.218 brouard 12886:
12887: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12888: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12889: /* To be optimized with precov */
1.217 brouard 12890: int stepsize;
1.218 brouard 12891: /* int agelim; */
12892: int ageminl;
1.217 brouard 12893: int hstepm;
12894: int nhstepm;
1.238 brouard 12895: int h, i, i1, j, k, nres;
1.218 brouard 12896:
1.217 brouard 12897: double agedeb;
12898: double ***p3mat;
1.218 brouard 12899:
12900: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12901: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12902: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12903: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12904: }
12905: printf("Computing pij back: result on file '%s' \n", filerespijb);
12906: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12907:
12908: stepsize=(int) (stepm+YEARM-1)/YEARM;
12909: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12910:
1.218 brouard 12911: /* agelim=AGESUP; */
1.289 brouard 12912: ageminl=AGEINF; /* was 30 */
1.218 brouard 12913: hstepm=stepsize*YEARM; /* Every year of age */
12914: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12915:
12916: /* hstepm=1; aff par mois*/
12917: pstamp(ficrespijb);
1.255 brouard 12918: 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 12919: i1= pow(2,cptcoveff);
1.218 brouard 12920: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12921: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12922: /* k=k+1; */
1.238 brouard 12923: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12924: k=TKresult[nres];
1.338 brouard 12925: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12926: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12927: /* if(i1 != 1 && TKresult[nres]!= k) */
12928: /* continue; */
12929: fprintf(ficrespijb,"\n#****** ");
12930: for(j=1;j<=cptcovs;j++){
1.338 brouard 12931: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12932: /* for(j=1;j<=cptcoveff;j++) */
12933: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12934: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12935: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12936: }
12937: fprintf(ficrespijb,"******\n");
12938: if(invalidvarcomb[k]){ /* Is it necessary here? */
12939: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12940: continue;
12941: }
12942:
12943: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12944: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12945: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12946: 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 */
12947: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12948:
12949: /* nhstepm=nhstepm*YEARM; aff par mois*/
12950:
12951: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12952: /* and memory limitations if stepm is small */
12953:
12954: /* oldm=oldms;savm=savms; */
12955: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12956: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12957: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12958: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12959: for(i=1; i<=nlstate;i++)
12960: for(j=1; j<=nlstate+ndeath;j++)
12961: fprintf(ficrespijb," %1d-%1d",i,j);
12962: fprintf(ficrespijb,"\n");
12963: for (h=0; h<=nhstepm; h++){
12964: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12965: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12966: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12967: for(i=1; i<=nlstate;i++)
12968: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12969: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12970: fprintf(ficrespijb,"\n");
1.337 brouard 12971: }
12972: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12973: fprintf(ficrespijb,"\n");
12974: } /* end age deb */
12975: /* } /\* end combination *\/ */
1.238 brouard 12976: } /* end nres */
1.218 brouard 12977: return 0;
12978: } /* hBijx */
1.217 brouard 12979:
1.180 brouard 12980:
1.136 brouard 12981: /***********************************************/
12982: /**************** Main Program *****************/
12983: /***********************************************/
12984:
12985: int main(int argc, char *argv[])
12986: {
12987: #ifdef GSL
12988: const gsl_multimin_fminimizer_type *T;
12989: size_t iteri = 0, it;
12990: int rval = GSL_CONTINUE;
12991: int status = GSL_SUCCESS;
12992: double ssval;
12993: #endif
12994: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12995: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12996: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12997: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12998: int jj, ll, li, lj, lk;
1.136 brouard 12999: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 13000: int num_filled;
1.136 brouard 13001: int itimes;
13002: int NDIM=2;
13003: int vpopbased=0;
1.235 brouard 13004: int nres=0;
1.258 brouard 13005: int endishere=0;
1.277 brouard 13006: int noffset=0;
1.274 brouard 13007: int ncurrv=0; /* Temporary variable */
13008:
1.164 brouard 13009: char ca[32], cb[32];
1.136 brouard 13010: /* FILE *fichtm; *//* Html File */
13011: /* FILE *ficgp;*/ /*Gnuplot File */
13012: struct stat info;
1.191 brouard 13013: double agedeb=0.;
1.194 brouard 13014:
13015: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 13016: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 13017:
1.165 brouard 13018: double fret;
1.191 brouard 13019: double dum=0.; /* Dummy variable */
1.136 brouard 13020: double ***p3mat;
1.218 brouard 13021: /* double ***mobaverage; */
1.319 brouard 13022: double wald;
1.164 brouard 13023:
1.351 brouard 13024: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 13025: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
13026:
1.234 brouard 13027: char modeltemp[MAXLINE];
1.332 brouard 13028: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 13029:
1.136 brouard 13030: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 13031: char *tok, *val; /* pathtot */
1.334 brouard 13032: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 13033: int c, h , cpt, c2;
1.191 brouard 13034: int jl=0;
13035: int i1, j1, jk, stepsize=0;
1.194 brouard 13036: int count=0;
13037:
1.164 brouard 13038: int *tab;
1.136 brouard 13039: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 13040: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
13041: /* double anprojf, mprojf, jprojf; */
13042: /* double jintmean,mintmean,aintmean; */
13043: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13044: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13045: double yrfproj= 10.0; /* Number of years of forward projections */
13046: double yrbproj= 10.0; /* Number of years of backward projections */
13047: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 13048: int mobilav=0,popforecast=0;
1.191 brouard 13049: int hstepm=0, nhstepm=0;
1.136 brouard 13050: int agemortsup;
13051: float sumlpop=0.;
13052: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
13053: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
13054:
1.191 brouard 13055: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 13056: double ftolpl=FTOL;
13057: double **prlim;
1.217 brouard 13058: double **bprlim;
1.317 brouard 13059: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
13060: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 13061: double ***paramstart; /* Matrix of starting parameter values */
13062: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 13063: double **matcov; /* Matrix of covariance */
1.203 brouard 13064: double **hess; /* Hessian matrix */
1.136 brouard 13065: double ***delti3; /* Scale */
13066: double *delti; /* Scale */
13067: double ***eij, ***vareij;
13068: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 13069:
1.136 brouard 13070: double *epj, vepp;
1.164 brouard 13071:
1.273 brouard 13072: double dateprev1, dateprev2;
1.296 brouard 13073: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
13074: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
13075:
1.217 brouard 13076:
1.136 brouard 13077: double **ximort;
1.145 brouard 13078: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 13079: int *dcwave;
13080:
1.164 brouard 13081: char z[1]="c";
1.136 brouard 13082:
13083: /*char *strt;*/
13084: char strtend[80];
1.126 brouard 13085:
1.164 brouard 13086:
1.126 brouard 13087: /* setlocale (LC_ALL, ""); */
13088: /* bindtextdomain (PACKAGE, LOCALEDIR); */
13089: /* textdomain (PACKAGE); */
13090: /* setlocale (LC_CTYPE, ""); */
13091: /* setlocale (LC_MESSAGES, ""); */
13092:
13093: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 13094: rstart_time = time(NULL);
13095: /* (void) gettimeofday(&start_time,&tzp);*/
13096: start_time = *localtime(&rstart_time);
1.126 brouard 13097: curr_time=start_time;
1.157 brouard 13098: /*tml = *localtime(&start_time.tm_sec);*/
13099: /* strcpy(strstart,asctime(&tml)); */
13100: strcpy(strstart,asctime(&start_time));
1.126 brouard 13101:
13102: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13103: /* tp.tm_sec = tp.tm_sec +86400; */
13104: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13105: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13106: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13107: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13108: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13109: /* strt=asctime(&tmg); */
13110: /* printf("Time(after) =%s",strstart); */
13111: /* (void) time (&time_value);
13112: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13113: * tm = *localtime(&time_value);
13114: * strstart=asctime(&tm);
13115: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13116: */
13117:
13118: nberr=0; /* Number of errors and warnings */
13119: nbwarn=0;
1.184 brouard 13120: #ifdef WIN32
13121: _getcwd(pathcd, size);
13122: #else
1.126 brouard 13123: getcwd(pathcd, size);
1.184 brouard 13124: #endif
1.191 brouard 13125: syscompilerinfo(0);
1.196 brouard 13126: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13127: if(argc <=1){
13128: printf("\nEnter the parameter file name: ");
1.205 brouard 13129: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13130: printf("ERROR Empty parameter file name\n");
13131: goto end;
13132: }
1.126 brouard 13133: i=strlen(pathr);
13134: if(pathr[i-1]=='\n')
13135: pathr[i-1]='\0';
1.156 brouard 13136: i=strlen(pathr);
1.205 brouard 13137: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13138: pathr[i-1]='\0';
1.205 brouard 13139: }
13140: i=strlen(pathr);
13141: if( i==0 ){
13142: printf("ERROR Empty parameter file name\n");
13143: goto end;
13144: }
13145: for (tok = pathr; tok != NULL; ){
1.126 brouard 13146: printf("Pathr |%s|\n",pathr);
13147: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13148: printf("val= |%s| pathr=%s\n",val,pathr);
13149: strcpy (pathtot, val);
13150: if(pathr[0] == '\0') break; /* Dirty */
13151: }
13152: }
1.281 brouard 13153: else if (argc<=2){
13154: strcpy(pathtot,argv[1]);
13155: }
1.126 brouard 13156: else{
13157: strcpy(pathtot,argv[1]);
1.281 brouard 13158: strcpy(z,argv[2]);
13159: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13160: }
13161: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13162: /*cygwin_split_path(pathtot,path,optionfile);
13163: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13164: /* cutv(path,optionfile,pathtot,'\\');*/
13165:
13166: /* Split argv[0], imach program to get pathimach */
13167: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13168: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13169: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13170: /* strcpy(pathimach,argv[0]); */
13171: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13172: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13173: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13174: #ifdef WIN32
13175: _chdir(path); /* Can be a relative path */
13176: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13177: #else
1.126 brouard 13178: chdir(path); /* Can be a relative path */
1.184 brouard 13179: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13180: #endif
13181: printf("Current directory %s!\n",pathcd);
1.126 brouard 13182: strcpy(command,"mkdir ");
13183: strcat(command,optionfilefiname);
13184: if((outcmd=system(command)) != 0){
1.169 brouard 13185: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13186: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13187: /* fclose(ficlog); */
13188: /* exit(1); */
13189: }
13190: /* if((imk=mkdir(optionfilefiname))<0){ */
13191: /* perror("mkdir"); */
13192: /* } */
13193:
13194: /*-------- arguments in the command line --------*/
13195:
1.186 brouard 13196: /* Main Log file */
1.126 brouard 13197: strcat(filelog, optionfilefiname);
13198: strcat(filelog,".log"); /* */
13199: if((ficlog=fopen(filelog,"w"))==NULL) {
13200: printf("Problem with logfile %s\n",filelog);
13201: goto end;
13202: }
13203: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13204: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13205: fprintf(ficlog,"\nEnter the parameter file name: \n");
13206: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13207: path=%s \n\
13208: optionfile=%s\n\
13209: optionfilext=%s\n\
1.156 brouard 13210: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13211:
1.197 brouard 13212: syscompilerinfo(1);
1.167 brouard 13213:
1.126 brouard 13214: printf("Local time (at start):%s",strstart);
13215: fprintf(ficlog,"Local time (at start): %s",strstart);
13216: fflush(ficlog);
13217: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13218: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13219:
13220: /* */
13221: strcpy(fileres,"r");
13222: strcat(fileres, optionfilefiname);
1.201 brouard 13223: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13224: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13225: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13226:
1.186 brouard 13227: /* Main ---------arguments file --------*/
1.126 brouard 13228:
13229: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13230: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13231: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13232: fflush(ficlog);
1.149 brouard 13233: /* goto end; */
13234: exit(70);
1.126 brouard 13235: }
13236:
13237: strcpy(filereso,"o");
1.201 brouard 13238: strcat(filereso,fileresu);
1.126 brouard 13239: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13240: printf("Problem with Output resultfile: %s\n", filereso);
13241: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13242: fflush(ficlog);
13243: goto end;
13244: }
1.278 brouard 13245: /*-------- Rewriting parameter file ----------*/
13246: strcpy(rfileres,"r"); /* "Rparameterfile */
13247: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13248: strcat(rfileres,"."); /* */
13249: strcat(rfileres,optionfilext); /* Other files have txt extension */
13250: if((ficres =fopen(rfileres,"w"))==NULL) {
13251: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13252: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13253: fflush(ficlog);
13254: goto end;
13255: }
13256: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13257:
1.278 brouard 13258:
1.126 brouard 13259: /* Reads comments: lines beginning with '#' */
13260: numlinepar=0;
1.277 brouard 13261: /* Is it a BOM UTF-8 Windows file? */
13262: /* First parameter line */
1.197 brouard 13263: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13264: noffset=0;
13265: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13266: {
13267: noffset=noffset+3;
13268: printf("# File is an UTF8 Bom.\n"); // 0xBF
13269: }
1.302 brouard 13270: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13271: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13272: {
13273: noffset=noffset+2;
13274: printf("# File is an UTF16BE BOM file\n");
13275: }
13276: else if( line[0] == 0 && line[1] == 0)
13277: {
13278: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13279: noffset=noffset+4;
13280: printf("# File is an UTF16BE BOM file\n");
13281: }
13282: } else{
13283: ;/*printf(" Not a BOM file\n");*/
13284: }
13285:
1.197 brouard 13286: /* If line starts with a # it is a comment */
1.277 brouard 13287: if (line[noffset] == '#') {
1.197 brouard 13288: numlinepar++;
13289: fputs(line,stdout);
13290: fputs(line,ficparo);
1.278 brouard 13291: fputs(line,ficres);
1.197 brouard 13292: fputs(line,ficlog);
13293: continue;
13294: }else
13295: break;
13296: }
13297: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13298: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13299: if (num_filled != 5) {
13300: printf("Should be 5 parameters\n");
1.283 brouard 13301: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13302: }
1.126 brouard 13303: numlinepar++;
1.197 brouard 13304: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13305: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13306: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13307: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13308: }
13309: /* Second parameter line */
13310: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13311: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13312: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13313: if (line[0] == '#') {
13314: numlinepar++;
1.283 brouard 13315: printf("%s",line);
13316: fprintf(ficres,"%s",line);
13317: fprintf(ficparo,"%s",line);
13318: fprintf(ficlog,"%s",line);
1.197 brouard 13319: continue;
13320: }else
13321: break;
13322: }
1.223 brouard 13323: 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", \
13324: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13325: if (num_filled != 11) {
13326: 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 13327: printf("but line=%s\n",line);
1.283 brouard 13328: 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");
13329: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13330: }
1.286 brouard 13331: if( lastpass > maxwav){
13332: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13333: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13334: fflush(ficlog);
13335: goto end;
13336: }
13337: 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 13338: 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 13339: 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 13340: 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 13341: }
1.203 brouard 13342: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13343: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13344: /* Third parameter line */
13345: while(fgets(line, MAXLINE, ficpar)) {
13346: /* If line starts with a # it is a comment */
13347: if (line[0] == '#') {
13348: numlinepar++;
1.283 brouard 13349: printf("%s",line);
13350: fprintf(ficres,"%s",line);
13351: fprintf(ficparo,"%s",line);
13352: fprintf(ficlog,"%s",line);
1.197 brouard 13353: continue;
13354: }else
13355: break;
13356: }
1.351 brouard 13357: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
13358: if (num_filled != 1){
13359: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13360: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13361: model[0]='\0';
13362: goto end;
13363: }else{
13364: trimbtab(linetmp,line); /* Trims multiple blanks in line */
13365: strcpy(line, linetmp);
13366: }
13367: }
13368: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 13369: if (num_filled != 1){
1.302 brouard 13370: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13371: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13372: model[0]='\0';
13373: goto end;
13374: }
13375: else{
13376: if (model[0]=='+'){
13377: for(i=1; i<=strlen(model);i++)
13378: modeltemp[i-1]=model[i];
1.201 brouard 13379: strcpy(model,modeltemp);
1.197 brouard 13380: }
13381: }
1.338 brouard 13382: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13383: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13384: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13385: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13386: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13387: }
13388: /* 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); */
13389: /* numlinepar=numlinepar+3; /\* In general *\/ */
13390: /* 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 13391: /* 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); */
13392: /* 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 13393: fflush(ficlog);
1.190 brouard 13394: /* if(model[0]=='#'|| model[0]== '\0'){ */
13395: if(model[0]=='#'){
1.279 brouard 13396: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13397: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13398: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13399: if(mle != -1){
1.279 brouard 13400: 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 13401: exit(1);
13402: }
13403: }
1.126 brouard 13404: while((c=getc(ficpar))=='#' && c!= EOF){
13405: ungetc(c,ficpar);
13406: fgets(line, MAXLINE, ficpar);
13407: numlinepar++;
1.195 brouard 13408: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13409: z[0]=line[1];
1.342 brouard 13410: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13411: debugILK=1;printf("DebugILK\n");
1.195 brouard 13412: }
13413: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13414: fputs(line, stdout);
13415: //puts(line);
1.126 brouard 13416: fputs(line,ficparo);
13417: fputs(line,ficlog);
13418: }
13419: ungetc(c,ficpar);
13420:
13421:
1.290 brouard 13422: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13423: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13424: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13425: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13426: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13427: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13428: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13429: v1+v2*age+v2*v3 makes cptcovn = 3
13430: */
13431: if (strlen(model)>1)
1.187 brouard 13432: 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 13433: else
1.187 brouard 13434: ncovmodel=2; /* Constant and age */
1.133 brouard 13435: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13436: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13437: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13438: 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);
13439: 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);
13440: fflush(stdout);
13441: fclose (ficlog);
13442: goto end;
13443: }
1.126 brouard 13444: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13445: delti=delti3[1][1];
13446: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13447: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13448: /* We could also provide initial parameters values giving by simple logistic regression
13449: * only one way, that is without matrix product. We will have nlstate maximizations */
13450: /* for(i=1;i<nlstate;i++){ */
13451: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13452: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13453: /* } */
1.126 brouard 13454: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13455: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13456: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13457: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13458: fclose (ficparo);
13459: fclose (ficlog);
13460: goto end;
13461: exit(0);
1.220 brouard 13462: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13463: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13464: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13465: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13466: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13467: matcov=matrix(1,npar,1,npar);
1.203 brouard 13468: hess=matrix(1,npar,1,npar);
1.220 brouard 13469: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13470: /* Read guessed parameters */
1.126 brouard 13471: /* Reads comments: lines beginning with '#' */
13472: while((c=getc(ficpar))=='#' && c!= EOF){
13473: ungetc(c,ficpar);
13474: fgets(line, MAXLINE, ficpar);
13475: numlinepar++;
1.141 brouard 13476: fputs(line,stdout);
1.126 brouard 13477: fputs(line,ficparo);
13478: fputs(line,ficlog);
13479: }
13480: ungetc(c,ficpar);
13481:
13482: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13483: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13484: for(i=1; i <=nlstate; i++){
1.234 brouard 13485: j=0;
1.126 brouard 13486: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13487: if(jj==i) continue;
13488: j++;
1.292 brouard 13489: while((c=getc(ficpar))=='#' && c!= EOF){
13490: ungetc(c,ficpar);
13491: fgets(line, MAXLINE, ficpar);
13492: numlinepar++;
13493: fputs(line,stdout);
13494: fputs(line,ficparo);
13495: fputs(line,ficlog);
13496: }
13497: ungetc(c,ficpar);
1.234 brouard 13498: fscanf(ficpar,"%1d%1d",&i1,&j1);
13499: if ((i1 != i) || (j1 != jj)){
13500: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13501: It might be a problem of design; if ncovcol and the model are correct\n \
13502: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13503: exit(1);
13504: }
13505: fprintf(ficparo,"%1d%1d",i1,j1);
13506: if(mle==1)
13507: printf("%1d%1d",i,jj);
13508: fprintf(ficlog,"%1d%1d",i,jj);
13509: for(k=1; k<=ncovmodel;k++){
13510: fscanf(ficpar," %lf",¶m[i][j][k]);
13511: if(mle==1){
13512: printf(" %lf",param[i][j][k]);
13513: fprintf(ficlog," %lf",param[i][j][k]);
13514: }
13515: else
13516: fprintf(ficlog," %lf",param[i][j][k]);
13517: fprintf(ficparo," %lf",param[i][j][k]);
13518: }
13519: fscanf(ficpar,"\n");
13520: numlinepar++;
13521: if(mle==1)
13522: printf("\n");
13523: fprintf(ficlog,"\n");
13524: fprintf(ficparo,"\n");
1.126 brouard 13525: }
13526: }
13527: fflush(ficlog);
1.234 brouard 13528:
1.251 brouard 13529: /* Reads parameters values */
1.126 brouard 13530: p=param[1][1];
1.251 brouard 13531: pstart=paramstart[1][1];
1.126 brouard 13532:
13533: /* Reads comments: lines beginning with '#' */
13534: while((c=getc(ficpar))=='#' && c!= EOF){
13535: ungetc(c,ficpar);
13536: fgets(line, MAXLINE, ficpar);
13537: numlinepar++;
1.141 brouard 13538: fputs(line,stdout);
1.126 brouard 13539: fputs(line,ficparo);
13540: fputs(line,ficlog);
13541: }
13542: ungetc(c,ficpar);
13543:
13544: for(i=1; i <=nlstate; i++){
13545: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13546: fscanf(ficpar,"%1d%1d",&i1,&j1);
13547: if ( (i1-i) * (j1-j) != 0){
13548: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13549: exit(1);
13550: }
13551: printf("%1d%1d",i,j);
13552: fprintf(ficparo,"%1d%1d",i1,j1);
13553: fprintf(ficlog,"%1d%1d",i1,j1);
13554: for(k=1; k<=ncovmodel;k++){
13555: fscanf(ficpar,"%le",&delti3[i][j][k]);
13556: printf(" %le",delti3[i][j][k]);
13557: fprintf(ficparo," %le",delti3[i][j][k]);
13558: fprintf(ficlog," %le",delti3[i][j][k]);
13559: }
13560: fscanf(ficpar,"\n");
13561: numlinepar++;
13562: printf("\n");
13563: fprintf(ficparo,"\n");
13564: fprintf(ficlog,"\n");
1.126 brouard 13565: }
13566: }
13567: fflush(ficlog);
1.234 brouard 13568:
1.145 brouard 13569: /* Reads covariance matrix */
1.126 brouard 13570: delti=delti3[1][1];
1.220 brouard 13571:
13572:
1.126 brouard 13573: /* 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 13574:
1.126 brouard 13575: /* Reads comments: lines beginning with '#' */
13576: while((c=getc(ficpar))=='#' && c!= EOF){
13577: ungetc(c,ficpar);
13578: fgets(line, MAXLINE, ficpar);
13579: numlinepar++;
1.141 brouard 13580: fputs(line,stdout);
1.126 brouard 13581: fputs(line,ficparo);
13582: fputs(line,ficlog);
13583: }
13584: ungetc(c,ficpar);
1.220 brouard 13585:
1.126 brouard 13586: matcov=matrix(1,npar,1,npar);
1.203 brouard 13587: hess=matrix(1,npar,1,npar);
1.131 brouard 13588: for(i=1; i <=npar; i++)
13589: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13590:
1.194 brouard 13591: /* Scans npar lines */
1.126 brouard 13592: for(i=1; i <=npar; i++){
1.226 brouard 13593: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13594: if(count != 3){
1.226 brouard 13595: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13596: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13597: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13598: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13599: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13600: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13601: exit(1);
1.220 brouard 13602: }else{
1.226 brouard 13603: if(mle==1)
13604: printf("%1d%1d%d",i1,j1,jk);
13605: }
13606: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13607: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13608: for(j=1; j <=i; j++){
1.226 brouard 13609: fscanf(ficpar," %le",&matcov[i][j]);
13610: if(mle==1){
13611: printf(" %.5le",matcov[i][j]);
13612: }
13613: fprintf(ficlog," %.5le",matcov[i][j]);
13614: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13615: }
13616: fscanf(ficpar,"\n");
13617: numlinepar++;
13618: if(mle==1)
1.220 brouard 13619: printf("\n");
1.126 brouard 13620: fprintf(ficlog,"\n");
13621: fprintf(ficparo,"\n");
13622: }
1.194 brouard 13623: /* End of read covariance matrix npar lines */
1.126 brouard 13624: for(i=1; i <=npar; i++)
13625: for(j=i+1;j<=npar;j++)
1.226 brouard 13626: matcov[i][j]=matcov[j][i];
1.126 brouard 13627:
13628: if(mle==1)
13629: printf("\n");
13630: fprintf(ficlog,"\n");
13631:
13632: fflush(ficlog);
13633:
13634: } /* End of mle != -3 */
1.218 brouard 13635:
1.186 brouard 13636: /* Main data
13637: */
1.290 brouard 13638: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13639: /* num=lvector(1,n); */
13640: /* moisnais=vector(1,n); */
13641: /* annais=vector(1,n); */
13642: /* moisdc=vector(1,n); */
13643: /* andc=vector(1,n); */
13644: /* weight=vector(1,n); */
13645: /* agedc=vector(1,n); */
13646: /* cod=ivector(1,n); */
13647: /* for(i=1;i<=n;i++){ */
13648: num=lvector(firstobs,lastobs);
13649: moisnais=vector(firstobs,lastobs);
13650: annais=vector(firstobs,lastobs);
13651: moisdc=vector(firstobs,lastobs);
13652: andc=vector(firstobs,lastobs);
13653: weight=vector(firstobs,lastobs);
13654: agedc=vector(firstobs,lastobs);
13655: cod=ivector(firstobs,lastobs);
13656: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13657: num[i]=0;
13658: moisnais[i]=0;
13659: annais[i]=0;
13660: moisdc[i]=0;
13661: andc[i]=0;
13662: agedc[i]=0;
13663: cod[i]=0;
13664: weight[i]=1.0; /* Equal weights, 1 by default */
13665: }
1.290 brouard 13666: mint=matrix(1,maxwav,firstobs,lastobs);
13667: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13668: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13669: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13670: tab=ivector(1,NCOVMAX);
1.144 brouard 13671: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13672: 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 13673:
1.136 brouard 13674: /* Reads data from file datafile */
13675: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13676: goto end;
13677:
13678: /* Calculation of the number of parameters from char model */
1.234 brouard 13679: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13680: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13681: k=3 V4 Tvar[k=3]= 4 (from V4)
13682: k=2 V1 Tvar[k=2]= 1 (from V1)
13683: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13684: */
13685:
13686: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13687: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13688: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13689: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13690: TvarsD=ivector(1,NCOVMAX); /* */
13691: TvarsQind=ivector(1,NCOVMAX); /* */
13692: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13693: TvarF=ivector(1,NCOVMAX); /* */
13694: TvarFind=ivector(1,NCOVMAX); /* */
13695: TvarV=ivector(1,NCOVMAX); /* */
13696: TvarVind=ivector(1,NCOVMAX); /* */
13697: TvarA=ivector(1,NCOVMAX); /* */
13698: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13699: TvarFD=ivector(1,NCOVMAX); /* */
13700: TvarFDind=ivector(1,NCOVMAX); /* */
13701: TvarFQ=ivector(1,NCOVMAX); /* */
13702: TvarFQind=ivector(1,NCOVMAX); /* */
13703: TvarVD=ivector(1,NCOVMAX); /* */
13704: TvarVDind=ivector(1,NCOVMAX); /* */
13705: TvarVQ=ivector(1,NCOVMAX); /* */
13706: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13707: TvarVV=ivector(1,NCOVMAX); /* */
13708: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 13709: TvarVVA=ivector(1,NCOVMAX); /* */
13710: TvarVVAind=ivector(1,NCOVMAX); /* */
13711: TvarAVVA=ivector(1,NCOVMAX); /* */
13712: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13713:
1.230 brouard 13714: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13715: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13716: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13717: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13718: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 13719: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
13720: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
13721:
1.137 brouard 13722: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13723: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13724: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13725: */
13726: /* For model-covariate k tells which data-covariate to use but
13727: because this model-covariate is a construction we invent a new column
13728: ncovcol + k1
13729: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13730: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13731: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13732: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13733: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13734: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13735: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13736: */
1.145 brouard 13737: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13738: 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 13739: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13740: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 13741: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 13742: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13743: 4 covariates (3 plus signs)
13744: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13745: */
13746: for(i=1;i<NCOVMAX;i++)
13747: Tage[i]=0;
1.230 brouard 13748: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13749: * individual dummy, fixed or varying:
13750: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13751: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13752: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13753: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13754: * Tmodelind[1]@9={9,0,3,2,}*/
13755: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13756: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13757: * individual quantitative, fixed or varying:
13758: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13759: * 3, 1, 0, 0, 0, 0, 0, 0},
13760: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 13761:
13762: /* Probably useless zeroes */
13763: for(i=1;i<NCOVMAX;i++){
13764: DummyV[i]=0;
13765: FixedV[i]=0;
13766: }
13767:
13768: for(i=1; i <=ncovcol;i++){
13769: DummyV[i]=0;
13770: FixedV[i]=0;
13771: }
13772: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
13773: DummyV[i]=1;
13774: FixedV[i]=0;
13775: }
13776: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
13777: DummyV[i]=0;
13778: FixedV[i]=1;
13779: }
13780: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
13781: DummyV[i]=1;
13782: FixedV[i]=1;
13783: }
13784: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
13785: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13786: 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]);
13787: }
13788:
13789:
13790:
1.186 brouard 13791: /* Main decodemodel */
13792:
1.187 brouard 13793:
1.223 brouard 13794: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13795: goto end;
13796:
1.137 brouard 13797: if((double)(lastobs-imx)/(double)imx > 1.10){
13798: nbwarn++;
13799: 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);
13800: 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);
13801: }
1.136 brouard 13802: /* if(mle==1){*/
1.137 brouard 13803: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13804: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13805: }
13806:
13807: /*-calculation of age at interview from date of interview and age at death -*/
13808: agev=matrix(1,maxwav,1,imx);
13809:
13810: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13811: goto end;
13812:
1.126 brouard 13813:
1.136 brouard 13814: agegomp=(int)agemin;
1.290 brouard 13815: free_vector(moisnais,firstobs,lastobs);
13816: free_vector(annais,firstobs,lastobs);
1.126 brouard 13817: /* free_matrix(mint,1,maxwav,1,n);
13818: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13819: /* free_vector(moisdc,1,n); */
13820: /* free_vector(andc,1,n); */
1.145 brouard 13821: /* */
13822:
1.126 brouard 13823: wav=ivector(1,imx);
1.214 brouard 13824: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13825: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13826: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13827: 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.*/
13828: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13829: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13830:
13831: /* Concatenates waves */
1.214 brouard 13832: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13833: Death is a valid wave (if date is known).
13834: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13835: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13836: and mw[mi+1][i]. dh depends on stepm.
13837: */
13838:
1.126 brouard 13839: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13840: /* Concatenates waves */
1.145 brouard 13841:
1.290 brouard 13842: free_vector(moisdc,firstobs,lastobs);
13843: free_vector(andc,firstobs,lastobs);
1.215 brouard 13844:
1.126 brouard 13845: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13846: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13847: ncodemax[1]=1;
1.145 brouard 13848: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13849: cptcoveff=0;
1.220 brouard 13850: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13851: 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 13852: }
13853:
13854: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13855: invalidvarcomb=ivector(0, ncovcombmax);
13856: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13857: invalidvarcomb[i]=0;
13858:
1.211 brouard 13859: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13860: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13861: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13862:
1.200 brouard 13863: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13864: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13865: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13866: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13867: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13868: * (currently 0 or 1) in the data.
13869: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13870: * corresponding modality (h,j).
13871: */
13872:
1.145 brouard 13873: h=0;
13874: /*if (cptcovn > 0) */
1.126 brouard 13875: m=pow(2,cptcoveff);
13876:
1.144 brouard 13877: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13878: * For k=4 covariates, h goes from 1 to m=2**k
13879: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13880: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13881: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13882: *______________________________ *______________________
13883: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13884: * 2 2 1 1 1 * 1 0 0 0 1
13885: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13886: * 4 2 2 1 1 * 3 0 0 1 1
13887: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13888: * 6 2 1 2 1 * 5 0 1 0 1
13889: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13890: * 8 2 2 2 1 * 7 0 1 1 1
13891: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13892: * 10 2 1 1 2 * 9 1 0 0 1
13893: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13894: * 12 2 2 1 2 * 11 1 0 1 1
13895: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13896: * 14 2 1 2 2 * 13 1 1 0 1
13897: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13898: * 16 2 2 2 2 * 15 1 1 1 1
13899: */
1.212 brouard 13900: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13901: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13902: * and the value of each covariate?
13903: * V1=1, V2=1, V3=2, V4=1 ?
13904: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13905: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13906: * In order to get the real value in the data, we use nbcode
13907: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13908: * We are keeping this crazy system in order to be able (in the future?)
13909: * to have more than 2 values (0 or 1) for a covariate.
13910: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13911: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13912: * bbbbbbbb
13913: * 76543210
13914: * h-1 00000101 (6-1=5)
1.219 brouard 13915: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13916: * &
13917: * 1 00000001 (1)
1.219 brouard 13918: * 00000000 = 1 & ((h-1) >> (k-1))
13919: * +1= 00000001 =1
1.211 brouard 13920: *
13921: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13922: * h' 1101 =2^3+2^2+0x2^1+2^0
13923: * >>k' 11
13924: * & 00000001
13925: * = 00000001
13926: * +1 = 00000010=2 = codtabm(14,3)
13927: * Reverse h=6 and m=16?
13928: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13929: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13930: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13931: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13932: * V3=decodtabm(14,3,2**4)=2
13933: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13934: *(h-1) >> (j-1) 0011 =13 >> 2
13935: * &1 000000001
13936: * = 000000001
13937: * +1= 000000010 =2
13938: * 2211
13939: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13940: * V3=2
1.220 brouard 13941: * codtabm and decodtabm are identical
1.211 brouard 13942: */
13943:
1.145 brouard 13944:
13945: free_ivector(Ndum,-1,NCOVMAX);
13946:
13947:
1.126 brouard 13948:
1.186 brouard 13949: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13950: strcpy(optionfilegnuplot,optionfilefiname);
13951: if(mle==-3)
1.201 brouard 13952: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13953: strcat(optionfilegnuplot,".gp");
13954:
13955: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13956: printf("Problem with file %s",optionfilegnuplot);
13957: }
13958: else{
1.204 brouard 13959: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13960: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13961: //fprintf(ficgp,"set missing 'NaNq'\n");
13962: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13963: }
13964: /* fclose(ficgp);*/
1.186 brouard 13965:
13966:
13967: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13968:
13969: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13970: if(mle==-3)
1.201 brouard 13971: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13972: strcat(optionfilehtm,".htm");
13973: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13974: printf("Problem with %s \n",optionfilehtm);
13975: exit(0);
1.126 brouard 13976: }
13977:
13978: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13979: strcat(optionfilehtmcov,"-cov.htm");
13980: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13981: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13982: }
13983: else{
13984: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13985: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13986: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13987: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13988: }
13989:
1.335 brouard 13990: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13991: <title>IMaCh %s</title></head>\n\
13992: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13993: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13994: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13995: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13996: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13997:
13998: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13999: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 14000: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 14001: 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 14002: \n\
14003: <hr size=\"2\" color=\"#EC5E5E\">\
14004: <ul><li><h4>Parameter files</h4>\n\
14005: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
14006: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
14007: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
14008: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
14009: - Date and time at start: %s</ul>\n",\
1.335 brouard 14010: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 14011: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
14012: fileres,fileres,\
14013: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
14014: fflush(fichtm);
14015:
14016: strcpy(pathr,path);
14017: strcat(pathr,optionfilefiname);
1.184 brouard 14018: #ifdef WIN32
14019: _chdir(optionfilefiname); /* Move to directory named optionfile */
14020: #else
1.126 brouard 14021: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 14022: #endif
14023:
1.126 brouard 14024:
1.220 brouard 14025: /* Calculates basic frequencies. Computes observed prevalence at single age
14026: and for any valid combination of covariates
1.126 brouard 14027: and prints on file fileres'p'. */
1.251 brouard 14028: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 14029: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 14030:
14031: fprintf(fichtm,"\n");
1.286 brouard 14032: 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 14033: ftol, stepm);
14034: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
14035: ncurrv=1;
14036: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
14037: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
14038: ncurrv=i;
14039: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14040: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 14041: ncurrv=i;
14042: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14043: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 14044: ncurrv=i;
14045: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
14046: 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", \
14047: nlstate, ndeath, maxwav, mle, weightopt);
14048:
14049: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
14050: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
14051:
14052:
1.317 brouard 14053: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 14054: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
14055: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 14056: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 14057: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 14058: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14059: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14060: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14061: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 14062:
1.126 brouard 14063: /* For Powell, parameters are in a vector p[] starting at p[1]
14064: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
14065: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
14066:
14067: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 14068: /* For mortality only */
1.126 brouard 14069: if (mle==-3){
1.136 brouard 14070: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 14071: for(i=1;i<=NDIM;i++)
14072: for(j=1;j<=NDIM;j++)
14073: ximort[i][j]=0.;
1.186 brouard 14074: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 14075: cens=ivector(firstobs,lastobs);
14076: ageexmed=vector(firstobs,lastobs);
14077: agecens=vector(firstobs,lastobs);
14078: dcwave=ivector(firstobs,lastobs);
1.223 brouard 14079:
1.126 brouard 14080: for (i=1; i<=imx; i++){
14081: dcwave[i]=-1;
14082: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 14083: if (s[m][i]>nlstate) {
14084: dcwave[i]=m;
14085: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
14086: break;
14087: }
1.126 brouard 14088: }
1.226 brouard 14089:
1.126 brouard 14090: for (i=1; i<=imx; i++) {
14091: if (wav[i]>0){
1.226 brouard 14092: ageexmed[i]=agev[mw[1][i]][i];
14093: j=wav[i];
14094: agecens[i]=1.;
14095:
14096: if (ageexmed[i]> 1 && wav[i] > 0){
14097: agecens[i]=agev[mw[j][i]][i];
14098: cens[i]= 1;
14099: }else if (ageexmed[i]< 1)
14100: cens[i]= -1;
14101: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
14102: cens[i]=0 ;
1.126 brouard 14103: }
14104: else cens[i]=-1;
14105: }
14106:
14107: for (i=1;i<=NDIM;i++) {
14108: for (j=1;j<=NDIM;j++)
1.226 brouard 14109: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 14110: }
14111:
1.302 brouard 14112: p[1]=0.0268; p[NDIM]=0.083;
14113: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14114:
14115:
1.136 brouard 14116: #ifdef GSL
14117: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14118: #else
1.126 brouard 14119: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14120: #endif
1.201 brouard 14121: strcpy(filerespow,"POW-MORT_");
14122: strcat(filerespow,fileresu);
1.126 brouard 14123: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14124: printf("Problem with resultfile: %s\n", filerespow);
14125: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14126: }
1.136 brouard 14127: #ifdef GSL
14128: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14129: #else
1.126 brouard 14130: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14131: #endif
1.126 brouard 14132: /* for (i=1;i<=nlstate;i++)
14133: for(j=1;j<=nlstate+ndeath;j++)
14134: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14135: */
14136: fprintf(ficrespow,"\n");
1.136 brouard 14137: #ifdef GSL
14138: /* gsl starts here */
14139: T = gsl_multimin_fminimizer_nmsimplex;
14140: gsl_multimin_fminimizer *sfm = NULL;
14141: gsl_vector *ss, *x;
14142: gsl_multimin_function minex_func;
14143:
14144: /* Initial vertex size vector */
14145: ss = gsl_vector_alloc (NDIM);
14146:
14147: if (ss == NULL){
14148: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14149: }
14150: /* Set all step sizes to 1 */
14151: gsl_vector_set_all (ss, 0.001);
14152:
14153: /* Starting point */
1.126 brouard 14154:
1.136 brouard 14155: x = gsl_vector_alloc (NDIM);
14156:
14157: if (x == NULL){
14158: gsl_vector_free(ss);
14159: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14160: }
14161:
14162: /* Initialize method and iterate */
14163: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14164: /* gsl_vector_set(x, 0, 0.0268); */
14165: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14166: gsl_vector_set(x, 0, p[1]);
14167: gsl_vector_set(x, 1, p[2]);
14168:
14169: minex_func.f = &gompertz_f;
14170: minex_func.n = NDIM;
14171: minex_func.params = (void *)&p; /* ??? */
14172:
14173: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14174: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14175:
14176: printf("Iterations beginning .....\n\n");
14177: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14178:
14179: iteri=0;
14180: while (rval == GSL_CONTINUE){
14181: iteri++;
14182: status = gsl_multimin_fminimizer_iterate(sfm);
14183:
14184: if (status) printf("error: %s\n", gsl_strerror (status));
14185: fflush(0);
14186:
14187: if (status)
14188: break;
14189:
14190: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14191: ssval = gsl_multimin_fminimizer_size (sfm);
14192:
14193: if (rval == GSL_SUCCESS)
14194: printf ("converged to a local maximum at\n");
14195:
14196: printf("%5d ", iteri);
14197: for (it = 0; it < NDIM; it++){
14198: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14199: }
14200: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14201: }
14202:
14203: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14204:
14205: gsl_vector_free(x); /* initial values */
14206: gsl_vector_free(ss); /* inital step size */
14207: for (it=0; it<NDIM; it++){
14208: p[it+1]=gsl_vector_get(sfm->x,it);
14209: fprintf(ficrespow," %.12lf", p[it]);
14210: }
14211: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14212: #endif
14213: #ifdef POWELL
14214: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14215: #endif
1.126 brouard 14216: fclose(ficrespow);
14217:
1.203 brouard 14218: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14219:
14220: for(i=1; i <=NDIM; i++)
14221: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14222: matcov[i][j]=matcov[j][i];
1.126 brouard 14223:
14224: printf("\nCovariance matrix\n ");
1.203 brouard 14225: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14226: for(i=1; i <=NDIM; i++) {
14227: for(j=1;j<=NDIM;j++){
1.220 brouard 14228: printf("%f ",matcov[i][j]);
14229: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14230: }
1.203 brouard 14231: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14232: }
14233:
14234: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14235: for (i=1;i<=NDIM;i++) {
1.126 brouard 14236: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14237: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14238: }
1.302 brouard 14239: lsurv=vector(agegomp,AGESUP);
14240: lpop=vector(agegomp,AGESUP);
14241: tpop=vector(agegomp,AGESUP);
1.126 brouard 14242: lsurv[agegomp]=100000;
14243:
14244: for (k=agegomp;k<=AGESUP;k++) {
14245: agemortsup=k;
14246: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14247: }
14248:
14249: for (k=agegomp;k<agemortsup;k++)
14250: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14251:
14252: for (k=agegomp;k<agemortsup;k++){
14253: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14254: sumlpop=sumlpop+lpop[k];
14255: }
14256:
14257: tpop[agegomp]=sumlpop;
14258: for (k=agegomp;k<(agemortsup-3);k++){
14259: /* tpop[k+1]=2;*/
14260: tpop[k+1]=tpop[k]-lpop[k];
14261: }
14262:
14263:
14264: printf("\nAge lx qx dx Lx Tx e(x)\n");
14265: for (k=agegomp;k<(agemortsup-2);k++)
14266: 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]);
14267:
14268:
14269: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14270: ageminpar=50;
14271: agemaxpar=100;
1.194 brouard 14272: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14273: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14274: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14275: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
14276: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14277: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14278: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14279: }else{
14280: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14281: 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 14282: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14283: }
1.201 brouard 14284: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14285: stepm, weightopt,\
14286: model,imx,p,matcov,agemortsup);
14287:
1.302 brouard 14288: free_vector(lsurv,agegomp,AGESUP);
14289: free_vector(lpop,agegomp,AGESUP);
14290: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14291: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14292: free_ivector(dcwave,firstobs,lastobs);
14293: free_vector(agecens,firstobs,lastobs);
14294: free_vector(ageexmed,firstobs,lastobs);
14295: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14296: #ifdef GSL
1.136 brouard 14297: #endif
1.186 brouard 14298: } /* Endof if mle==-3 mortality only */
1.205 brouard 14299: /* Standard */
14300: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14301: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14302: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14303: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14304: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14305: for (k=1; k<=npar;k++)
14306: printf(" %d %8.5f",k,p[k]);
14307: printf("\n");
1.205 brouard 14308: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14309: /* mlikeli uses func not funcone */
1.247 brouard 14310: /* for(i=1;i<nlstate;i++){ */
14311: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14312: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14313: /* } */
1.205 brouard 14314: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14315: }
14316: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14317: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14318: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14319: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14320: }
14321: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14322: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14323: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14324: /* exit(0); */
1.126 brouard 14325: for (k=1; k<=npar;k++)
14326: printf(" %d %8.5f",k,p[k]);
14327: printf("\n");
14328:
14329: /*--------- results files --------------*/
1.283 brouard 14330: /* 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 14331:
14332:
14333: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14334: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14335: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14336:
14337: printf("#model= 1 + age ");
14338: fprintf(ficres,"#model= 1 + age ");
14339: fprintf(ficlog,"#model= 1 + age ");
14340: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14341: </ul>", model);
14342:
14343: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14344: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14345: if(nagesqr==1){
14346: printf(" + age*age ");
14347: fprintf(ficres," + age*age ");
14348: fprintf(ficlog," + age*age ");
14349: fprintf(fichtm, "<th>+ age*age</th>");
14350: }
14351: for(j=1;j <=ncovmodel-2;j++){
14352: if(Typevar[j]==0) {
14353: printf(" + V%d ",Tvar[j]);
14354: fprintf(ficres," + V%d ",Tvar[j]);
14355: fprintf(ficlog," + V%d ",Tvar[j]);
14356: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14357: }else if(Typevar[j]==1) {
14358: printf(" + V%d*age ",Tvar[j]);
14359: fprintf(ficres," + V%d*age ",Tvar[j]);
14360: fprintf(ficlog," + V%d*age ",Tvar[j]);
14361: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14362: }else if(Typevar[j]==2) {
14363: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14364: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14365: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14366: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14367: }else if(Typevar[j]==3) { /* TO VERIFY */
14368: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14369: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14370: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14371: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14372: }
14373: }
14374: printf("\n");
14375: fprintf(ficres,"\n");
14376: fprintf(ficlog,"\n");
14377: fprintf(fichtm, "</tr>");
14378: fprintf(fichtm, "\n");
14379:
14380:
1.126 brouard 14381: for(i=1,jk=1; i <=nlstate; i++){
14382: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14383: if (k != i) {
1.319 brouard 14384: fprintf(fichtm, "<tr>");
1.225 brouard 14385: printf("%d%d ",i,k);
14386: fprintf(ficlog,"%d%d ",i,k);
14387: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14388: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14389: for(j=1; j <=ncovmodel; j++){
14390: printf("%12.7f ",p[jk]);
14391: fprintf(ficlog,"%12.7f ",p[jk]);
14392: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14393: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14394: jk++;
14395: }
14396: printf("\n");
14397: fprintf(ficlog,"\n");
14398: fprintf(ficres,"\n");
1.319 brouard 14399: fprintf(fichtm, "</tr>\n");
1.225 brouard 14400: }
1.126 brouard 14401: }
14402: }
1.319 brouard 14403: /* fprintf(fichtm,"</tr>\n"); */
14404: fprintf(fichtm,"</table>\n");
14405: fprintf(fichtm, "\n");
14406:
1.203 brouard 14407: if(mle != 0){
14408: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14409: ftolhess=ftol; /* Usually correct */
1.203 brouard 14410: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14411: 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");
14412: 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 14413: 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 14414: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14415: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14416: if(nagesqr==1){
14417: printf(" + age*age ");
14418: fprintf(ficres," + age*age ");
14419: fprintf(ficlog," + age*age ");
14420: fprintf(fichtm, "<th>+ age*age</th>");
14421: }
14422: for(j=1;j <=ncovmodel-2;j++){
14423: if(Typevar[j]==0) {
14424: printf(" + V%d ",Tvar[j]);
14425: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14426: }else if(Typevar[j]==1) {
14427: printf(" + V%d*age ",Tvar[j]);
14428: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14429: }else if(Typevar[j]==2) {
14430: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14431: }else if(Typevar[j]==3) { /* TO VERIFY */
14432: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14433: }
14434: }
14435: fprintf(fichtm, "</tr>\n");
14436:
1.203 brouard 14437: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14438: for(k=1; k <=(nlstate+ndeath); k++){
14439: if (k != i) {
1.319 brouard 14440: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14441: printf("%d%d ",i,k);
14442: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14443: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14444: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14445: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14446: 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]));
14447: 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 14448: if(fabs(wald) > 1.96){
1.321 brouard 14449: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14450: }else{
14451: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14452: }
1.324 brouard 14453: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14454: 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 14455: jk++;
14456: }
14457: printf("\n");
14458: fprintf(ficlog,"\n");
1.319 brouard 14459: fprintf(fichtm, "</tr>\n");
1.225 brouard 14460: }
14461: }
1.193 brouard 14462: }
1.203 brouard 14463: } /* end of hesscov and Wald tests */
1.319 brouard 14464: fprintf(fichtm,"</table>\n");
1.225 brouard 14465:
1.203 brouard 14466: /* */
1.126 brouard 14467: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14468: printf("# Scales (for hessian or gradient estimation)\n");
14469: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14470: for(i=1,jk=1; i <=nlstate; i++){
14471: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14472: if (j!=i) {
14473: fprintf(ficres,"%1d%1d",i,j);
14474: printf("%1d%1d",i,j);
14475: fprintf(ficlog,"%1d%1d",i,j);
14476: for(k=1; k<=ncovmodel;k++){
14477: printf(" %.5e",delti[jk]);
14478: fprintf(ficlog," %.5e",delti[jk]);
14479: fprintf(ficres," %.5e",delti[jk]);
14480: jk++;
14481: }
14482: printf("\n");
14483: fprintf(ficlog,"\n");
14484: fprintf(ficres,"\n");
14485: }
1.126 brouard 14486: }
14487: }
14488:
14489: 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 14490: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14491: 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");
14492: 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");
14493: /* # 121 Var(a12)\n\ */
14494: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14495: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14496: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14497: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14498: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14499: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14500: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14501:
14502:
14503: /* Just to have a covariance matrix which will be more understandable
14504: even is we still don't want to manage dictionary of variables
14505: */
14506: for(itimes=1;itimes<=2;itimes++){
14507: jj=0;
14508: for(i=1; i <=nlstate; i++){
1.225 brouard 14509: for(j=1; j <=nlstate+ndeath; j++){
14510: if(j==i) continue;
14511: for(k=1; k<=ncovmodel;k++){
14512: jj++;
14513: ca[0]= k+'a'-1;ca[1]='\0';
14514: if(itimes==1){
14515: if(mle>=1)
14516: printf("#%1d%1d%d",i,j,k);
14517: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14518: fprintf(ficres,"#%1d%1d%d",i,j,k);
14519: }else{
14520: if(mle>=1)
14521: printf("%1d%1d%d",i,j,k);
14522: fprintf(ficlog,"%1d%1d%d",i,j,k);
14523: fprintf(ficres,"%1d%1d%d",i,j,k);
14524: }
14525: ll=0;
14526: for(li=1;li <=nlstate; li++){
14527: for(lj=1;lj <=nlstate+ndeath; lj++){
14528: if(lj==li) continue;
14529: for(lk=1;lk<=ncovmodel;lk++){
14530: ll++;
14531: if(ll<=jj){
14532: cb[0]= lk +'a'-1;cb[1]='\0';
14533: if(ll<jj){
14534: if(itimes==1){
14535: if(mle>=1)
14536: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14537: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14538: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14539: }else{
14540: if(mle>=1)
14541: printf(" %.5e",matcov[jj][ll]);
14542: fprintf(ficlog," %.5e",matcov[jj][ll]);
14543: fprintf(ficres," %.5e",matcov[jj][ll]);
14544: }
14545: }else{
14546: if(itimes==1){
14547: if(mle>=1)
14548: printf(" Var(%s%1d%1d)",ca,i,j);
14549: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14550: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14551: }else{
14552: if(mle>=1)
14553: printf(" %.7e",matcov[jj][ll]);
14554: fprintf(ficlog," %.7e",matcov[jj][ll]);
14555: fprintf(ficres," %.7e",matcov[jj][ll]);
14556: }
14557: }
14558: }
14559: } /* end lk */
14560: } /* end lj */
14561: } /* end li */
14562: if(mle>=1)
14563: printf("\n");
14564: fprintf(ficlog,"\n");
14565: fprintf(ficres,"\n");
14566: numlinepar++;
14567: } /* end k*/
14568: } /*end j */
1.126 brouard 14569: } /* end i */
14570: } /* end itimes */
14571:
14572: fflush(ficlog);
14573: fflush(ficres);
1.225 brouard 14574: while(fgets(line, MAXLINE, ficpar)) {
14575: /* If line starts with a # it is a comment */
14576: if (line[0] == '#') {
14577: numlinepar++;
14578: fputs(line,stdout);
14579: fputs(line,ficparo);
14580: fputs(line,ficlog);
1.299 brouard 14581: fputs(line,ficres);
1.225 brouard 14582: continue;
14583: }else
14584: break;
14585: }
14586:
1.209 brouard 14587: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14588: /* ungetc(c,ficpar); */
14589: /* fgets(line, MAXLINE, ficpar); */
14590: /* fputs(line,stdout); */
14591: /* fputs(line,ficparo); */
14592: /* } */
14593: /* ungetc(c,ficpar); */
1.126 brouard 14594:
14595: estepm=0;
1.209 brouard 14596: 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 14597:
14598: if (num_filled != 6) {
14599: 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);
14600: 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);
14601: goto end;
14602: }
14603: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14604: }
14605: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14606: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14607:
1.209 brouard 14608: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14609: if (estepm==0 || estepm < stepm) estepm=stepm;
14610: if (fage <= 2) {
14611: bage = ageminpar;
14612: fage = agemaxpar;
14613: }
14614:
14615: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14616: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14617: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14618:
1.186 brouard 14619: /* Other stuffs, more or less useful */
1.254 brouard 14620: while(fgets(line, MAXLINE, ficpar)) {
14621: /* If line starts with a # it is a comment */
14622: if (line[0] == '#') {
14623: numlinepar++;
14624: fputs(line,stdout);
14625: fputs(line,ficparo);
14626: fputs(line,ficlog);
1.299 brouard 14627: fputs(line,ficres);
1.254 brouard 14628: continue;
14629: }else
14630: break;
14631: }
14632:
14633: 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){
14634:
14635: if (num_filled != 7) {
14636: 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);
14637: 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);
14638: goto end;
14639: }
14640: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14641: 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);
14642: 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);
14643: 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 14644: }
1.254 brouard 14645:
14646: while(fgets(line, MAXLINE, ficpar)) {
14647: /* If line starts with a # it is a comment */
14648: if (line[0] == '#') {
14649: numlinepar++;
14650: fputs(line,stdout);
14651: fputs(line,ficparo);
14652: fputs(line,ficlog);
1.299 brouard 14653: fputs(line,ficres);
1.254 brouard 14654: continue;
14655: }else
14656: break;
1.126 brouard 14657: }
14658:
14659:
14660: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14661: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14662:
1.254 brouard 14663: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14664: if (num_filled != 1) {
14665: 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);
14666: 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);
14667: goto end;
14668: }
14669: printf("pop_based=%d\n",popbased);
14670: fprintf(ficlog,"pop_based=%d\n",popbased);
14671: fprintf(ficparo,"pop_based=%d\n",popbased);
14672: fprintf(ficres,"pop_based=%d\n",popbased);
14673: }
14674:
1.258 brouard 14675: /* Results */
1.332 brouard 14676: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14677: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14678: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14679: endishere=0;
1.258 brouard 14680: nresult=0;
1.308 brouard 14681: parameterline=0;
1.258 brouard 14682: do{
14683: if(!fgets(line, MAXLINE, ficpar)){
14684: endishere=1;
1.308 brouard 14685: parameterline=15;
1.258 brouard 14686: }else if (line[0] == '#') {
14687: /* If line starts with a # it is a comment */
1.254 brouard 14688: numlinepar++;
14689: fputs(line,stdout);
14690: fputs(line,ficparo);
14691: fputs(line,ficlog);
1.299 brouard 14692: fputs(line,ficres);
1.254 brouard 14693: continue;
1.258 brouard 14694: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14695: parameterline=11;
1.296 brouard 14696: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14697: parameterline=12;
1.307 brouard 14698: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14699: parameterline=13;
1.307 brouard 14700: }
1.258 brouard 14701: else{
14702: parameterline=14;
1.254 brouard 14703: }
1.308 brouard 14704: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14705: case 11:
1.296 brouard 14706: 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)){
14707: 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 14708: 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);
14709: 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);
14710: 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);
14711: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14712: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14713: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14714: prvforecast = 1;
14715: }
14716: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14717: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14718: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14719: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14720: prvforecast = 2;
14721: }
14722: else {
14723: 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);
14724: 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);
14725: goto end;
1.258 brouard 14726: }
1.254 brouard 14727: break;
1.258 brouard 14728: case 12:
1.296 brouard 14729: 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)){
14730: 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);
14731: 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);
14732: 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);
14733: 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);
14734: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14735: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14736: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14737: prvbackcast = 1;
14738: }
14739: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14740: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14741: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14742: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14743: prvbackcast = 2;
14744: }
14745: else {
14746: 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);
14747: 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);
14748: goto end;
1.258 brouard 14749: }
1.230 brouard 14750: break;
1.258 brouard 14751: case 13:
1.332 brouard 14752: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14753: nresult++; /* Sum of resultlines */
1.342 brouard 14754: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14755: /* removefirstspace(&resultlineori); */
14756:
14757: if(strstr(resultlineori,"v") !=0){
14758: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14759: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14760: return 1;
14761: }
14762: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14763: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14764: if(nresult > MAXRESULTLINESPONE-1){
14765: 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);
14766: 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 14767: goto end;
14768: }
1.332 brouard 14769:
1.310 brouard 14770: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14771: fprintf(ficparo,"result: %s\n",resultline);
14772: fprintf(ficres,"result: %s\n",resultline);
14773: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14774: } else
14775: goto end;
1.307 brouard 14776: break;
14777: case 14:
14778: printf("Error: Unknown command '%s'\n",line);
14779: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14780: if(line[0] == ' ' || line[0] == '\n'){
14781: printf("It should not be an empty line '%s'\n",line);
14782: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14783: }
1.307 brouard 14784: if(ncovmodel >=2 && nresult==0 ){
14785: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14786: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14787: }
1.307 brouard 14788: /* goto end; */
14789: break;
1.308 brouard 14790: case 15:
14791: printf("End of resultlines.\n");
14792: fprintf(ficlog,"End of resultlines.\n");
14793: break;
14794: default: /* parameterline =0 */
1.307 brouard 14795: nresult=1;
14796: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14797: } /* End switch parameterline */
14798: }while(endishere==0); /* End do */
1.126 brouard 14799:
1.230 brouard 14800: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14801: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14802:
14803: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14804: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14805: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14806: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14807: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14808: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14809: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14810: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14811: }else{
1.270 brouard 14812: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14813: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14814: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14815: if(prvforecast==1){
14816: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14817: jprojd=jproj1;
14818: mprojd=mproj1;
14819: anprojd=anproj1;
14820: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14821: jprojf=jproj2;
14822: mprojf=mproj2;
14823: anprojf=anproj2;
14824: } else if(prvforecast == 2){
14825: dateprojd=dateintmean;
14826: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14827: dateprojf=dateintmean+yrfproj;
14828: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14829: }
14830: if(prvbackcast==1){
14831: datebackd=(jback1+12*mback1+365*anback1)/365;
14832: jbackd=jback1;
14833: mbackd=mback1;
14834: anbackd=anback1;
14835: datebackf=(jback2+12*mback2+365*anback2)/365;
14836: jbackf=jback2;
14837: mbackf=mback2;
14838: anbackf=anback2;
14839: } else if(prvbackcast == 2){
14840: datebackd=dateintmean;
14841: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14842: datebackf=dateintmean-yrbproj;
14843: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14844: }
14845:
1.350 brouard 14846: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 14847: }
14848: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14849: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14850: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14851:
1.225 brouard 14852: /*------------ free_vector -------------*/
14853: /* chdir(path); */
1.220 brouard 14854:
1.215 brouard 14855: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14856: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14857: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14858: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14859: free_lvector(num,firstobs,lastobs);
14860: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14861: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14862: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14863: fclose(ficparo);
14864: fclose(ficres);
1.220 brouard 14865:
14866:
1.186 brouard 14867: /* Other results (useful)*/
1.220 brouard 14868:
14869:
1.126 brouard 14870: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14871: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14872: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14873: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14874: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14875: fclose(ficrespl);
14876:
14877: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14878: /*#include "hpijx.h"*/
1.332 brouard 14879: /** 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?*/
14880: /* calls hpxij with combination k */
1.180 brouard 14881: hPijx(p, bage, fage);
1.145 brouard 14882: fclose(ficrespij);
1.227 brouard 14883:
1.220 brouard 14884: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14885: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14886: k=1;
1.126 brouard 14887: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14888:
1.269 brouard 14889: /* Prevalence for each covariate combination in probs[age][status][cov] */
14890: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14891: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14892: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14893: for(k=1;k<=ncovcombmax;k++)
14894: probs[i][j][k]=0.;
1.269 brouard 14895: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14896: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14897: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14898: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14899: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14900: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14901: for(k=1;k<=ncovcombmax;k++)
14902: mobaverages[i][j][k]=0.;
1.219 brouard 14903: mobaverage=mobaverages;
14904: if (mobilav!=0) {
1.235 brouard 14905: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14906: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14907: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14908: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14909: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14910: }
1.269 brouard 14911: } else if (mobilavproj !=0) {
1.235 brouard 14912: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14913: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14914: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14915: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14916: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14917: }
1.269 brouard 14918: }else{
14919: printf("Internal error moving average\n");
14920: fflush(stdout);
14921: exit(1);
1.219 brouard 14922: }
14923: }/* end if moving average */
1.227 brouard 14924:
1.126 brouard 14925: /*---------- Forecasting ------------------*/
1.296 brouard 14926: if(prevfcast==1){
14927: /* /\* if(stepm ==1){*\/ */
14928: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14929: /*This done previously after freqsummary.*/
14930: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14931: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14932:
14933: /* } else if (prvforecast==2){ */
14934: /* /\* if(stepm ==1){*\/ */
14935: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14936: /* } */
14937: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14938: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14939: }
1.269 brouard 14940:
1.296 brouard 14941: /* Prevbcasting */
14942: if(prevbcast==1){
1.219 brouard 14943: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14944: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14945: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14946:
14947: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14948:
14949: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14950:
1.219 brouard 14951: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14952: fclose(ficresplb);
14953:
1.222 brouard 14954: hBijx(p, bage, fage, mobaverage);
14955: fclose(ficrespijb);
1.219 brouard 14956:
1.296 brouard 14957: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14958: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14959: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14960: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14961: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14962: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14963:
14964:
1.269 brouard 14965: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14966:
14967:
1.269 brouard 14968: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14969: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14970: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14971: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14972: } /* end Prevbcasting */
1.268 brouard 14973:
1.186 brouard 14974:
14975: /* ------ Other prevalence ratios------------ */
1.126 brouard 14976:
1.215 brouard 14977: free_ivector(wav,1,imx);
14978: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14979: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14980: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14981:
14982:
1.127 brouard 14983: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14984:
1.201 brouard 14985: strcpy(filerese,"E_");
14986: strcat(filerese,fileresu);
1.126 brouard 14987: if((ficreseij=fopen(filerese,"w"))==NULL) {
14988: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14989: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14990: }
1.208 brouard 14991: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14992: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14993:
14994: pstamp(ficreseij);
1.219 brouard 14995:
1.351 brouard 14996: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
14997: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 14998:
1.351 brouard 14999: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
15000: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
15001: /* if(i1 != 1 && TKresult[nres]!= k) */
15002: /* continue; */
1.219 brouard 15003: fprintf(ficreseij,"\n#****** ");
1.235 brouard 15004: printf("\n#****** ");
1.351 brouard 15005: for(j=1;j<=cptcovs;j++){
15006: /* for(j=1;j<=cptcoveff;j++) { */
15007: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15008: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15009: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15010: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 15011: }
15012: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 15013: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
15014: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 15015: }
15016: fprintf(ficreseij,"******\n");
1.235 brouard 15017: printf("******\n");
1.219 brouard 15018:
15019: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15020: oldm=oldms;savm=savms;
1.330 brouard 15021: /* 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 15022: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 15023:
1.219 brouard 15024: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 15025: }
15026: fclose(ficreseij);
1.208 brouard 15027: printf("done evsij\n");fflush(stdout);
15028: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 15029:
1.218 brouard 15030:
1.227 brouard 15031: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 15032: /* Should be moved in a function */
1.201 brouard 15033: strcpy(filerest,"T_");
15034: strcat(filerest,fileresu);
1.127 brouard 15035: if((ficrest=fopen(filerest,"w"))==NULL) {
15036: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
15037: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
15038: }
1.208 brouard 15039: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
15040: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 15041: strcpy(fileresstde,"STDE_");
15042: strcat(fileresstde,fileresu);
1.126 brouard 15043: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 15044: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
15045: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 15046: }
1.227 brouard 15047: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
15048: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 15049:
1.201 brouard 15050: strcpy(filerescve,"CVE_");
15051: strcat(filerescve,fileresu);
1.126 brouard 15052: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 15053: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
15054: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 15055: }
1.227 brouard 15056: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
15057: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 15058:
1.201 brouard 15059: strcpy(fileresv,"V_");
15060: strcat(fileresv,fileresu);
1.126 brouard 15061: if((ficresvij=fopen(fileresv,"w"))==NULL) {
15062: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
15063: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
15064: }
1.227 brouard 15065: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
15066: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 15067:
1.235 brouard 15068: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
15069: if (cptcovn < 1){i1=1;}
15070:
1.334 brouard 15071: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
15072: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
15073: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
15074: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
15075: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
15076: /* */
15077: 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 15078: continue;
1.350 brouard 15079: printf("\n# model %s \n#****** Result for:", model); /* HERE model is empty */
1.321 brouard 15080: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
15081: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 15082: /* It might not be a good idea to mix dummies and quantitative */
15083: /* 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 *\/ */
15084: 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 */
15085: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
15086: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
15087: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
15088: * (V5 is quanti) V4 and V3 are dummies
15089: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
15090: * l=1 l=2
15091: * k=1 1 1 0 0
15092: * k=2 2 1 1 0
15093: * k=3 [1] [2] 0 1
15094: * k=4 2 2 1 1
15095: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
15096: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
15097: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
15098: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
15099: */
15100: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
15101: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
15102: /* We give up with the combinations!! */
1.342 brouard 15103: /* if(debugILK) */
15104: /* 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 15105:
15106: 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 15107: /* 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] */
15108: 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 */
15109: 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 */
15110: 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 15111: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15112: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15113: }else{
15114: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15115: }
15116: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15117: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15118: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15119: /* For each selected (single) quantitative value */
1.337 brouard 15120: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15121: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15122: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15123: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15124: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15125: }else{
15126: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15127: }
15128: }else{
15129: 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 */
15130: 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 */
15131: exit(1);
15132: }
1.335 brouard 15133: } /* End loop for each variable in the resultline */
1.334 brouard 15134: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15135: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15136: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15137: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15138: /* } */
1.208 brouard 15139: fprintf(ficrest,"******\n");
1.227 brouard 15140: fprintf(ficlog,"******\n");
15141: printf("******\n");
1.208 brouard 15142:
15143: fprintf(ficresstdeij,"\n#****** ");
15144: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15145: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15146: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15147: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15148: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15149: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15150: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15151: }
15152: 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 15153: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15154: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15155: }
1.208 brouard 15156: fprintf(ficresstdeij,"******\n");
15157: fprintf(ficrescveij,"******\n");
15158:
15159: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15160: /* pstamp(ficresvij); */
1.225 brouard 15161: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15162: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15163: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15164: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15165: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15166: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15167: }
1.208 brouard 15168: fprintf(ficresvij,"******\n");
15169:
15170: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15171: oldm=oldms;savm=savms;
1.235 brouard 15172: printf(" cvevsij ");
15173: fprintf(ficlog, " cvevsij ");
15174: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15175: printf(" end cvevsij \n ");
15176: fprintf(ficlog, " end cvevsij \n ");
15177:
15178: /*
15179: */
15180: /* goto endfree; */
15181:
15182: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15183: pstamp(ficrest);
15184:
1.269 brouard 15185: epj=vector(1,nlstate+1);
1.208 brouard 15186: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15187: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15188: cptcod= 0; /* To be deleted */
15189: printf("varevsij vpopbased=%d \n",vpopbased);
15190: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15191: 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 15192: 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 ");
15193: if(vpopbased==1)
15194: 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);
15195: else
1.288 brouard 15196: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15197: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15198: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15199: fprintf(ficrest,"\n");
15200: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15201: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15202: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15203: for(age=bage; age <=fage ;age++){
1.235 brouard 15204: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15205: if (vpopbased==1) {
15206: if(mobilav ==0){
15207: for(i=1; i<=nlstate;i++)
15208: prlim[i][i]=probs[(int)age][i][k];
15209: }else{ /* mobilav */
15210: for(i=1; i<=nlstate;i++)
15211: prlim[i][i]=mobaverage[(int)age][i][k];
15212: }
15213: }
1.219 brouard 15214:
1.227 brouard 15215: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15216: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15217: /* printf(" age %4.0f ",age); */
15218: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15219: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15220: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15221: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15222: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15223: }
15224: epj[nlstate+1] +=epj[j];
15225: }
15226: /* printf(" age %4.0f \n",age); */
1.219 brouard 15227:
1.227 brouard 15228: for(i=1, vepp=0.;i <=nlstate;i++)
15229: for(j=1;j <=nlstate;j++)
15230: vepp += vareij[i][j][(int)age];
15231: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15232: for(j=1;j <=nlstate;j++){
15233: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15234: }
15235: fprintf(ficrest,"\n");
15236: }
1.208 brouard 15237: } /* End vpopbased */
1.269 brouard 15238: free_vector(epj,1,nlstate+1);
1.208 brouard 15239: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15240: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15241: printf("done selection\n");fflush(stdout);
15242: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15243:
1.335 brouard 15244: } /* End k selection or end covariate selection for nres */
1.227 brouard 15245:
15246: printf("done State-specific expectancies\n");fflush(stdout);
15247: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15248:
1.335 brouard 15249: /* variance-covariance of forward period prevalence */
1.269 brouard 15250: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15251:
1.227 brouard 15252:
1.290 brouard 15253: free_vector(weight,firstobs,lastobs);
1.351 brouard 15254: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 15255: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15256: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15257: free_matrix(anint,1,maxwav,firstobs,lastobs);
15258: free_matrix(mint,1,maxwav,firstobs,lastobs);
15259: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15260: free_ivector(tab,1,NCOVMAX);
15261: fclose(ficresstdeij);
15262: fclose(ficrescveij);
15263: fclose(ficresvij);
15264: fclose(ficrest);
15265: fclose(ficpar);
15266:
15267:
1.126 brouard 15268: /*---------- End : free ----------------*/
1.219 brouard 15269: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15270: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15271: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15272: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15273: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15274: } /* mle==-3 arrives here for freeing */
1.227 brouard 15275: /* endfree:*/
15276: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15277: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15278: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15279: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15280: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15281: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15282: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15283: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15284: free_matrix(matcov,1,npar,1,npar);
15285: free_matrix(hess,1,npar,1,npar);
15286: /*free_vector(delti,1,npar);*/
15287: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15288: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15289: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15290: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15291:
15292: free_ivector(ncodemax,1,NCOVMAX);
15293: free_ivector(ncodemaxwundef,1,NCOVMAX);
15294: free_ivector(Dummy,-1,NCOVMAX);
15295: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 15296: free_ivector(DummyV,-1,NCOVMAX);
15297: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15298: free_ivector(Typevar,-1,NCOVMAX);
15299: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15300: free_ivector(TvarsQ,1,NCOVMAX);
15301: free_ivector(TvarsQind,1,NCOVMAX);
15302: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15303: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15304: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15305: free_ivector(TvarFD,1,NCOVMAX);
15306: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15307: free_ivector(TvarF,1,NCOVMAX);
15308: free_ivector(TvarFind,1,NCOVMAX);
15309: free_ivector(TvarV,1,NCOVMAX);
15310: free_ivector(TvarVind,1,NCOVMAX);
15311: free_ivector(TvarA,1,NCOVMAX);
15312: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15313: free_ivector(TvarFQ,1,NCOVMAX);
15314: free_ivector(TvarFQind,1,NCOVMAX);
15315: free_ivector(TvarVD,1,NCOVMAX);
15316: free_ivector(TvarVDind,1,NCOVMAX);
15317: free_ivector(TvarVQ,1,NCOVMAX);
15318: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 15319: free_ivector(TvarAVVA,1,NCOVMAX);
15320: free_ivector(TvarAVVAind,1,NCOVMAX);
15321: free_ivector(TvarVVA,1,NCOVMAX);
15322: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15323: free_ivector(TvarVV,1,NCOVMAX);
15324: free_ivector(TvarVVind,1,NCOVMAX);
15325:
1.230 brouard 15326: free_ivector(Tvarsel,1,NCOVMAX);
15327: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15328: free_ivector(Tposprod,1,NCOVMAX);
15329: free_ivector(Tprod,1,NCOVMAX);
15330: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15331: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15332: free_ivector(Tage,1,NCOVMAX);
15333: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15334: free_ivector(TmodelInvind,1,NCOVMAX);
15335: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15336:
15337: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15338:
1.227 brouard 15339: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15340: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15341: fflush(fichtm);
15342: fflush(ficgp);
15343:
1.227 brouard 15344:
1.126 brouard 15345: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15346: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15347: 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 15348: }else{
15349: printf("End of Imach\n");
15350: fprintf(ficlog,"End of Imach\n");
15351: }
15352: printf("See log file on %s\n",filelog);
15353: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15354: /*(void) gettimeofday(&end_time,&tzp);*/
15355: rend_time = time(NULL);
15356: end_time = *localtime(&rend_time);
15357: /* tml = *localtime(&end_time.tm_sec); */
15358: strcpy(strtend,asctime(&end_time));
1.126 brouard 15359: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15360: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15361: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15362:
1.157 brouard 15363: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15364: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15365: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15366: /* printf("Total time was %d uSec.\n", total_usecs);*/
15367: /* if(fileappend(fichtm,optionfilehtm)){ */
15368: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15369: fclose(fichtm);
15370: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15371: fclose(fichtmcov);
15372: fclose(ficgp);
15373: fclose(ficlog);
15374: /*------ End -----------*/
1.227 brouard 15375:
1.281 brouard 15376:
15377: /* Executes gnuplot */
1.227 brouard 15378:
15379: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15380: #ifdef WIN32
1.227 brouard 15381: if (_chdir(pathcd) != 0)
15382: printf("Can't move to directory %s!\n",path);
15383: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15384: #else
1.227 brouard 15385: if(chdir(pathcd) != 0)
15386: printf("Can't move to directory %s!\n", path);
15387: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15388: #endif
1.126 brouard 15389: printf("Current directory %s!\n",pathcd);
15390: /*strcat(plotcmd,CHARSEPARATOR);*/
15391: sprintf(plotcmd,"gnuplot");
1.157 brouard 15392: #ifdef _WIN32
1.126 brouard 15393: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15394: #endif
15395: if(!stat(plotcmd,&info)){
1.158 brouard 15396: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15397: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15398: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15399: }else
15400: strcpy(pplotcmd,plotcmd);
1.157 brouard 15401: #ifdef __unix
1.126 brouard 15402: strcpy(plotcmd,GNUPLOTPROGRAM);
15403: if(!stat(plotcmd,&info)){
1.158 brouard 15404: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15405: }else
15406: strcpy(pplotcmd,plotcmd);
15407: #endif
15408: }else
15409: strcpy(pplotcmd,plotcmd);
15410:
15411: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15412: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15413: strcpy(pplotcmd,plotcmd);
1.227 brouard 15414:
1.126 brouard 15415: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15416: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15417: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15418: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15419: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15420: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15421: strcpy(plotcmd,pplotcmd);
15422: }
1.126 brouard 15423: }
1.158 brouard 15424: printf(" Successful, please wait...");
1.126 brouard 15425: while (z[0] != 'q') {
15426: /* chdir(path); */
1.154 brouard 15427: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15428: scanf("%s",z);
15429: /* if (z[0] == 'c') system("./imach"); */
15430: if (z[0] == 'e') {
1.158 brouard 15431: #ifdef __APPLE__
1.152 brouard 15432: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15433: #elif __linux
15434: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15435: #else
1.152 brouard 15436: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15437: #endif
15438: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15439: system(pplotcmd);
1.126 brouard 15440: }
15441: else if (z[0] == 'g') system(plotcmd);
15442: else if (z[0] == 'q') exit(0);
15443: }
1.227 brouard 15444: end:
1.126 brouard 15445: while (z[0] != 'q') {
1.195 brouard 15446: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15447: scanf("%s",z);
15448: }
1.283 brouard 15449: printf("End\n");
1.282 brouard 15450: exit(0);
1.126 brouard 15451: }
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