Annotation of imach/src/imach.c, revision 1.352
1.352 ! brouard 1: /* $Id: imach.c,v 1.351 2023/04/29 10:43:47 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.352 ! brouard 4: Revision 1.351 2023/04/29 10:43:47 brouard
! 5: Summary: 099r45
! 6:
1.351 brouard 7: Revision 1.350 2023/04/24 11:38:06 brouard
8: *** empty log message ***
9:
1.350 brouard 10: Revision 1.349 2023/01/31 09:19:37 brouard
11: Summary: Improvements in models with age*Vn*Vm
12:
1.348 brouard 13: Revision 1.347 2022/09/18 14:36:44 brouard
14: Summary: version 0.99r42
15:
1.347 brouard 16: Revision 1.346 2022/09/16 13:52:36 brouard
17: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
18:
1.346 brouard 19: Revision 1.345 2022/09/16 13:40:11 brouard
20: Summary: Version 0.99r41
21:
22: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
23:
1.345 brouard 24: Revision 1.344 2022/09/14 19:33:30 brouard
25: Summary: version 0.99r40
26:
27: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
28:
1.344 brouard 29: Revision 1.343 2022/09/14 14:22:16 brouard
30: Summary: version 0.99r39
31:
32: * imach.c (Module): Version 0.99r39 with colored dummy covariates
33: (fixed or time varying), using new last columns of
34: ILK_parameter.txt file.
35:
1.343 brouard 36: Revision 1.342 2022/09/11 19:54:09 brouard
37: Summary: 0.99r38
38:
39: * imach.c (Module): Adding timevarying products of any kinds,
40: should work before shifting cotvar from ncovcol+nqv columns in
41: order to have a correspondance between the column of cotvar and
42: the id of column.
43: (Module): Some cleaning and adding covariates in ILK.txt
44:
1.342 brouard 45: Revision 1.341 2022/09/11 07:58:42 brouard
46: Summary: Version 0.99r38
47:
48: After adding change in cotvar.
49:
1.341 brouard 50: Revision 1.340 2022/09/11 07:53:11 brouard
51: Summary: Version imach 0.99r37
52:
53: * imach.c (Module): Adding timevarying products of any kinds,
54: should work before shifting cotvar from ncovcol+nqv columns in
55: order to have a correspondance between the column of cotvar and
56: the id of column.
57:
1.340 brouard 58: Revision 1.339 2022/09/09 17:55:22 brouard
59: Summary: version 0.99r37
60:
61: * imach.c (Module): Many improvements for fixing products of fixed
62: timevarying as well as fixed * fixed, and test with quantitative
63: covariate.
64:
1.339 brouard 65: Revision 1.338 2022/09/04 17:40:33 brouard
66: Summary: 0.99r36
67:
68: * imach.c (Module): Now the easy runs i.e. without result or
69: model=1+age only did not work. The defautl combination should be 1
70: and not 0 because everything hasn't been tranformed yet.
71:
1.338 brouard 72: Revision 1.337 2022/09/02 14:26:02 brouard
73: Summary: version 0.99r35
74:
75: * src/imach.c: Version 0.99r35 because it outputs same results with
76: 1+age+V1+V1*age for females and 1+age for females only
77: (education=1 noweight)
78:
1.337 brouard 79: Revision 1.336 2022/08/31 09:52:36 brouard
80: *** empty log message ***
81:
1.336 brouard 82: Revision 1.335 2022/08/31 08:23:16 brouard
83: Summary: improvements...
84:
1.335 brouard 85: Revision 1.334 2022/08/25 09:08:41 brouard
86: Summary: In progress for quantitative
87:
1.334 brouard 88: Revision 1.333 2022/08/21 09:10:30 brouard
89: * src/imach.c (Module): Version 0.99r33 A lot of changes in
90: reassigning covariates: my first idea was that people will always
91: use the first covariate V1 into the model but in fact they are
92: producing data with many covariates and can use an equation model
93: with some of the covariate; it means that in a model V2+V3 instead
94: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
95: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
96: the equation model is restricted to two variables only (V2, V3)
97: and the combination for V2 should be codtabm(k,1) instead of
98: (codtabm(k,2), and the code should be
99: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
100: made. All of these should be simplified once a day like we did in
101: hpxij() for example by using precov[nres] which is computed in
102: decoderesult for each nres of each resultline. Loop should be done
103: on the equation model globally by distinguishing only product with
104: age (which are changing with age) and no more on type of
105: covariates, single dummies, single covariates.
106:
1.333 brouard 107: Revision 1.332 2022/08/21 09:06:25 brouard
108: Summary: Version 0.99r33
109:
110: * src/imach.c (Module): Version 0.99r33 A lot of changes in
111: reassigning covariates: my first idea was that people will always
112: use the first covariate V1 into the model but in fact they are
113: producing data with many covariates and can use an equation model
114: with some of the covariate; it means that in a model V2+V3 instead
115: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
116: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
117: the equation model is restricted to two variables only (V2, V3)
118: and the combination for V2 should be codtabm(k,1) instead of
119: (codtabm(k,2), and the code should be
120: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
121: made. All of these should be simplified once a day like we did in
122: hpxij() for example by using precov[nres] which is computed in
123: decoderesult for each nres of each resultline. Loop should be done
124: on the equation model globally by distinguishing only product with
125: age (which are changing with age) and no more on type of
126: covariates, single dummies, single covariates.
127:
1.332 brouard 128: Revision 1.331 2022/08/07 05:40:09 brouard
129: *** empty log message ***
130:
1.331 brouard 131: Revision 1.330 2022/08/06 07:18:25 brouard
132: Summary: last 0.99r31
133:
134: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
135:
1.330 brouard 136: Revision 1.329 2022/08/03 17:29:54 brouard
137: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
138:
1.329 brouard 139: Revision 1.328 2022/07/27 17:40:48 brouard
140: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
141:
1.328 brouard 142: Revision 1.327 2022/07/27 14:47:35 brouard
143: Summary: Still a problem for one-step probabilities in case of quantitative variables
144:
1.327 brouard 145: Revision 1.326 2022/07/26 17:33:55 brouard
146: Summary: some test with nres=1
147:
1.326 brouard 148: Revision 1.325 2022/07/25 14:27:23 brouard
149: Summary: r30
150:
151: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
152: coredumped, revealed by Feiuno, thank you.
153:
1.325 brouard 154: Revision 1.324 2022/07/23 17:44:26 brouard
155: *** empty log message ***
156:
1.324 brouard 157: Revision 1.323 2022/07/22 12:30:08 brouard
158: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
159:
1.323 brouard 160: Revision 1.322 2022/07/22 12:27:48 brouard
161: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
162:
1.322 brouard 163: Revision 1.321 2022/07/22 12:04:24 brouard
164: Summary: r28
165:
166: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
167:
1.321 brouard 168: Revision 1.320 2022/06/02 05:10:11 brouard
169: *** empty log message ***
170:
1.320 brouard 171: Revision 1.319 2022/06/02 04:45:11 brouard
172: * imach.c (Module): Adding the Wald tests from the log to the main
173: htm for better display of the maximum likelihood estimators.
174:
1.319 brouard 175: Revision 1.318 2022/05/24 08:10:59 brouard
176: * imach.c (Module): Some attempts to find a bug of wrong estimates
177: of confidencce intervals with product in the equation modelC
178:
1.318 brouard 179: Revision 1.317 2022/05/15 15:06:23 brouard
180: * imach.c (Module): Some minor improvements
181:
1.317 brouard 182: Revision 1.316 2022/05/11 15:11:31 brouard
183: Summary: r27
184:
1.316 brouard 185: Revision 1.315 2022/05/11 15:06:32 brouard
186: *** empty log message ***
187:
1.315 brouard 188: Revision 1.314 2022/04/13 17:43:09 brouard
189: * imach.c (Module): Adding link to text data files
190:
1.314 brouard 191: Revision 1.313 2022/04/11 15:57:42 brouard
192: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
193:
1.313 brouard 194: Revision 1.312 2022/04/05 21:24:39 brouard
195: *** empty log message ***
196:
1.312 brouard 197: Revision 1.311 2022/04/05 21:03:51 brouard
198: Summary: Fixed quantitative covariates
199:
200: Fixed covariates (dummy or quantitative)
201: with missing values have never been allowed but are ERRORS and
202: program quits. Standard deviations of fixed covariates were
203: wrongly computed. Mean and standard deviations of time varying
204: covariates are still not computed.
205:
1.311 brouard 206: Revision 1.310 2022/03/17 08:45:53 brouard
207: Summary: 99r25
208:
209: Improving detection of errors: result lines should be compatible with
210: the model.
211:
1.310 brouard 212: Revision 1.309 2021/05/20 12:39:14 brouard
213: Summary: Version 0.99r24
214:
1.309 brouard 215: Revision 1.308 2021/03/31 13:11:57 brouard
216: Summary: Version 0.99r23
217:
218:
219: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
220:
1.308 brouard 221: Revision 1.307 2021/03/08 18:11:32 brouard
222: Summary: 0.99r22 fixed bug on result:
223:
1.307 brouard 224: Revision 1.306 2021/02/20 15:44:02 brouard
225: Summary: Version 0.99r21
226:
227: * imach.c (Module): Fix bug on quitting after result lines!
228: (Module): Version 0.99r21
229:
1.306 brouard 230: Revision 1.305 2021/02/20 15:28:30 brouard
231: * imach.c (Module): Fix bug on quitting after result lines!
232:
1.305 brouard 233: Revision 1.304 2021/02/12 11:34:20 brouard
234: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
235:
1.304 brouard 236: Revision 1.303 2021/02/11 19:50:15 brouard
237: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
238:
1.303 brouard 239: Revision 1.302 2020/02/22 21:00:05 brouard
240: * (Module): imach.c Update mle=-3 (for computing Life expectancy
241: and life table from the data without any state)
242:
1.302 brouard 243: Revision 1.301 2019/06/04 13:51:20 brouard
244: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
245:
1.301 brouard 246: Revision 1.300 2019/05/22 19:09:45 brouard
247: Summary: version 0.99r19 of May 2019
248:
1.300 brouard 249: Revision 1.299 2019/05/22 18:37:08 brouard
250: Summary: Cleaned 0.99r19
251:
1.299 brouard 252: Revision 1.298 2019/05/22 18:19:56 brouard
253: *** empty log message ***
254:
1.298 brouard 255: Revision 1.297 2019/05/22 17:56:10 brouard
256: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
257:
1.297 brouard 258: Revision 1.296 2019/05/20 13:03:18 brouard
259: Summary: Projection syntax simplified
260:
261:
262: We can now start projections, forward or backward, from the mean date
263: of inteviews up to or down to a number of years of projection:
264: prevforecast=1 yearsfproj=15.3 mobil_average=0
265: or
266: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
267: or
268: prevbackcast=1 yearsbproj=12.3 mobil_average=1
269: or
270: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
271:
1.296 brouard 272: Revision 1.295 2019/05/18 09:52:50 brouard
273: Summary: doxygen tex bug
274:
1.295 brouard 275: Revision 1.294 2019/05/16 14:54:33 brouard
276: Summary: There was some wrong lines added
277:
1.294 brouard 278: Revision 1.293 2019/05/09 15:17:34 brouard
279: *** empty log message ***
280:
1.293 brouard 281: Revision 1.292 2019/05/09 14:17:20 brouard
282: Summary: Some updates
283:
1.292 brouard 284: Revision 1.291 2019/05/09 13:44:18 brouard
285: Summary: Before ncovmax
286:
1.291 brouard 287: Revision 1.290 2019/05/09 13:39:37 brouard
288: Summary: 0.99r18 unlimited number of individuals
289:
290: 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.
291:
1.290 brouard 292: Revision 1.289 2018/12/13 09:16:26 brouard
293: Summary: Bug for young ages (<-30) will be in r17
294:
1.289 brouard 295: Revision 1.288 2018/05/02 20:58:27 brouard
296: Summary: Some bugs fixed
297:
1.288 brouard 298: Revision 1.287 2018/05/01 17:57:25 brouard
299: Summary: Bug fixed by providing frequencies only for non missing covariates
300:
1.287 brouard 301: Revision 1.286 2018/04/27 14:27:04 brouard
302: Summary: some minor bugs
303:
1.286 brouard 304: Revision 1.285 2018/04/21 21:02:16 brouard
305: Summary: Some bugs fixed, valgrind tested
306:
1.285 brouard 307: Revision 1.284 2018/04/20 05:22:13 brouard
308: Summary: Computing mean and stdeviation of fixed quantitative variables
309:
1.284 brouard 310: Revision 1.283 2018/04/19 14:49:16 brouard
311: Summary: Some minor bugs fixed
312:
1.283 brouard 313: Revision 1.282 2018/02/27 22:50:02 brouard
314: *** empty log message ***
315:
1.282 brouard 316: Revision 1.281 2018/02/27 19:25:23 brouard
317: Summary: Adding second argument for quitting
318:
1.281 brouard 319: Revision 1.280 2018/02/21 07:58:13 brouard
320: Summary: 0.99r15
321:
322: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
323:
1.280 brouard 324: Revision 1.279 2017/07/20 13:35:01 brouard
325: Summary: temporary working
326:
1.279 brouard 327: Revision 1.278 2017/07/19 14:09:02 brouard
328: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
329:
1.278 brouard 330: Revision 1.277 2017/07/17 08:53:49 brouard
331: Summary: BOM files can be read now
332:
1.277 brouard 333: Revision 1.276 2017/06/30 15:48:31 brouard
334: Summary: Graphs improvements
335:
1.276 brouard 336: Revision 1.275 2017/06/30 13:39:33 brouard
337: Summary: Saito's color
338:
1.275 brouard 339: Revision 1.274 2017/06/29 09:47:08 brouard
340: Summary: Version 0.99r14
341:
1.274 brouard 342: Revision 1.273 2017/06/27 11:06:02 brouard
343: Summary: More documentation on projections
344:
1.273 brouard 345: Revision 1.272 2017/06/27 10:22:40 brouard
346: Summary: Color of backprojection changed from 6 to 5(yellow)
347:
1.272 brouard 348: Revision 1.271 2017/06/27 10:17:50 brouard
349: Summary: Some bug with rint
350:
1.271 brouard 351: Revision 1.270 2017/05/24 05:45:29 brouard
352: *** empty log message ***
353:
1.270 brouard 354: Revision 1.269 2017/05/23 08:39:25 brouard
355: Summary: Code into subroutine, cleanings
356:
1.269 brouard 357: Revision 1.268 2017/05/18 20:09:32 brouard
358: Summary: backprojection and confidence intervals of backprevalence
359:
1.268 brouard 360: Revision 1.267 2017/05/13 10:25:05 brouard
361: Summary: temporary save for backprojection
362:
1.267 brouard 363: Revision 1.266 2017/05/13 07:26:12 brouard
364: Summary: Version 0.99r13 (improvements and bugs fixed)
365:
1.266 brouard 366: Revision 1.265 2017/04/26 16:22:11 brouard
367: Summary: imach 0.99r13 Some bugs fixed
368:
1.265 brouard 369: Revision 1.264 2017/04/26 06:01:29 brouard
370: Summary: Labels in graphs
371:
1.264 brouard 372: Revision 1.263 2017/04/24 15:23:15 brouard
373: Summary: to save
374:
1.263 brouard 375: Revision 1.262 2017/04/18 16:48:12 brouard
376: *** empty log message ***
377:
1.262 brouard 378: Revision 1.261 2017/04/05 10:14:09 brouard
379: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
380:
1.261 brouard 381: Revision 1.260 2017/04/04 17:46:59 brouard
382: Summary: Gnuplot indexations fixed (humm)
383:
1.260 brouard 384: Revision 1.259 2017/04/04 13:01:16 brouard
385: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
386:
1.259 brouard 387: Revision 1.258 2017/04/03 10:17:47 brouard
388: Summary: Version 0.99r12
389:
390: Some cleanings, conformed with updated documentation.
391:
1.258 brouard 392: Revision 1.257 2017/03/29 16:53:30 brouard
393: Summary: Temp
394:
1.257 brouard 395: Revision 1.256 2017/03/27 05:50:23 brouard
396: Summary: Temporary
397:
1.256 brouard 398: Revision 1.255 2017/03/08 16:02:28 brouard
399: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
400:
1.255 brouard 401: Revision 1.254 2017/03/08 07:13:00 brouard
402: Summary: Fixing data parameter line
403:
1.254 brouard 404: Revision 1.253 2016/12/15 11:59:41 brouard
405: Summary: 0.99 in progress
406:
1.253 brouard 407: Revision 1.252 2016/09/15 21:15:37 brouard
408: *** empty log message ***
409:
1.252 brouard 410: Revision 1.251 2016/09/15 15:01:13 brouard
411: Summary: not working
412:
1.251 brouard 413: Revision 1.250 2016/09/08 16:07:27 brouard
414: Summary: continue
415:
1.250 brouard 416: Revision 1.249 2016/09/07 17:14:18 brouard
417: Summary: Starting values from frequencies
418:
1.249 brouard 419: Revision 1.248 2016/09/07 14:10:18 brouard
420: *** empty log message ***
421:
1.248 brouard 422: Revision 1.247 2016/09/02 11:11:21 brouard
423: *** empty log message ***
424:
1.247 brouard 425: Revision 1.246 2016/09/02 08:49:22 brouard
426: *** empty log message ***
427:
1.246 brouard 428: Revision 1.245 2016/09/02 07:25:01 brouard
429: *** empty log message ***
430:
1.245 brouard 431: Revision 1.244 2016/09/02 07:17:34 brouard
432: *** empty log message ***
433:
1.244 brouard 434: Revision 1.243 2016/09/02 06:45:35 brouard
435: *** empty log message ***
436:
1.243 brouard 437: Revision 1.242 2016/08/30 15:01:20 brouard
438: Summary: Fixing a lots
439:
1.242 brouard 440: Revision 1.241 2016/08/29 17:17:25 brouard
441: Summary: gnuplot problem in Back projection to fix
442:
1.241 brouard 443: Revision 1.240 2016/08/29 07:53:18 brouard
444: Summary: Better
445:
1.240 brouard 446: Revision 1.239 2016/08/26 15:51:03 brouard
447: Summary: Improvement in Powell output in order to copy and paste
448:
449: Author:
450:
1.239 brouard 451: Revision 1.238 2016/08/26 14:23:35 brouard
452: Summary: Starting tests of 0.99
453:
1.238 brouard 454: Revision 1.237 2016/08/26 09:20:19 brouard
455: Summary: to valgrind
456:
1.237 brouard 457: Revision 1.236 2016/08/25 10:50:18 brouard
458: *** empty log message ***
459:
1.236 brouard 460: Revision 1.235 2016/08/25 06:59:23 brouard
461: *** empty log message ***
462:
1.235 brouard 463: Revision 1.234 2016/08/23 16:51:20 brouard
464: *** empty log message ***
465:
1.234 brouard 466: Revision 1.233 2016/08/23 07:40:50 brouard
467: Summary: not working
468:
1.233 brouard 469: Revision 1.232 2016/08/22 14:20:21 brouard
470: Summary: not working
471:
1.232 brouard 472: Revision 1.231 2016/08/22 07:17:15 brouard
473: Summary: not working
474:
1.231 brouard 475: Revision 1.230 2016/08/22 06:55:53 brouard
476: Summary: Not working
477:
1.230 brouard 478: Revision 1.229 2016/07/23 09:45:53 brouard
479: Summary: Completing for func too
480:
1.229 brouard 481: Revision 1.228 2016/07/22 17:45:30 brouard
482: Summary: Fixing some arrays, still debugging
483:
1.227 brouard 484: Revision 1.226 2016/07/12 18:42:34 brouard
485: Summary: temp
486:
1.226 brouard 487: Revision 1.225 2016/07/12 08:40:03 brouard
488: Summary: saving but not running
489:
1.225 brouard 490: Revision 1.224 2016/07/01 13:16:01 brouard
491: Summary: Fixes
492:
1.224 brouard 493: Revision 1.223 2016/02/19 09:23:35 brouard
494: Summary: temporary
495:
1.223 brouard 496: Revision 1.222 2016/02/17 08:14:50 brouard
497: Summary: Probably last 0.98 stable version 0.98r6
498:
1.222 brouard 499: Revision 1.221 2016/02/15 23:35:36 brouard
500: Summary: minor bug
501:
1.220 brouard 502: Revision 1.219 2016/02/15 00:48:12 brouard
503: *** empty log message ***
504:
1.219 brouard 505: Revision 1.218 2016/02/12 11:29:23 brouard
506: Summary: 0.99 Back projections
507:
1.218 brouard 508: Revision 1.217 2015/12/23 17:18:31 brouard
509: Summary: Experimental backcast
510:
1.217 brouard 511: Revision 1.216 2015/12/18 17:32:11 brouard
512: Summary: 0.98r4 Warning and status=-2
513:
514: Version 0.98r4 is now:
515: - displaying an error when status is -1, date of interview unknown and date of death known;
516: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
517: Older changes concerning s=-2, dating from 2005 have been supersed.
518:
1.216 brouard 519: Revision 1.215 2015/12/16 08:52:24 brouard
520: Summary: 0.98r4 working
521:
1.215 brouard 522: Revision 1.214 2015/12/16 06:57:54 brouard
523: Summary: temporary not working
524:
1.214 brouard 525: Revision 1.213 2015/12/11 18:22:17 brouard
526: Summary: 0.98r4
527:
1.213 brouard 528: Revision 1.212 2015/11/21 12:47:24 brouard
529: Summary: minor typo
530:
1.212 brouard 531: Revision 1.211 2015/11/21 12:41:11 brouard
532: Summary: 0.98r3 with some graph of projected cross-sectional
533:
534: Author: Nicolas Brouard
535:
1.211 brouard 536: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 537: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 538: Summary: Adding ftolpl parameter
539: Author: N Brouard
540:
541: We had difficulties to get smoothed confidence intervals. It was due
542: to the period prevalence which wasn't computed accurately. The inner
543: parameter ftolpl is now an outer parameter of the .imach parameter
544: file after estepm. If ftolpl is small 1.e-4 and estepm too,
545: computation are long.
546:
1.209 brouard 547: Revision 1.208 2015/11/17 14:31:57 brouard
548: Summary: temporary
549:
1.208 brouard 550: Revision 1.207 2015/10/27 17:36:57 brouard
551: *** empty log message ***
552:
1.207 brouard 553: Revision 1.206 2015/10/24 07:14:11 brouard
554: *** empty log message ***
555:
1.206 brouard 556: Revision 1.205 2015/10/23 15:50:53 brouard
557: Summary: 0.98r3 some clarification for graphs on likelihood contributions
558:
1.205 brouard 559: Revision 1.204 2015/10/01 16:20:26 brouard
560: Summary: Some new graphs of contribution to likelihood
561:
1.204 brouard 562: Revision 1.203 2015/09/30 17:45:14 brouard
563: Summary: looking at better estimation of the hessian
564:
565: Also a better criteria for convergence to the period prevalence And
566: therefore adding the number of years needed to converge. (The
567: prevalence in any alive state shold sum to one
568:
1.203 brouard 569: Revision 1.202 2015/09/22 19:45:16 brouard
570: Summary: Adding some overall graph on contribution to likelihood. Might change
571:
1.202 brouard 572: Revision 1.201 2015/09/15 17:34:58 brouard
573: Summary: 0.98r0
574:
575: - Some new graphs like suvival functions
576: - Some bugs fixed like model=1+age+V2.
577:
1.201 brouard 578: Revision 1.200 2015/09/09 16:53:55 brouard
579: Summary: Big bug thanks to Flavia
580:
581: Even model=1+age+V2. did not work anymore
582:
1.200 brouard 583: Revision 1.199 2015/09/07 14:09:23 brouard
584: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
585:
1.199 brouard 586: Revision 1.198 2015/09/03 07:14:39 brouard
587: Summary: 0.98q5 Flavia
588:
1.198 brouard 589: Revision 1.197 2015/09/01 18:24:39 brouard
590: *** empty log message ***
591:
1.197 brouard 592: Revision 1.196 2015/08/18 23:17:52 brouard
593: Summary: 0.98q5
594:
1.196 brouard 595: Revision 1.195 2015/08/18 16:28:39 brouard
596: Summary: Adding a hack for testing purpose
597:
598: After reading the title, ftol and model lines, if the comment line has
599: a q, starting with #q, the answer at the end of the run is quit. It
600: permits to run test files in batch with ctest. The former workaround was
601: $ echo q | imach foo.imach
602:
1.195 brouard 603: Revision 1.194 2015/08/18 13:32:00 brouard
604: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
605:
1.194 brouard 606: Revision 1.193 2015/08/04 07:17:42 brouard
607: Summary: 0.98q4
608:
1.193 brouard 609: Revision 1.192 2015/07/16 16:49:02 brouard
610: Summary: Fixing some outputs
611:
1.192 brouard 612: Revision 1.191 2015/07/14 10:00:33 brouard
613: Summary: Some fixes
614:
1.191 brouard 615: Revision 1.190 2015/05/05 08:51:13 brouard
616: Summary: Adding digits in output parameters (7 digits instead of 6)
617:
618: Fix 1+age+.
619:
1.190 brouard 620: Revision 1.189 2015/04/30 14:45:16 brouard
621: Summary: 0.98q2
622:
1.189 brouard 623: Revision 1.188 2015/04/30 08:27:53 brouard
624: *** empty log message ***
625:
1.188 brouard 626: Revision 1.187 2015/04/29 09:11:15 brouard
627: *** empty log message ***
628:
1.187 brouard 629: Revision 1.186 2015/04/23 12:01:52 brouard
630: Summary: V1*age is working now, version 0.98q1
631:
632: Some codes had been disabled in order to simplify and Vn*age was
633: working in the optimization phase, ie, giving correct MLE parameters,
634: but, as usual, outputs were not correct and program core dumped.
635:
1.186 brouard 636: Revision 1.185 2015/03/11 13:26:42 brouard
637: Summary: Inclusion of compile and links command line for Intel Compiler
638:
1.185 brouard 639: Revision 1.184 2015/03/11 11:52:39 brouard
640: Summary: Back from Windows 8. Intel Compiler
641:
1.184 brouard 642: Revision 1.183 2015/03/10 20:34:32 brouard
643: Summary: 0.98q0, trying with directest, mnbrak fixed
644:
645: We use directest instead of original Powell test; probably no
646: incidence on the results, but better justifications;
647: We fixed Numerical Recipes mnbrak routine which was wrong and gave
648: wrong results.
649:
1.183 brouard 650: Revision 1.182 2015/02/12 08:19:57 brouard
651: Summary: Trying to keep directest which seems simpler and more general
652: Author: Nicolas Brouard
653:
1.182 brouard 654: Revision 1.181 2015/02/11 23:22:24 brouard
655: Summary: Comments on Powell added
656:
657: Author:
658:
1.181 brouard 659: Revision 1.180 2015/02/11 17:33:45 brouard
660: Summary: Finishing move from main to function (hpijx and prevalence_limit)
661:
1.180 brouard 662: Revision 1.179 2015/01/04 09:57:06 brouard
663: Summary: back to OS/X
664:
1.179 brouard 665: Revision 1.178 2015/01/04 09:35:48 brouard
666: *** empty log message ***
667:
1.178 brouard 668: Revision 1.177 2015/01/03 18:40:56 brouard
669: Summary: Still testing ilc32 on OSX
670:
1.177 brouard 671: Revision 1.176 2015/01/03 16:45:04 brouard
672: *** empty log message ***
673:
1.176 brouard 674: Revision 1.175 2015/01/03 16:33:42 brouard
675: *** empty log message ***
676:
1.175 brouard 677: Revision 1.174 2015/01/03 16:15:49 brouard
678: Summary: Still in cross-compilation
679:
1.174 brouard 680: Revision 1.173 2015/01/03 12:06:26 brouard
681: Summary: trying to detect cross-compilation
682:
1.173 brouard 683: Revision 1.172 2014/12/27 12:07:47 brouard
684: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
685:
1.172 brouard 686: Revision 1.171 2014/12/23 13:26:59 brouard
687: Summary: Back from Visual C
688:
689: Still problem with utsname.h on Windows
690:
1.171 brouard 691: Revision 1.170 2014/12/23 11:17:12 brouard
692: Summary: Cleaning some \%% back to %%
693:
694: The escape was mandatory for a specific compiler (which one?), but too many warnings.
695:
1.170 brouard 696: Revision 1.169 2014/12/22 23:08:31 brouard
697: Summary: 0.98p
698:
699: Outputs some informations on compiler used, OS etc. Testing on different platforms.
700:
1.169 brouard 701: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 702: Summary: update
1.169 brouard 703:
1.168 brouard 704: Revision 1.167 2014/12/22 13:50:56 brouard
705: Summary: Testing uname and compiler version and if compiled 32 or 64
706:
707: Testing on Linux 64
708:
1.167 brouard 709: Revision 1.166 2014/12/22 11:40:47 brouard
710: *** empty log message ***
711:
1.166 brouard 712: Revision 1.165 2014/12/16 11:20:36 brouard
713: Summary: After compiling on Visual C
714:
715: * imach.c (Module): Merging 1.61 to 1.162
716:
1.165 brouard 717: Revision 1.164 2014/12/16 10:52:11 brouard
718: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
719:
720: * imach.c (Module): Merging 1.61 to 1.162
721:
1.164 brouard 722: Revision 1.163 2014/12/16 10:30:11 brouard
723: * imach.c (Module): Merging 1.61 to 1.162
724:
1.163 brouard 725: Revision 1.162 2014/09/25 11:43:39 brouard
726: Summary: temporary backup 0.99!
727:
1.162 brouard 728: Revision 1.1 2014/09/16 11:06:58 brouard
729: Summary: With some code (wrong) for nlopt
730:
731: Author:
732:
733: Revision 1.161 2014/09/15 20:41:41 brouard
734: Summary: Problem with macro SQR on Intel compiler
735:
1.161 brouard 736: Revision 1.160 2014/09/02 09:24:05 brouard
737: *** empty log message ***
738:
1.160 brouard 739: Revision 1.159 2014/09/01 10:34:10 brouard
740: Summary: WIN32
741: Author: Brouard
742:
1.159 brouard 743: Revision 1.158 2014/08/27 17:11:51 brouard
744: *** empty log message ***
745:
1.158 brouard 746: Revision 1.157 2014/08/27 16:26:55 brouard
747: Summary: Preparing windows Visual studio version
748: Author: Brouard
749:
750: In order to compile on Visual studio, time.h is now correct and time_t
751: and tm struct should be used. difftime should be used but sometimes I
752: just make the differences in raw time format (time(&now).
753: Trying to suppress #ifdef LINUX
754: Add xdg-open for __linux in order to open default browser.
755:
1.157 brouard 756: Revision 1.156 2014/08/25 20:10:10 brouard
757: *** empty log message ***
758:
1.156 brouard 759: Revision 1.155 2014/08/25 18:32:34 brouard
760: Summary: New compile, minor changes
761: Author: Brouard
762:
1.155 brouard 763: Revision 1.154 2014/06/20 17:32:08 brouard
764: Summary: Outputs now all graphs of convergence to period prevalence
765:
1.154 brouard 766: Revision 1.153 2014/06/20 16:45:46 brouard
767: Summary: If 3 live state, convergence to period prevalence on same graph
768: Author: Brouard
769:
1.153 brouard 770: Revision 1.152 2014/06/18 17:54:09 brouard
771: Summary: open browser, use gnuplot on same dir than imach if not found in the path
772:
1.152 brouard 773: Revision 1.151 2014/06/18 16:43:30 brouard
774: *** empty log message ***
775:
1.151 brouard 776: Revision 1.150 2014/06/18 16:42:35 brouard
777: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
778: Author: brouard
779:
1.150 brouard 780: Revision 1.149 2014/06/18 15:51:14 brouard
781: Summary: Some fixes in parameter files errors
782: Author: Nicolas Brouard
783:
1.149 brouard 784: Revision 1.148 2014/06/17 17:38:48 brouard
785: Summary: Nothing new
786: Author: Brouard
787:
788: Just a new packaging for OS/X version 0.98nS
789:
1.148 brouard 790: Revision 1.147 2014/06/16 10:33:11 brouard
791: *** empty log message ***
792:
1.147 brouard 793: Revision 1.146 2014/06/16 10:20:28 brouard
794: Summary: Merge
795: Author: Brouard
796:
797: Merge, before building revised version.
798:
1.146 brouard 799: Revision 1.145 2014/06/10 21:23:15 brouard
800: Summary: Debugging with valgrind
801: Author: Nicolas Brouard
802:
803: Lot of changes in order to output the results with some covariates
804: After the Edimburgh REVES conference 2014, it seems mandatory to
805: improve the code.
806: No more memory valgrind error but a lot has to be done in order to
807: continue the work of splitting the code into subroutines.
808: Also, decodemodel has been improved. Tricode is still not
809: optimal. nbcode should be improved. Documentation has been added in
810: the source code.
811:
1.144 brouard 812: Revision 1.143 2014/01/26 09:45:38 brouard
813: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
814:
815: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
816: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
817:
1.143 brouard 818: Revision 1.142 2014/01/26 03:57:36 brouard
819: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
820:
821: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
822:
1.142 brouard 823: Revision 1.141 2014/01/26 02:42:01 brouard
824: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
825:
1.141 brouard 826: Revision 1.140 2011/09/02 10:37:54 brouard
827: Summary: times.h is ok with mingw32 now.
828:
1.140 brouard 829: Revision 1.139 2010/06/14 07:50:17 brouard
830: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
831: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
832:
1.139 brouard 833: Revision 1.138 2010/04/30 18:19:40 brouard
834: *** empty log message ***
835:
1.138 brouard 836: Revision 1.137 2010/04/29 18:11:38 brouard
837: (Module): Checking covariates for more complex models
838: than V1+V2. A lot of change to be done. Unstable.
839:
1.137 brouard 840: Revision 1.136 2010/04/26 20:30:53 brouard
841: (Module): merging some libgsl code. Fixing computation
842: of likelione (using inter/intrapolation if mle = 0) in order to
843: get same likelihood as if mle=1.
844: Some cleaning of code and comments added.
845:
1.136 brouard 846: Revision 1.135 2009/10/29 15:33:14 brouard
847: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
848:
1.135 brouard 849: Revision 1.134 2009/10/29 13:18:53 brouard
850: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
851:
1.134 brouard 852: Revision 1.133 2009/07/06 10:21:25 brouard
853: just nforces
854:
1.133 brouard 855: Revision 1.132 2009/07/06 08:22:05 brouard
856: Many tings
857:
1.132 brouard 858: Revision 1.131 2009/06/20 16:22:47 brouard
859: Some dimensions resccaled
860:
1.131 brouard 861: Revision 1.130 2009/05/26 06:44:34 brouard
862: (Module): Max Covariate is now set to 20 instead of 8. A
863: lot of cleaning with variables initialized to 0. Trying to make
864: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
865:
1.130 brouard 866: Revision 1.129 2007/08/31 13:49:27 lievre
867: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
868:
1.129 lievre 869: Revision 1.128 2006/06/30 13:02:05 brouard
870: (Module): Clarifications on computing e.j
871:
1.128 brouard 872: Revision 1.127 2006/04/28 18:11:50 brouard
873: (Module): Yes the sum of survivors was wrong since
874: imach-114 because nhstepm was no more computed in the age
875: loop. Now we define nhstepma in the age loop.
876: (Module): In order to speed up (in case of numerous covariates) we
877: compute health expectancies (without variances) in a first step
878: and then all the health expectancies with variances or standard
879: deviation (needs data from the Hessian matrices) which slows the
880: computation.
881: In the future we should be able to stop the program is only health
882: expectancies and graph are needed without standard deviations.
883:
1.127 brouard 884: Revision 1.126 2006/04/28 17:23:28 brouard
885: (Module): Yes the sum of survivors was wrong since
886: imach-114 because nhstepm was no more computed in the age
887: loop. Now we define nhstepma in the age loop.
888: Version 0.98h
889:
1.126 brouard 890: Revision 1.125 2006/04/04 15:20:31 lievre
891: Errors in calculation of health expectancies. Age was not initialized.
892: Forecasting file added.
893:
894: Revision 1.124 2006/03/22 17:13:53 lievre
895: Parameters are printed with %lf instead of %f (more numbers after the comma).
896: The log-likelihood is printed in the log file
897:
898: Revision 1.123 2006/03/20 10:52:43 brouard
899: * imach.c (Module): <title> changed, corresponds to .htm file
900: name. <head> headers where missing.
901:
902: * imach.c (Module): Weights can have a decimal point as for
903: English (a comma might work with a correct LC_NUMERIC environment,
904: otherwise the weight is truncated).
905: Modification of warning when the covariates values are not 0 or
906: 1.
907: Version 0.98g
908:
909: Revision 1.122 2006/03/20 09:45:41 brouard
910: (Module): Weights can have a decimal point as for
911: English (a comma might work with a correct LC_NUMERIC environment,
912: otherwise the weight is truncated).
913: Modification of warning when the covariates values are not 0 or
914: 1.
915: Version 0.98g
916:
917: Revision 1.121 2006/03/16 17:45:01 lievre
918: * imach.c (Module): Comments concerning covariates added
919:
920: * imach.c (Module): refinements in the computation of lli if
921: status=-2 in order to have more reliable computation if stepm is
922: not 1 month. Version 0.98f
923:
924: Revision 1.120 2006/03/16 15:10:38 lievre
925: (Module): refinements in the computation of lli if
926: status=-2 in order to have more reliable computation if stepm is
927: not 1 month. Version 0.98f
928:
929: Revision 1.119 2006/03/15 17:42:26 brouard
930: (Module): Bug if status = -2, the loglikelihood was
931: computed as likelihood omitting the logarithm. Version O.98e
932:
933: Revision 1.118 2006/03/14 18:20:07 brouard
934: (Module): varevsij Comments added explaining the second
935: table of variances if popbased=1 .
936: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
937: (Module): Function pstamp added
938: (Module): Version 0.98d
939:
940: Revision 1.117 2006/03/14 17:16:22 brouard
941: (Module): varevsij Comments added explaining the second
942: table of variances if popbased=1 .
943: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
944: (Module): Function pstamp added
945: (Module): Version 0.98d
946:
947: Revision 1.116 2006/03/06 10:29:27 brouard
948: (Module): Variance-covariance wrong links and
949: varian-covariance of ej. is needed (Saito).
950:
951: Revision 1.115 2006/02/27 12:17:45 brouard
952: (Module): One freematrix added in mlikeli! 0.98c
953:
954: Revision 1.114 2006/02/26 12:57:58 brouard
955: (Module): Some improvements in processing parameter
956: filename with strsep.
957:
958: Revision 1.113 2006/02/24 14:20:24 brouard
959: (Module): Memory leaks checks with valgrind and:
960: datafile was not closed, some imatrix were not freed and on matrix
961: allocation too.
962:
963: Revision 1.112 2006/01/30 09:55:26 brouard
964: (Module): Back to gnuplot.exe instead of wgnuplot.exe
965:
966: Revision 1.111 2006/01/25 20:38:18 brouard
967: (Module): Lots of cleaning and bugs added (Gompertz)
968: (Module): Comments can be added in data file. Missing date values
969: can be a simple dot '.'.
970:
971: Revision 1.110 2006/01/25 00:51:50 brouard
972: (Module): Lots of cleaning and bugs added (Gompertz)
973:
974: Revision 1.109 2006/01/24 19:37:15 brouard
975: (Module): Comments (lines starting with a #) are allowed in data.
976:
977: Revision 1.108 2006/01/19 18:05:42 lievre
978: Gnuplot problem appeared...
979: To be fixed
980:
981: Revision 1.107 2006/01/19 16:20:37 brouard
982: Test existence of gnuplot in imach path
983:
984: Revision 1.106 2006/01/19 13:24:36 brouard
985: Some cleaning and links added in html output
986:
987: Revision 1.105 2006/01/05 20:23:19 lievre
988: *** empty log message ***
989:
990: Revision 1.104 2005/09/30 16:11:43 lievre
991: (Module): sump fixed, loop imx fixed, and simplifications.
992: (Module): If the status is missing at the last wave but we know
993: that the person is alive, then we can code his/her status as -2
994: (instead of missing=-1 in earlier versions) and his/her
995: contributions to the likelihood is 1 - Prob of dying from last
996: health status (= 1-p13= p11+p12 in the easiest case of somebody in
997: the healthy state at last known wave). Version is 0.98
998:
999: Revision 1.103 2005/09/30 15:54:49 lievre
1000: (Module): sump fixed, loop imx fixed, and simplifications.
1001:
1002: Revision 1.102 2004/09/15 17:31:30 brouard
1003: Add the possibility to read data file including tab characters.
1004:
1005: Revision 1.101 2004/09/15 10:38:38 brouard
1006: Fix on curr_time
1007:
1008: Revision 1.100 2004/07/12 18:29:06 brouard
1009: Add version for Mac OS X. Just define UNIX in Makefile
1010:
1011: Revision 1.99 2004/06/05 08:57:40 brouard
1012: *** empty log message ***
1013:
1014: Revision 1.98 2004/05/16 15:05:56 brouard
1015: New version 0.97 . First attempt to estimate force of mortality
1016: directly from the data i.e. without the need of knowing the health
1017: state at each age, but using a Gompertz model: log u =a + b*age .
1018: This is the basic analysis of mortality and should be done before any
1019: other analysis, in order to test if the mortality estimated from the
1020: cross-longitudinal survey is different from the mortality estimated
1021: from other sources like vital statistic data.
1022:
1023: The same imach parameter file can be used but the option for mle should be -3.
1024:
1.324 brouard 1025: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1026: former routines in order to include the new code within the former code.
1027:
1028: The output is very simple: only an estimate of the intercept and of
1029: the slope with 95% confident intervals.
1030:
1031: Current limitations:
1032: A) Even if you enter covariates, i.e. with the
1033: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1034: B) There is no computation of Life Expectancy nor Life Table.
1035:
1036: Revision 1.97 2004/02/20 13:25:42 lievre
1037: Version 0.96d. Population forecasting command line is (temporarily)
1038: suppressed.
1039:
1040: Revision 1.96 2003/07/15 15:38:55 brouard
1041: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1042: rewritten within the same printf. Workaround: many printfs.
1043:
1044: Revision 1.95 2003/07/08 07:54:34 brouard
1045: * imach.c (Repository):
1046: (Repository): Using imachwizard code to output a more meaningful covariance
1047: matrix (cov(a12,c31) instead of numbers.
1048:
1049: Revision 1.94 2003/06/27 13:00:02 brouard
1050: Just cleaning
1051:
1052: Revision 1.93 2003/06/25 16:33:55 brouard
1053: (Module): On windows (cygwin) function asctime_r doesn't
1054: exist so I changed back to asctime which exists.
1055: (Module): Version 0.96b
1056:
1057: Revision 1.92 2003/06/25 16:30:45 brouard
1058: (Module): On windows (cygwin) function asctime_r doesn't
1059: exist so I changed back to asctime which exists.
1060:
1061: Revision 1.91 2003/06/25 15:30:29 brouard
1062: * imach.c (Repository): Duplicated warning errors corrected.
1063: (Repository): Elapsed time after each iteration is now output. It
1064: helps to forecast when convergence will be reached. Elapsed time
1065: is stamped in powell. We created a new html file for the graphs
1066: concerning matrix of covariance. It has extension -cov.htm.
1067:
1068: Revision 1.90 2003/06/24 12:34:15 brouard
1069: (Module): Some bugs corrected for windows. Also, when
1070: mle=-1 a template is output in file "or"mypar.txt with the design
1071: of the covariance matrix to be input.
1072:
1073: Revision 1.89 2003/06/24 12:30:52 brouard
1074: (Module): Some bugs corrected for windows. Also, when
1075: mle=-1 a template is output in file "or"mypar.txt with the design
1076: of the covariance matrix to be input.
1077:
1078: Revision 1.88 2003/06/23 17:54:56 brouard
1079: * 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.
1080:
1081: Revision 1.87 2003/06/18 12:26:01 brouard
1082: Version 0.96
1083:
1084: Revision 1.86 2003/06/17 20:04:08 brouard
1085: (Module): Change position of html and gnuplot routines and added
1086: routine fileappend.
1087:
1088: Revision 1.85 2003/06/17 13:12:43 brouard
1089: * imach.c (Repository): Check when date of death was earlier that
1090: current date of interview. It may happen when the death was just
1091: prior to the death. In this case, dh was negative and likelihood
1092: was wrong (infinity). We still send an "Error" but patch by
1093: assuming that the date of death was just one stepm after the
1094: interview.
1095: (Repository): Because some people have very long ID (first column)
1096: we changed int to long in num[] and we added a new lvector for
1097: memory allocation. But we also truncated to 8 characters (left
1098: truncation)
1099: (Repository): No more line truncation errors.
1100:
1101: Revision 1.84 2003/06/13 21:44:43 brouard
1102: * imach.c (Repository): Replace "freqsummary" at a correct
1103: place. It differs from routine "prevalence" which may be called
1104: many times. Probs is memory consuming and must be used with
1105: parcimony.
1106: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1107:
1108: Revision 1.83 2003/06/10 13:39:11 lievre
1109: *** empty log message ***
1110:
1111: Revision 1.82 2003/06/05 15:57:20 brouard
1112: Add log in imach.c and fullversion number is now printed.
1113:
1114: */
1115: /*
1116: Interpolated Markov Chain
1117:
1118: Short summary of the programme:
1119:
1.227 brouard 1120: This program computes Healthy Life Expectancies or State-specific
1121: (if states aren't health statuses) Expectancies from
1122: cross-longitudinal data. Cross-longitudinal data consist in:
1123:
1124: -1- a first survey ("cross") where individuals from different ages
1125: are interviewed on their health status or degree of disability (in
1126: the case of a health survey which is our main interest)
1127:
1128: -2- at least a second wave of interviews ("longitudinal") which
1129: measure each change (if any) in individual health status. Health
1130: expectancies are computed from the time spent in each health state
1131: according to a model. More health states you consider, more time is
1132: necessary to reach the Maximum Likelihood of the parameters involved
1133: in the model. The simplest model is the multinomial logistic model
1134: where pij is the probability to be observed in state j at the second
1135: wave conditional to be observed in state i at the first
1136: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1137: etc , where 'age' is age and 'sex' is a covariate. If you want to
1138: have a more complex model than "constant and age", you should modify
1139: the program where the markup *Covariates have to be included here
1140: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1141: convergence.
1142:
1143: The advantage of this computer programme, compared to a simple
1144: multinomial logistic model, is clear when the delay between waves is not
1145: identical for each individual. Also, if a individual missed an
1146: intermediate interview, the information is lost, but taken into
1147: account using an interpolation or extrapolation.
1148:
1149: hPijx is the probability to be observed in state i at age x+h
1150: conditional to the observed state i at age x. The delay 'h' can be
1151: split into an exact number (nh*stepm) of unobserved intermediate
1152: states. This elementary transition (by month, quarter,
1153: semester or year) is modelled as a multinomial logistic. The hPx
1154: matrix is simply the matrix product of nh*stepm elementary matrices
1155: and the contribution of each individual to the likelihood is simply
1156: hPijx.
1157:
1158: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1159: of the life expectancies. It also computes the period (stable) prevalence.
1160:
1161: Back prevalence and projections:
1.227 brouard 1162:
1163: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1164: double agemaxpar, double ftolpl, int *ncvyearp, double
1165: dateprev1,double dateprev2, int firstpass, int lastpass, int
1166: mobilavproj)
1167:
1168: Computes the back prevalence limit for any combination of
1169: covariate values k at any age between ageminpar and agemaxpar and
1170: returns it in **bprlim. In the loops,
1171:
1172: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1173: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1174:
1175: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1176: Computes for any combination of covariates k and any age between bage and fage
1177: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1178: oldm=oldms;savm=savms;
1.227 brouard 1179:
1.267 brouard 1180: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1181: Computes the transition matrix starting at age 'age' over
1182: 'nhstepm*hstepm*stepm' months (i.e. until
1183: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1184: nhstepm*hstepm matrices.
1185:
1186: Returns p3mat[i][j][h] after calling
1187: p3mat[i][j][h]=matprod2(newm,
1188: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1189: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1190: oldm);
1.226 brouard 1191:
1192: Important routines
1193:
1194: - func (or funcone), computes logit (pij) distinguishing
1195: o fixed variables (single or product dummies or quantitative);
1196: o varying variables by:
1197: (1) wave (single, product dummies, quantitative),
1198: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1199: % fixed dummy (treated) or quantitative (not done because time-consuming);
1200: % varying dummy (not done) or quantitative (not done);
1201: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1202: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1203: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1204: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1205: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1206:
1.226 brouard 1207:
1208:
1.324 brouard 1209: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1210: Institut national d'études démographiques, Paris.
1.126 brouard 1211: This software have been partly granted by Euro-REVES, a concerted action
1212: from the European Union.
1213: It is copyrighted identically to a GNU software product, ie programme and
1214: software can be distributed freely for non commercial use. Latest version
1215: can be accessed at http://euroreves.ined.fr/imach .
1216:
1217: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1218: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1219:
1220: **********************************************************************/
1221: /*
1222: main
1223: read parameterfile
1224: read datafile
1225: concatwav
1226: freqsummary
1227: if (mle >= 1)
1228: mlikeli
1229: print results files
1230: if mle==1
1231: computes hessian
1232: read end of parameter file: agemin, agemax, bage, fage, estepm
1233: begin-prev-date,...
1234: open gnuplot file
1235: open html file
1.145 brouard 1236: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1237: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1238: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1239: freexexit2 possible for memory heap.
1240:
1241: h Pij x | pij_nom ficrestpij
1242: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1243: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1244: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1245:
1246: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1247: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1248: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1249: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1250: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1251:
1.126 brouard 1252: forecasting if prevfcast==1 prevforecast call prevalence()
1253: health expectancies
1254: Variance-covariance of DFLE
1255: prevalence()
1256: movingaverage()
1257: varevsij()
1258: if popbased==1 varevsij(,popbased)
1259: total life expectancies
1260: Variance of period (stable) prevalence
1261: end
1262: */
1263:
1.187 brouard 1264: /* #define DEBUG */
1265: /* #define DEBUGBRENT */
1.203 brouard 1266: /* #define DEBUGLINMIN */
1267: /* #define DEBUGHESS */
1268: #define DEBUGHESSIJ
1.224 brouard 1269: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1270: #define POWELL /* Instead of NLOPT */
1.224 brouard 1271: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1272: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1273: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1274: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1275:
1276: #include <math.h>
1277: #include <stdio.h>
1278: #include <stdlib.h>
1279: #include <string.h>
1.226 brouard 1280: #include <ctype.h>
1.159 brouard 1281:
1282: #ifdef _WIN32
1283: #include <io.h>
1.172 brouard 1284: #include <windows.h>
1285: #include <tchar.h>
1.159 brouard 1286: #else
1.126 brouard 1287: #include <unistd.h>
1.159 brouard 1288: #endif
1.126 brouard 1289:
1290: #include <limits.h>
1291: #include <sys/types.h>
1.171 brouard 1292:
1293: #if defined(__GNUC__)
1294: #include <sys/utsname.h> /* Doesn't work on Windows */
1295: #endif
1296:
1.126 brouard 1297: #include <sys/stat.h>
1298: #include <errno.h>
1.159 brouard 1299: /* extern int errno; */
1.126 brouard 1300:
1.157 brouard 1301: /* #ifdef LINUX */
1302: /* #include <time.h> */
1303: /* #include "timeval.h" */
1304: /* #else */
1305: /* #include <sys/time.h> */
1306: /* #endif */
1307:
1.126 brouard 1308: #include <time.h>
1309:
1.136 brouard 1310: #ifdef GSL
1311: #include <gsl/gsl_errno.h>
1312: #include <gsl/gsl_multimin.h>
1313: #endif
1314:
1.167 brouard 1315:
1.162 brouard 1316: #ifdef NLOPT
1317: #include <nlopt.h>
1318: typedef struct {
1319: double (* function)(double [] );
1320: } myfunc_data ;
1321: #endif
1322:
1.126 brouard 1323: /* #include <libintl.h> */
1324: /* #define _(String) gettext (String) */
1325:
1.349 brouard 1326: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1327:
1328: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1329: #define GNUPLOTVERSION 5.1
1330: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1331: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1332: #define FILENAMELENGTH 256
1.126 brouard 1333:
1334: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1335: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1336:
1.349 brouard 1337: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1338: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1339:
1340: #define NINTERVMAX 8
1.144 brouard 1341: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1342: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1343: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1344: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1345: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1346: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1347: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1348: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1349: /* #define AGESUP 130 */
1.288 brouard 1350: /* #define AGESUP 150 */
1351: #define AGESUP 200
1.268 brouard 1352: #define AGEINF 0
1.218 brouard 1353: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1354: #define AGEBASE 40
1.194 brouard 1355: #define AGEOVERFLOW 1.e20
1.164 brouard 1356: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1357: #ifdef _WIN32
1358: #define DIRSEPARATOR '\\'
1359: #define CHARSEPARATOR "\\"
1360: #define ODIRSEPARATOR '/'
1361: #else
1.126 brouard 1362: #define DIRSEPARATOR '/'
1363: #define CHARSEPARATOR "/"
1364: #define ODIRSEPARATOR '\\'
1365: #endif
1366:
1.352 ! brouard 1367: /* $Id: imach.c,v 1.351 2023/04/29 10:43:47 brouard Exp $ */
1.126 brouard 1368: /* $State: Exp $ */
1.196 brouard 1369: #include "version.h"
1370: char version[]=__IMACH_VERSION__;
1.352 ! brouard 1371: 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";
! 1372: char fullversion[]="$Revision: 1.351 $ $Date: 2023/04/29 10:43:47 $";
1.126 brouard 1373: char strstart[80];
1374: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1375: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1376: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1377: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1378: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1379: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1380: 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 1381: 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 1382: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1383: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1384: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1385: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1386: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1387: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1388: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1389: 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 1390: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1391: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1392: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1393: 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 */
1394: 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 */
1395: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1396: 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 1397: int nsd=0; /**< Total number of single dummy variables (output) */
1398: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1399: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1400: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1401: int ntveff=0; /**< ntveff number of effective time varying variables */
1402: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1403: int cptcov=0; /* Working variable */
1.334 brouard 1404: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1405: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1406: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1407: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1408: int nlstate=2; /* Number of live states */
1409: int ndeath=1; /* Number of dead states */
1.130 brouard 1410: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1411: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1412: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1413: int popbased=0;
1414:
1415: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1416: int maxwav=0; /* Maxim number of waves */
1417: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1418: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1419: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1420: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1421: int mle=1, weightopt=0;
1.126 brouard 1422: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1423: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1424: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1425: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1426: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1427: int selected(int kvar); /* Is covariate kvar selected for printing results */
1428:
1.130 brouard 1429: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1430: double **matprod2(); /* test */
1.126 brouard 1431: double **oldm, **newm, **savm; /* Working pointers to matrices */
1432: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1433: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1434:
1.136 brouard 1435: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1436: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1437: FILE *ficlog, *ficrespow;
1.130 brouard 1438: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1439: double fretone; /* Only one call to likelihood */
1.130 brouard 1440: long ipmx=0; /* Number of contributions */
1.126 brouard 1441: double sw; /* Sum of weights */
1442: char filerespow[FILENAMELENGTH];
1443: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1444: FILE *ficresilk;
1445: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1446: FILE *ficresprobmorprev;
1447: FILE *fichtm, *fichtmcov; /* Html File */
1448: FILE *ficreseij;
1449: char filerese[FILENAMELENGTH];
1450: FILE *ficresstdeij;
1451: char fileresstde[FILENAMELENGTH];
1452: FILE *ficrescveij;
1453: char filerescve[FILENAMELENGTH];
1454: FILE *ficresvij;
1455: char fileresv[FILENAMELENGTH];
1.269 brouard 1456:
1.126 brouard 1457: char title[MAXLINE];
1.234 brouard 1458: char model[MAXLINE]; /**< The model line */
1.217 brouard 1459: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1460: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1461: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1462: char command[FILENAMELENGTH];
1463: int outcmd=0;
1464:
1.217 brouard 1465: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1466: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1467: char filelog[FILENAMELENGTH]; /* Log file */
1468: char filerest[FILENAMELENGTH];
1469: char fileregp[FILENAMELENGTH];
1470: char popfile[FILENAMELENGTH];
1471:
1472: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1473:
1.157 brouard 1474: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1475: /* struct timezone tzp; */
1476: /* extern int gettimeofday(); */
1477: struct tm tml, *gmtime(), *localtime();
1478:
1479: extern time_t time();
1480:
1481: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1482: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1483: time_t rlast_btime; /* raw time */
1.157 brouard 1484: struct tm tm;
1485:
1.126 brouard 1486: char strcurr[80], strfor[80];
1487:
1488: char *endptr;
1489: long lval;
1490: double dval;
1491:
1492: #define NR_END 1
1493: #define FREE_ARG char*
1494: #define FTOL 1.0e-10
1495:
1496: #define NRANSI
1.240 brouard 1497: #define ITMAX 200
1498: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1499:
1500: #define TOL 2.0e-4
1501:
1502: #define CGOLD 0.3819660
1503: #define ZEPS 1.0e-10
1504: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1505:
1506: #define GOLD 1.618034
1507: #define GLIMIT 100.0
1508: #define TINY 1.0e-20
1509:
1510: static double maxarg1,maxarg2;
1511: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1512: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1513:
1514: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1515: #define rint(a) floor(a+0.5)
1.166 brouard 1516: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1517: #define mytinydouble 1.0e-16
1.166 brouard 1518: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1519: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1520: /* static double dsqrarg; */
1521: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1522: static double sqrarg;
1523: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1524: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1525: int agegomp= AGEGOMP;
1526:
1527: int imx;
1528: int stepm=1;
1529: /* Stepm, step in month: minimum step interpolation*/
1530:
1531: int estepm;
1532: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1533:
1534: int m,nb;
1535: long *num;
1.197 brouard 1536: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1537: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1538: covariate for which somebody answered excluding
1539: undefined. Usually 2: 0 and 1. */
1540: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1541: covariate for which somebody answered including
1542: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1543: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1544: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1545: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1546: 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 1547: double *ageexmed,*agecens;
1548: double dateintmean=0;
1.296 brouard 1549: double anprojd, mprojd, jprojd; /* For eventual projections */
1550: double anprojf, mprojf, jprojf;
1.126 brouard 1551:
1.296 brouard 1552: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1553: double anbackf, mbackf, jbackf;
1554: double jintmean,mintmean,aintmean;
1.126 brouard 1555: double *weight;
1556: int **s; /* Status */
1.141 brouard 1557: double *agedc;
1.145 brouard 1558: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1559: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1560: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1561: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1562: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1563: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1564: double idx;
1565: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1566: /* Some documentation */
1567: /* Design original data
1568: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1569: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1570: * ntv=3 nqtv=1
1.330 brouard 1571: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1572: * For time varying covariate, quanti or dummies
1573: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1574: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1575: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1576: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1577: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1578: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1579: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1580: * k= 1 2 3 4 5 6 7 8 9 10 11
1581: */
1582: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1583: /* 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
1584: # States 1=Coresidence, 2 Living alone, 3 Institution
1585: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1586: */
1.349 brouard 1587: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1588: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1589: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1590: /* fixed or varying), 1 for age product, 2 for*/
1591: /* product without age, 3 for age and double product */
1592: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1593: /*(single or product without age), 2 dummy*/
1594: /* with age product, 3 quant with age product*/
1595: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1596: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1597: /*TnsdVar[Tvar] 1 2 3 */
1598: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1599: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1600: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1601: /* nsq 1 2 */ /* Counting single quantit tv */
1602: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1603: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1604: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1605: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1606: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1607: /* 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"*/
1608: /* 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}*/
1609: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>}
1610: /* 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}*/
1611: /* 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 1612: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1613: /* 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 1614: /* 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 1615: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1616: /* Type */
1617: /* V 1 2 3 4 5 */
1618: /* F F V V V */
1619: /* D Q D D Q */
1620: /* */
1621: int *TvarsD;
1.330 brouard 1622: int *TnsdVar;
1.234 brouard 1623: int *TvarsDind;
1624: int *TvarsQ;
1625: int *TvarsQind;
1626:
1.318 brouard 1627: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1628: int nresult=0;
1.258 brouard 1629: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1630: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1631: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1632: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1633: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1634: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1635: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1636: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1637: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1638: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1639: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1640:
1641: /* 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
1642: # States 1=Coresidence, 2 Living alone, 3 Institution
1643: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1644: */
1.234 brouard 1645: /* 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 1646: 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 */
1647: 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 */
1648: 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 */
1649: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1650: 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 */
1651: 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 1652: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1653: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1654: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1655: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1656: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1657: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1658: 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 */
1659: 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 1660: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1661: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1662: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1663: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1664: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1665: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1666: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1667: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1668: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1669: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1670: /* 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 1671: int *Tvarsel; /**< Selected covariates for output */
1672: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1673: 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 1674: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1675: 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 1676: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1677: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1678: int *Tage;
1.227 brouard 1679: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1680: 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 1681: 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*/
1682: 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 1683: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1684: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1685: int **Tvard;
1.330 brouard 1686: int **Tvardk;
1.227 brouard 1687: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1688: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1689: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1690: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1691: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1692: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1693: double *lsurv, *lpop, *tpop;
1694:
1.231 brouard 1695: #define FD 1; /* Fixed dummy covariate */
1696: #define FQ 2; /* Fixed quantitative covariate */
1697: #define FP 3; /* Fixed product covariate */
1698: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1699: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1700: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1701: #define VD 10; /* Varying dummy covariate */
1702: #define VQ 11; /* Varying quantitative covariate */
1703: #define VP 12; /* Varying product covariate */
1704: #define VPDD 13; /* Varying product dummy*dummy covariate */
1705: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1706: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1707: #define APFD 16; /* Age product * fixed dummy covariate */
1708: #define APFQ 17; /* Age product * fixed quantitative covariate */
1709: #define APVD 18; /* Age product * varying dummy covariate */
1710: #define APVQ 19; /* Age product * varying quantitative covariate */
1711:
1712: #define FTYPE 1; /* Fixed covariate */
1713: #define VTYPE 2; /* Varying covariate (loop in wave) */
1714: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1715:
1716: struct kmodel{
1717: int maintype; /* main type */
1718: int subtype; /* subtype */
1719: };
1720: struct kmodel modell[NCOVMAX];
1721:
1.143 brouard 1722: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1723: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1724:
1725: /**************** split *************************/
1726: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1727: {
1728: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1729: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1730: */
1731: char *ss; /* pointer */
1.186 brouard 1732: int l1=0, l2=0; /* length counters */
1.126 brouard 1733:
1734: l1 = strlen(path ); /* length of path */
1735: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1736: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1737: if ( ss == NULL ) { /* no directory, so determine current directory */
1738: strcpy( name, path ); /* we got the fullname name because no directory */
1739: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1740: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1741: /* get current working directory */
1742: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1743: #ifdef WIN32
1744: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1745: #else
1746: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1747: #endif
1.126 brouard 1748: return( GLOCK_ERROR_GETCWD );
1749: }
1750: /* got dirc from getcwd*/
1751: printf(" DIRC = %s \n",dirc);
1.205 brouard 1752: } else { /* strip directory from path */
1.126 brouard 1753: ss++; /* after this, the filename */
1754: l2 = strlen( ss ); /* length of filename */
1755: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1756: strcpy( name, ss ); /* save file name */
1757: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1758: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1759: printf(" DIRC2 = %s \n",dirc);
1760: }
1761: /* We add a separator at the end of dirc if not exists */
1762: l1 = strlen( dirc ); /* length of directory */
1763: if( dirc[l1-1] != DIRSEPARATOR ){
1764: dirc[l1] = DIRSEPARATOR;
1765: dirc[l1+1] = 0;
1766: printf(" DIRC3 = %s \n",dirc);
1767: }
1768: ss = strrchr( name, '.' ); /* find last / */
1769: if (ss >0){
1770: ss++;
1771: strcpy(ext,ss); /* save extension */
1772: l1= strlen( name);
1773: l2= strlen(ss)+1;
1774: strncpy( finame, name, l1-l2);
1775: finame[l1-l2]= 0;
1776: }
1777:
1778: return( 0 ); /* we're done */
1779: }
1780:
1781:
1782: /******************************************/
1783:
1784: void replace_back_to_slash(char *s, char*t)
1785: {
1786: int i;
1787: int lg=0;
1788: i=0;
1789: lg=strlen(t);
1790: for(i=0; i<= lg; i++) {
1791: (s[i] = t[i]);
1792: if (t[i]== '\\') s[i]='/';
1793: }
1794: }
1795:
1.132 brouard 1796: char *trimbb(char *out, char *in)
1.137 brouard 1797: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1798: char *s;
1799: s=out;
1800: while (*in != '\0'){
1.137 brouard 1801: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1802: in++;
1803: }
1804: *out++ = *in++;
1805: }
1806: *out='\0';
1807: return s;
1808: }
1809:
1.351 brouard 1810: char *trimbtab(char *out, char *in)
1811: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1812: char *s;
1813: s=out;
1814: while (*in != '\0'){
1815: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1816: in++;
1817: }
1818: *out++ = *in++;
1819: }
1820: *out='\0';
1821: return s;
1822: }
1823:
1.187 brouard 1824: /* char *substrchaine(char *out, char *in, char *chain) */
1825: /* { */
1826: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1827: /* char *s, *t; */
1828: /* t=in;s=out; */
1829: /* while ((*in != *chain) && (*in != '\0')){ */
1830: /* *out++ = *in++; */
1831: /* } */
1832:
1833: /* /\* *in matches *chain *\/ */
1834: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1835: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1836: /* } */
1837: /* in--; chain--; */
1838: /* while ( (*in != '\0')){ */
1839: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1840: /* *out++ = *in++; */
1841: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1842: /* } */
1843: /* *out='\0'; */
1844: /* out=s; */
1845: /* return out; */
1846: /* } */
1847: char *substrchaine(char *out, char *in, char *chain)
1848: {
1849: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1850: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1851:
1852: char *strloc;
1853:
1.349 brouard 1854: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1855: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1856: 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 1857: if(strloc != NULL){
1.349 brouard 1858: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1859: 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)*/
1860: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1861: }
1.349 brouard 1862: 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 1863: return out;
1864: }
1865:
1866:
1.145 brouard 1867: char *cutl(char *blocc, char *alocc, char *in, char occ)
1868: {
1.187 brouard 1869: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1870: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1871: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1872: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1873: */
1.160 brouard 1874: char *s, *t;
1.145 brouard 1875: t=in;s=in;
1876: while ((*in != occ) && (*in != '\0')){
1877: *alocc++ = *in++;
1878: }
1879: if( *in == occ){
1880: *(alocc)='\0';
1881: s=++in;
1882: }
1883:
1884: if (s == t) {/* occ not found */
1885: *(alocc-(in-s))='\0';
1886: in=s;
1887: }
1888: while ( *in != '\0'){
1889: *blocc++ = *in++;
1890: }
1891:
1892: *blocc='\0';
1893: return t;
1894: }
1.137 brouard 1895: char *cutv(char *blocc, char *alocc, char *in, char occ)
1896: {
1.187 brouard 1897: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1898: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1899: gives blocc="abcdef2ghi" and alocc="j".
1900: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1901: */
1902: char *s, *t;
1903: t=in;s=in;
1904: while (*in != '\0'){
1905: while( *in == occ){
1906: *blocc++ = *in++;
1907: s=in;
1908: }
1909: *blocc++ = *in++;
1910: }
1911: if (s == t) /* occ not found */
1912: *(blocc-(in-s))='\0';
1913: else
1914: *(blocc-(in-s)-1)='\0';
1915: in=s;
1916: while ( *in != '\0'){
1917: *alocc++ = *in++;
1918: }
1919:
1920: *alocc='\0';
1921: return s;
1922: }
1923:
1.126 brouard 1924: int nbocc(char *s, char occ)
1925: {
1926: int i,j=0;
1927: int lg=20;
1928: i=0;
1929: lg=strlen(s);
1930: for(i=0; i<= lg; i++) {
1.234 brouard 1931: if (s[i] == occ ) j++;
1.126 brouard 1932: }
1933: return j;
1934: }
1935:
1.349 brouard 1936: int nboccstr(char *textin, char *chain)
1937: {
1938: /* Counts the number of occurence of "chain" in string textin */
1939: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1940: char *strloc;
1941:
1942: int i,j=0;
1943:
1944: i=0;
1945:
1946: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1947: for(;;) {
1948: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1949: if(strloc != NULL){
1950: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1951: j++;
1952: }else
1953: break;
1954: }
1955: return j;
1956:
1957: }
1.137 brouard 1958: /* void cutv(char *u,char *v, char*t, char occ) */
1959: /* { */
1960: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1961: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1962: /* gives u="abcdef2ghi" and v="j" *\/ */
1963: /* int i,lg,j,p=0; */
1964: /* i=0; */
1965: /* lg=strlen(t); */
1966: /* for(j=0; j<=lg-1; j++) { */
1967: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1968: /* } */
1.126 brouard 1969:
1.137 brouard 1970: /* for(j=0; j<p; j++) { */
1971: /* (u[j] = t[j]); */
1972: /* } */
1973: /* u[p]='\0'; */
1.126 brouard 1974:
1.137 brouard 1975: /* for(j=0; j<= lg; j++) { */
1976: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1977: /* } */
1978: /* } */
1.126 brouard 1979:
1.160 brouard 1980: #ifdef _WIN32
1981: char * strsep(char **pp, const char *delim)
1982: {
1983: char *p, *q;
1984:
1985: if ((p = *pp) == NULL)
1986: return 0;
1987: if ((q = strpbrk (p, delim)) != NULL)
1988: {
1989: *pp = q + 1;
1990: *q = '\0';
1991: }
1992: else
1993: *pp = 0;
1994: return p;
1995: }
1996: #endif
1997:
1.126 brouard 1998: /********************** nrerror ********************/
1999:
2000: void nrerror(char error_text[])
2001: {
2002: fprintf(stderr,"ERREUR ...\n");
2003: fprintf(stderr,"%s\n",error_text);
2004: exit(EXIT_FAILURE);
2005: }
2006: /*********************** vector *******************/
2007: double *vector(int nl, int nh)
2008: {
2009: double *v;
2010: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2011: if (!v) nrerror("allocation failure in vector");
2012: return v-nl+NR_END;
2013: }
2014:
2015: /************************ free vector ******************/
2016: void free_vector(double*v, int nl, int nh)
2017: {
2018: free((FREE_ARG)(v+nl-NR_END));
2019: }
2020:
2021: /************************ivector *******************************/
2022: int *ivector(long nl,long nh)
2023: {
2024: int *v;
2025: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2026: if (!v) nrerror("allocation failure in ivector");
2027: return v-nl+NR_END;
2028: }
2029:
2030: /******************free ivector **************************/
2031: void free_ivector(int *v, long nl, long nh)
2032: {
2033: free((FREE_ARG)(v+nl-NR_END));
2034: }
2035:
2036: /************************lvector *******************************/
2037: long *lvector(long nl,long nh)
2038: {
2039: long *v;
2040: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2041: if (!v) nrerror("allocation failure in ivector");
2042: return v-nl+NR_END;
2043: }
2044:
2045: /******************free lvector **************************/
2046: void free_lvector(long *v, long nl, long nh)
2047: {
2048: free((FREE_ARG)(v+nl-NR_END));
2049: }
2050:
2051: /******************* imatrix *******************************/
2052: int **imatrix(long nrl, long nrh, long ncl, long nch)
2053: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2054: {
2055: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2056: int **m;
2057:
2058: /* allocate pointers to rows */
2059: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2060: if (!m) nrerror("allocation failure 1 in matrix()");
2061: m += NR_END;
2062: m -= nrl;
2063:
2064:
2065: /* allocate rows and set pointers to them */
2066: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2067: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2068: m[nrl] += NR_END;
2069: m[nrl] -= ncl;
2070:
2071: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2072:
2073: /* return pointer to array of pointers to rows */
2074: return m;
2075: }
2076:
2077: /****************** free_imatrix *************************/
2078: void free_imatrix(m,nrl,nrh,ncl,nch)
2079: int **m;
2080: long nch,ncl,nrh,nrl;
2081: /* free an int matrix allocated by imatrix() */
2082: {
2083: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2084: free((FREE_ARG) (m+nrl-NR_END));
2085: }
2086:
2087: /******************* matrix *******************************/
2088: double **matrix(long nrl, long nrh, long ncl, long nch)
2089: {
2090: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2091: double **m;
2092:
2093: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2094: if (!m) nrerror("allocation failure 1 in matrix()");
2095: m += NR_END;
2096: m -= nrl;
2097:
2098: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2099: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2100: m[nrl] += NR_END;
2101: m[nrl] -= ncl;
2102:
2103: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2104: return m;
1.145 brouard 2105: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2106: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2107: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2108: */
2109: }
2110:
2111: /*************************free matrix ************************/
2112: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2113: {
2114: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2115: free((FREE_ARG)(m+nrl-NR_END));
2116: }
2117:
2118: /******************* ma3x *******************************/
2119: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2120: {
2121: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2122: double ***m;
2123:
2124: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2125: if (!m) nrerror("allocation failure 1 in matrix()");
2126: m += NR_END;
2127: m -= nrl;
2128:
2129: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2130: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2131: m[nrl] += NR_END;
2132: m[nrl] -= ncl;
2133:
2134: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2135:
2136: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2137: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2138: m[nrl][ncl] += NR_END;
2139: m[nrl][ncl] -= nll;
2140: for (j=ncl+1; j<=nch; j++)
2141: m[nrl][j]=m[nrl][j-1]+nlay;
2142:
2143: for (i=nrl+1; i<=nrh; i++) {
2144: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2145: for (j=ncl+1; j<=nch; j++)
2146: m[i][j]=m[i][j-1]+nlay;
2147: }
2148: return m;
2149: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2150: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2151: */
2152: }
2153:
2154: /*************************free ma3x ************************/
2155: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2156: {
2157: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2158: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2159: free((FREE_ARG)(m+nrl-NR_END));
2160: }
2161:
2162: /*************** function subdirf ***********/
2163: char *subdirf(char fileres[])
2164: {
2165: /* Caution optionfilefiname is hidden */
2166: strcpy(tmpout,optionfilefiname);
2167: strcat(tmpout,"/"); /* Add to the right */
2168: strcat(tmpout,fileres);
2169: return tmpout;
2170: }
2171:
2172: /*************** function subdirf2 ***********/
2173: char *subdirf2(char fileres[], char *preop)
2174: {
1.314 brouard 2175: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2176: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2177: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2178: /* Caution optionfilefiname is hidden */
2179: strcpy(tmpout,optionfilefiname);
2180: strcat(tmpout,"/");
2181: strcat(tmpout,preop);
2182: strcat(tmpout,fileres);
2183: return tmpout;
2184: }
2185:
2186: /*************** function subdirf3 ***********/
2187: char *subdirf3(char fileres[], char *preop, char *preop2)
2188: {
2189:
2190: /* Caution optionfilefiname is hidden */
2191: strcpy(tmpout,optionfilefiname);
2192: strcat(tmpout,"/");
2193: strcat(tmpout,preop);
2194: strcat(tmpout,preop2);
2195: strcat(tmpout,fileres);
2196: return tmpout;
2197: }
1.213 brouard 2198:
2199: /*************** function subdirfext ***********/
2200: char *subdirfext(char fileres[], char *preop, char *postop)
2201: {
2202:
2203: strcpy(tmpout,preop);
2204: strcat(tmpout,fileres);
2205: strcat(tmpout,postop);
2206: return tmpout;
2207: }
1.126 brouard 2208:
1.213 brouard 2209: /*************** function subdirfext3 ***********/
2210: char *subdirfext3(char fileres[], char *preop, char *postop)
2211: {
2212:
2213: /* Caution optionfilefiname is hidden */
2214: strcpy(tmpout,optionfilefiname);
2215: strcat(tmpout,"/");
2216: strcat(tmpout,preop);
2217: strcat(tmpout,fileres);
2218: strcat(tmpout,postop);
2219: return tmpout;
2220: }
2221:
1.162 brouard 2222: char *asc_diff_time(long time_sec, char ascdiff[])
2223: {
2224: long sec_left, days, hours, minutes;
2225: days = (time_sec) / (60*60*24);
2226: sec_left = (time_sec) % (60*60*24);
2227: hours = (sec_left) / (60*60) ;
2228: sec_left = (sec_left) %(60*60);
2229: minutes = (sec_left) /60;
2230: sec_left = (sec_left) % (60);
2231: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2232: return ascdiff;
2233: }
2234:
1.126 brouard 2235: /***************** f1dim *************************/
2236: extern int ncom;
2237: extern double *pcom,*xicom;
2238: extern double (*nrfunc)(double []);
2239:
2240: double f1dim(double x)
2241: {
2242: int j;
2243: double f;
2244: double *xt;
2245:
2246: xt=vector(1,ncom);
2247: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2248: f=(*nrfunc)(xt);
2249: free_vector(xt,1,ncom);
2250: return f;
2251: }
2252:
2253: /*****************brent *************************/
2254: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2255: {
2256: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2257: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2258: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2259: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2260: * returned function value.
2261: */
1.126 brouard 2262: int iter;
2263: double a,b,d,etemp;
1.159 brouard 2264: double fu=0,fv,fw,fx;
1.164 brouard 2265: double ftemp=0.;
1.126 brouard 2266: double p,q,r,tol1,tol2,u,v,w,x,xm;
2267: double e=0.0;
2268:
2269: a=(ax < cx ? ax : cx);
2270: b=(ax > cx ? ax : cx);
2271: x=w=v=bx;
2272: fw=fv=fx=(*f)(x);
2273: for (iter=1;iter<=ITMAX;iter++) {
2274: xm=0.5*(a+b);
2275: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2276: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2277: printf(".");fflush(stdout);
2278: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2279: #ifdef DEBUGBRENT
1.126 brouard 2280: 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);
2281: 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);
2282: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2283: #endif
2284: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2285: *xmin=x;
2286: return fx;
2287: }
2288: ftemp=fu;
2289: if (fabs(e) > tol1) {
2290: r=(x-w)*(fx-fv);
2291: q=(x-v)*(fx-fw);
2292: p=(x-v)*q-(x-w)*r;
2293: q=2.0*(q-r);
2294: if (q > 0.0) p = -p;
2295: q=fabs(q);
2296: etemp=e;
2297: e=d;
2298: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2299: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2300: else {
1.224 brouard 2301: d=p/q;
2302: u=x+d;
2303: if (u-a < tol2 || b-u < tol2)
2304: d=SIGN(tol1,xm-x);
1.126 brouard 2305: }
2306: } else {
2307: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2308: }
2309: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2310: fu=(*f)(u);
2311: if (fu <= fx) {
2312: if (u >= x) a=x; else b=x;
2313: SHFT(v,w,x,u)
1.183 brouard 2314: SHFT(fv,fw,fx,fu)
2315: } else {
2316: if (u < x) a=u; else b=u;
2317: if (fu <= fw || w == x) {
1.224 brouard 2318: v=w;
2319: w=u;
2320: fv=fw;
2321: fw=fu;
1.183 brouard 2322: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2323: v=u;
2324: fv=fu;
1.183 brouard 2325: }
2326: }
1.126 brouard 2327: }
2328: nrerror("Too many iterations in brent");
2329: *xmin=x;
2330: return fx;
2331: }
2332:
2333: /****************** mnbrak ***********************/
2334:
2335: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2336: double (*func)(double))
1.183 brouard 2337: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2338: the downhill direction (defined by the function as evaluated at the initial points) and returns
2339: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2340: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2341: */
1.126 brouard 2342: double ulim,u,r,q, dum;
2343: double fu;
1.187 brouard 2344:
2345: double scale=10.;
2346: int iterscale=0;
2347:
2348: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2349: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2350:
2351:
2352: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2353: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2354: /* *bx = *ax - (*ax - *bx)/scale; */
2355: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2356: /* } */
2357:
1.126 brouard 2358: if (*fb > *fa) {
2359: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2360: SHFT(dum,*fb,*fa,dum)
2361: }
1.126 brouard 2362: *cx=(*bx)+GOLD*(*bx-*ax);
2363: *fc=(*func)(*cx);
1.183 brouard 2364: #ifdef DEBUG
1.224 brouard 2365: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2366: 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 2367: #endif
1.224 brouard 2368: 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 2369: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2370: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2371: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2372: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2373: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2374: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2375: fu=(*func)(u);
1.163 brouard 2376: #ifdef DEBUG
2377: /* f(x)=A(x-u)**2+f(u) */
2378: double A, fparabu;
2379: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2380: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2381: 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);
2382: 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 2383: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2384: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2385: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2386: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2387: #endif
1.184 brouard 2388: #ifdef MNBRAKORIGINAL
1.183 brouard 2389: #else
1.191 brouard 2390: /* if (fu > *fc) { */
2391: /* #ifdef DEBUG */
2392: /* printf("mnbrak4 fu > fc \n"); */
2393: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2394: /* #endif */
2395: /* /\* 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 *\\/ *\/ */
2396: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2397: /* dum=u; /\* Shifting c and u *\/ */
2398: /* u = *cx; */
2399: /* *cx = dum; */
2400: /* dum = fu; */
2401: /* fu = *fc; */
2402: /* *fc =dum; */
2403: /* } else { /\* end *\/ */
2404: /* #ifdef DEBUG */
2405: /* printf("mnbrak3 fu < fc \n"); */
2406: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2407: /* #endif */
2408: /* dum=u; /\* Shifting c and u *\/ */
2409: /* u = *cx; */
2410: /* *cx = dum; */
2411: /* dum = fu; */
2412: /* fu = *fc; */
2413: /* *fc =dum; */
2414: /* } */
1.224 brouard 2415: #ifdef DEBUGMNBRAK
2416: double A, fparabu;
2417: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2418: fparabu= *fa - A*(*ax-u)*(*ax-u);
2419: 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);
2420: 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 2421: #endif
1.191 brouard 2422: dum=u; /* Shifting c and u */
2423: u = *cx;
2424: *cx = dum;
2425: dum = fu;
2426: fu = *fc;
2427: *fc =dum;
1.183 brouard 2428: #endif
1.162 brouard 2429: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2430: #ifdef DEBUG
1.224 brouard 2431: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2432: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2433: #endif
1.126 brouard 2434: fu=(*func)(u);
2435: if (fu < *fc) {
1.183 brouard 2436: #ifdef DEBUG
1.224 brouard 2437: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2438: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2439: #endif
2440: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2441: SHFT(*fb,*fc,fu,(*func)(u))
2442: #ifdef DEBUG
2443: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2444: #endif
2445: }
1.162 brouard 2446: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2447: #ifdef DEBUG
1.224 brouard 2448: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2449: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2450: #endif
1.126 brouard 2451: u=ulim;
2452: fu=(*func)(u);
1.183 brouard 2453: } else { /* u could be left to b (if r > q parabola has a maximum) */
2454: #ifdef DEBUG
1.224 brouard 2455: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2456: 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 2457: #endif
1.126 brouard 2458: u=(*cx)+GOLD*(*cx-*bx);
2459: fu=(*func)(u);
1.224 brouard 2460: #ifdef DEBUG
2461: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2462: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2463: #endif
1.183 brouard 2464: } /* end tests */
1.126 brouard 2465: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2466: SHFT(*fa,*fb,*fc,fu)
2467: #ifdef DEBUG
1.224 brouard 2468: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2469: 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 2470: #endif
2471: } /* 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 2472: }
2473:
2474: /*************** linmin ************************/
1.162 brouard 2475: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2476: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2477: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2478: the value of func at the returned location p . This is actually all accomplished by calling the
2479: routines mnbrak and brent .*/
1.126 brouard 2480: int ncom;
2481: double *pcom,*xicom;
2482: double (*nrfunc)(double []);
2483:
1.224 brouard 2484: #ifdef LINMINORIGINAL
1.126 brouard 2485: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2486: #else
2487: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2488: #endif
1.126 brouard 2489: {
2490: double brent(double ax, double bx, double cx,
2491: double (*f)(double), double tol, double *xmin);
2492: double f1dim(double x);
2493: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2494: double *fc, double (*func)(double));
2495: int j;
2496: double xx,xmin,bx,ax;
2497: double fx,fb,fa;
1.187 brouard 2498:
1.203 brouard 2499: #ifdef LINMINORIGINAL
2500: #else
2501: double scale=10., axs, xxs; /* Scale added for infinity */
2502: #endif
2503:
1.126 brouard 2504: ncom=n;
2505: pcom=vector(1,n);
2506: xicom=vector(1,n);
2507: nrfunc=func;
2508: for (j=1;j<=n;j++) {
2509: pcom[j]=p[j];
1.202 brouard 2510: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2511: }
1.187 brouard 2512:
1.203 brouard 2513: #ifdef LINMINORIGINAL
2514: xx=1.;
2515: #else
2516: axs=0.0;
2517: xxs=1.;
2518: do{
2519: xx= xxs;
2520: #endif
1.187 brouard 2521: ax=0.;
2522: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2523: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2524: /* 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)) */
2525: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2526: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2527: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2528: /* 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 2529: #ifdef LINMINORIGINAL
2530: #else
2531: if (fx != fx){
1.224 brouard 2532: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2533: printf("|");
2534: fprintf(ficlog,"|");
1.203 brouard 2535: #ifdef DEBUGLINMIN
1.224 brouard 2536: 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 2537: #endif
2538: }
1.224 brouard 2539: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2540: #endif
2541:
1.191 brouard 2542: #ifdef DEBUGLINMIN
2543: 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 2544: 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 2545: #endif
1.224 brouard 2546: #ifdef LINMINORIGINAL
2547: #else
1.317 brouard 2548: if(fb == fx){ /* Flat function in the direction */
2549: xmin=xx;
1.224 brouard 2550: *flat=1;
1.317 brouard 2551: }else{
1.224 brouard 2552: *flat=0;
2553: #endif
2554: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2555: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2556: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2557: /* fmin = f(p[j] + xmin * xi[j]) */
2558: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2559: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2560: #ifdef DEBUG
1.224 brouard 2561: 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);
2562: 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);
2563: #endif
2564: #ifdef LINMINORIGINAL
2565: #else
2566: }
1.126 brouard 2567: #endif
1.191 brouard 2568: #ifdef DEBUGLINMIN
2569: printf("linmin end ");
1.202 brouard 2570: fprintf(ficlog,"linmin end ");
1.191 brouard 2571: #endif
1.126 brouard 2572: for (j=1;j<=n;j++) {
1.203 brouard 2573: #ifdef LINMINORIGINAL
2574: xi[j] *= xmin;
2575: #else
2576: #ifdef DEBUGLINMIN
2577: if(xxs <1.0)
2578: printf(" before xi[%d]=%12.8f", j,xi[j]);
2579: #endif
2580: 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) */
2581: #ifdef DEBUGLINMIN
2582: if(xxs <1.0)
2583: 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 );
2584: #endif
2585: #endif
1.187 brouard 2586: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2587: }
1.191 brouard 2588: #ifdef DEBUGLINMIN
1.203 brouard 2589: printf("\n");
1.191 brouard 2590: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2591: 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 2592: for (j=1;j<=n;j++) {
1.202 brouard 2593: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2594: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2595: if(j % ncovmodel == 0){
1.191 brouard 2596: printf("\n");
1.202 brouard 2597: fprintf(ficlog,"\n");
2598: }
1.191 brouard 2599: }
1.203 brouard 2600: #else
1.191 brouard 2601: #endif
1.126 brouard 2602: free_vector(xicom,1,n);
2603: free_vector(pcom,1,n);
2604: }
2605:
2606:
2607: /*************** powell ************************/
1.162 brouard 2608: /*
1.317 brouard 2609: Minimization of a function func of n variables. Input consists in an initial starting point
2610: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2611: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2612: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2613: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2614: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2615: */
1.224 brouard 2616: #ifdef LINMINORIGINAL
2617: #else
2618: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2619: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2620: #endif
1.126 brouard 2621: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2622: double (*func)(double []))
2623: {
1.224 brouard 2624: #ifdef LINMINORIGINAL
2625: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2626: double (*func)(double []));
1.224 brouard 2627: #else
1.241 brouard 2628: void linmin(double p[], double xi[], int n, double *fret,
2629: double (*func)(double []),int *flat);
1.224 brouard 2630: #endif
1.239 brouard 2631: int i,ibig,j,jk,k;
1.126 brouard 2632: double del,t,*pt,*ptt,*xit;
1.181 brouard 2633: double directest;
1.126 brouard 2634: double fp,fptt;
2635: double *xits;
2636: int niterf, itmp;
1.349 brouard 2637: int Bigter=0, nBigterf=1;
2638:
1.126 brouard 2639: pt=vector(1,n);
2640: ptt=vector(1,n);
2641: xit=vector(1,n);
2642: xits=vector(1,n);
2643: *fret=(*func)(p);
2644: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2645: rcurr_time = time(NULL);
2646: fp=(*fret); /* Initialisation */
1.126 brouard 2647: for (*iter=1;;++(*iter)) {
2648: ibig=0;
2649: del=0.0;
1.157 brouard 2650: rlast_time=rcurr_time;
1.349 brouard 2651: rlast_btime=rcurr_time;
1.157 brouard 2652: /* (void) gettimeofday(&curr_time,&tzp); */
2653: rcurr_time = time(NULL);
2654: curr_time = *localtime(&rcurr_time);
1.337 brouard 2655: /* 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); */
2656: /* 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 2657: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
2658: 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);
2659: 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);
2660: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2661: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2662: for (i=1;i<=n;i++) {
1.126 brouard 2663: fprintf(ficrespow," %.12lf", p[i]);
2664: }
1.239 brouard 2665: fprintf(ficrespow,"\n");fflush(ficrespow);
2666: printf("\n#model= 1 + age ");
2667: fprintf(ficlog,"\n#model= 1 + age ");
2668: if(nagesqr==1){
1.241 brouard 2669: printf(" + age*age ");
2670: fprintf(ficlog," + age*age ");
1.239 brouard 2671: }
2672: for(j=1;j <=ncovmodel-2;j++){
2673: if(Typevar[j]==0) {
2674: printf(" + V%d ",Tvar[j]);
2675: fprintf(ficlog," + V%d ",Tvar[j]);
2676: }else if(Typevar[j]==1) {
2677: printf(" + V%d*age ",Tvar[j]);
2678: fprintf(ficlog," + V%d*age ",Tvar[j]);
2679: }else if(Typevar[j]==2) {
2680: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2681: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 2682: }else if(Typevar[j]==3) {
2683: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2684: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2685: }
2686: }
1.126 brouard 2687: printf("\n");
1.239 brouard 2688: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2689: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2690: fprintf(ficlog,"\n");
1.239 brouard 2691: for(i=1,jk=1; i <=nlstate; i++){
2692: for(k=1; k <=(nlstate+ndeath); k++){
2693: if (k != i) {
2694: printf("%d%d ",i,k);
2695: fprintf(ficlog,"%d%d ",i,k);
2696: for(j=1; j <=ncovmodel; j++){
2697: printf("%12.7f ",p[jk]);
2698: fprintf(ficlog,"%12.7f ",p[jk]);
2699: jk++;
2700: }
2701: printf("\n");
2702: fprintf(ficlog,"\n");
2703: }
2704: }
2705: }
1.241 brouard 2706: if(*iter <=3 && *iter >1){
1.157 brouard 2707: tml = *localtime(&rcurr_time);
2708: strcpy(strcurr,asctime(&tml));
2709: rforecast_time=rcurr_time;
1.126 brouard 2710: itmp = strlen(strcurr);
2711: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2712: strcurr[itmp-1]='\0';
1.162 brouard 2713: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2714: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 2715: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
2716: niterf=nBigterf*ncovmodel;
2717: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2718: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2719: forecast_time = *localtime(&rforecast_time);
2720: strcpy(strfor,asctime(&forecast_time));
2721: itmp = strlen(strfor);
2722: if(strfor[itmp-1]=='\n')
2723: strfor[itmp-1]='\0';
1.349 brouard 2724: 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);
2725: 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 2726: }
2727: }
1.187 brouard 2728: for (i=1;i<=n;i++) { /* For each direction i */
2729: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2730: fptt=(*fret);
2731: #ifdef DEBUG
1.203 brouard 2732: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2733: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2734: #endif
1.203 brouard 2735: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2736: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2737: #ifdef LINMINORIGINAL
1.188 brouard 2738: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2739: #else
2740: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2741: flatdir[i]=flat; /* Function is vanishing in that direction i */
2742: #endif
2743: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2744: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2745: /* because that direction will be replaced unless the gain del is small */
2746: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2747: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2748: /* with the new direction. */
2749: del=fabs(fptt-(*fret));
2750: ibig=i;
1.126 brouard 2751: }
2752: #ifdef DEBUG
2753: printf("%d %.12e",i,(*fret));
2754: fprintf(ficlog,"%d %.12e",i,(*fret));
2755: for (j=1;j<=n;j++) {
1.224 brouard 2756: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2757: printf(" x(%d)=%.12e",j,xit[j]);
2758: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2759: }
2760: for(j=1;j<=n;j++) {
1.225 brouard 2761: printf(" p(%d)=%.12e",j,p[j]);
2762: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2763: }
2764: printf("\n");
2765: fprintf(ficlog,"\n");
2766: #endif
1.187 brouard 2767: } /* end loop on each direction i */
2768: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2769: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2770: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2771: for(j=1;j<=n;j++) {
2772: if(flatdir[j] >0){
2773: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2774: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2775: }
1.319 brouard 2776: /* printf("\n"); */
2777: /* fprintf(ficlog,"\n"); */
2778: }
1.243 brouard 2779: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2780: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2781: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2782: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2783: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2784: /* decreased of more than 3.84 */
2785: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2786: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2787: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2788:
1.188 brouard 2789: /* Starting the program with initial values given by a former maximization will simply change */
2790: /* the scales of the directions and the directions, because the are reset to canonical directions */
2791: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2792: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2793: #ifdef DEBUG
2794: int k[2],l;
2795: k[0]=1;
2796: k[1]=-1;
2797: printf("Max: %.12e",(*func)(p));
2798: fprintf(ficlog,"Max: %.12e",(*func)(p));
2799: for (j=1;j<=n;j++) {
2800: printf(" %.12e",p[j]);
2801: fprintf(ficlog," %.12e",p[j]);
2802: }
2803: printf("\n");
2804: fprintf(ficlog,"\n");
2805: for(l=0;l<=1;l++) {
2806: for (j=1;j<=n;j++) {
2807: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2808: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2809: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2810: }
2811: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2812: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2813: }
2814: #endif
2815:
2816: free_vector(xit,1,n);
2817: free_vector(xits,1,n);
2818: free_vector(ptt,1,n);
2819: free_vector(pt,1,n);
2820: return;
1.192 brouard 2821: } /* enough precision */
1.240 brouard 2822: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2823: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2824: ptt[j]=2.0*p[j]-pt[j];
2825: xit[j]=p[j]-pt[j];
2826: pt[j]=p[j];
2827: }
1.181 brouard 2828: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2829: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2830: if (*iter <=4) {
1.225 brouard 2831: #else
2832: #endif
1.224 brouard 2833: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2834: #else
1.161 brouard 2835: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2836: #endif
1.162 brouard 2837: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2838: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2839: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2840: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2841: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2842: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2843: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2844: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2845: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2846: /* Even if f3 <f1, directest can be negative and t >0 */
2847: /* mu² and del² are equal when f3=f1 */
2848: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2849: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2850: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2851: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2852: #ifdef NRCORIGINAL
2853: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2854: #else
2855: 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 2856: t= t- del*SQR(fp-fptt);
1.183 brouard 2857: #endif
1.202 brouard 2858: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2859: #ifdef DEBUG
1.181 brouard 2860: 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);
2861: 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 2862: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2863: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2864: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2865: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2866: 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);
2867: 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);
2868: #endif
1.183 brouard 2869: #ifdef POWELLORIGINAL
2870: if (t < 0.0) { /* Then we use it for new direction */
2871: #else
1.182 brouard 2872: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2873: 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 2874: 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 2875: 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 2876: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2877: }
1.181 brouard 2878: if (directest < 0.0) { /* Then we use it for new direction */
2879: #endif
1.191 brouard 2880: #ifdef DEBUGLINMIN
1.234 brouard 2881: printf("Before linmin in direction P%d-P0\n",n);
2882: for (j=1;j<=n;j++) {
2883: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2884: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2885: if(j % ncovmodel == 0){
2886: printf("\n");
2887: fprintf(ficlog,"\n");
2888: }
2889: }
1.224 brouard 2890: #endif
2891: #ifdef LINMINORIGINAL
1.234 brouard 2892: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2893: #else
1.234 brouard 2894: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2895: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2896: #endif
1.234 brouard 2897:
1.191 brouard 2898: #ifdef DEBUGLINMIN
1.234 brouard 2899: for (j=1;j<=n;j++) {
2900: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2901: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2902: if(j % ncovmodel == 0){
2903: printf("\n");
2904: fprintf(ficlog,"\n");
2905: }
2906: }
1.224 brouard 2907: #endif
1.234 brouard 2908: for (j=1;j<=n;j++) {
2909: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2910: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2911: }
1.224 brouard 2912: #ifdef LINMINORIGINAL
2913: #else
1.234 brouard 2914: for (j=1, flatd=0;j<=n;j++) {
2915: if(flatdir[j]>0)
2916: flatd++;
2917: }
2918: if(flatd >0){
1.255 brouard 2919: printf("%d flat directions: ",flatd);
2920: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2921: for (j=1;j<=n;j++) {
2922: if(flatdir[j]>0){
2923: printf("%d ",j);
2924: fprintf(ficlog,"%d ",j);
2925: }
2926: }
2927: printf("\n");
2928: fprintf(ficlog,"\n");
1.319 brouard 2929: #ifdef FLATSUP
2930: free_vector(xit,1,n);
2931: free_vector(xits,1,n);
2932: free_vector(ptt,1,n);
2933: free_vector(pt,1,n);
2934: return;
2935: #endif
1.234 brouard 2936: }
1.191 brouard 2937: #endif
1.234 brouard 2938: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2939: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2940:
1.126 brouard 2941: #ifdef DEBUG
1.234 brouard 2942: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2943: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2944: for(j=1;j<=n;j++){
2945: printf(" %lf",xit[j]);
2946: fprintf(ficlog," %lf",xit[j]);
2947: }
2948: printf("\n");
2949: fprintf(ficlog,"\n");
1.126 brouard 2950: #endif
1.192 brouard 2951: } /* end of t or directest negative */
1.224 brouard 2952: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2953: #else
1.234 brouard 2954: } /* end if (fptt < fp) */
1.192 brouard 2955: #endif
1.225 brouard 2956: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2957: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2958: #else
1.224 brouard 2959: #endif
1.234 brouard 2960: } /* loop iteration */
1.126 brouard 2961: }
1.234 brouard 2962:
1.126 brouard 2963: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2964:
1.235 brouard 2965: 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 2966: {
1.338 brouard 2967: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2968: * (and selected quantitative values in nres)
2969: * by left multiplying the unit
2970: * matrix by transitions matrix until convergence is reached with precision ftolpl
2971: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2972: * Wx is row vector: population in state 1, population in state 2, population dead
2973: * or prevalence in state 1, prevalence in state 2, 0
2974: * newm is the matrix after multiplications, its rows are identical at a factor.
2975: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2976: * Output is prlim.
2977: * Initial matrix pimij
2978: */
1.206 brouard 2979: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2980: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2981: /* 0, 0 , 1} */
2982: /*
2983: * and after some iteration: */
2984: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2985: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2986: /* 0, 0 , 1} */
2987: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2988: /* {0.51571254859325999, 0.4842874514067399, */
2989: /* 0.51326036147820708, 0.48673963852179264} */
2990: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2991:
1.332 brouard 2992: int i, ii,j,k, k1;
1.209 brouard 2993: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2994: /* double **matprod2(); */ /* test */
1.218 brouard 2995: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2996: double **newm;
1.209 brouard 2997: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2998: int ncvloop=0;
1.288 brouard 2999: int first=0;
1.169 brouard 3000:
1.209 brouard 3001: min=vector(1,nlstate);
3002: max=vector(1,nlstate);
3003: meandiff=vector(1,nlstate);
3004:
1.218 brouard 3005: /* Starting with matrix unity */
1.126 brouard 3006: for (ii=1;ii<=nlstate+ndeath;ii++)
3007: for (j=1;j<=nlstate+ndeath;j++){
3008: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3009: }
1.169 brouard 3010:
3011: cov[1]=1.;
3012:
3013: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 3014: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 3015: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 3016: ncvloop++;
1.126 brouard 3017: newm=savm;
3018: /* Covariates have to be included here again */
1.138 brouard 3019: cov[2]=agefin;
1.319 brouard 3020: if(nagesqr==1){
3021: cov[3]= agefin*agefin;
3022: }
1.332 brouard 3023: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3024: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3025: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3026: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3027: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3028: }else{
3029: cov[2+nagesqr+k1]=precov[nres][k1];
3030: }
3031: }/* End of loop on model equation */
3032:
3033: /* Start of old code (replaced by a loop on position in the model equation */
3034: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3035: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3036: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3037: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3038: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3039: /* * k 1 2 3 4 5 6 7 8 */
3040: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3041: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3042: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3043: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3044: /* *nsd=3 (1) (2) (3) */
3045: /* *TvarsD[nsd] [1]=2 1 3 */
3046: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3047: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3048: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3049: /* *Tvard[] [1][1]=1 [2][1]=1 */
3050: /* * [1][2]=3 [2][2]=2 */
3051: /* *Tprod[](=k) [1]=1 [2]=8 */
3052: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3053: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3054: /* *TvarsDpType */
3055: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3056: /* * nsd=1 (1) (2) */
3057: /* *TvarsD[nsd] 3 2 */
3058: /* *TnsdVar (3)=1 (2)=2 */
3059: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3060: /* *Tage[] [1]=2 [2]= 3 */
3061: /* *\/ */
3062: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3063: /* /\* 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)); *\/ */
3064: /* } */
3065: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3066: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3067: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3068: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3069: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3070: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3071: /* /\* 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]); *\/ */
3072: /* } */
3073: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3074: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3075: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3076: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3077: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3078: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3079: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3080: /* } */
3081: /* /\* 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]); *\/ */
3082: /* } */
3083: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3084: /* /\* 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]); *\/ */
3085: /* if(Dummy[Tvard[k][1]]==0){ */
3086: /* if(Dummy[Tvard[k][2]]==0){ */
3087: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3088: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3089: /* }else{ */
3090: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3091: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3092: /* } */
3093: /* }else{ */
3094: /* if(Dummy[Tvard[k][2]]==0){ */
3095: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3096: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3097: /* }else{ */
3098: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3099: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3100: /* } */
3101: /* } */
3102: /* } /\* End product without age *\/ */
3103: /* ENd of old code */
1.138 brouard 3104: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3105: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3106: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3107: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3108: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3109: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3110: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3111:
1.126 brouard 3112: savm=oldm;
3113: oldm=newm;
1.209 brouard 3114:
3115: for(j=1; j<=nlstate; j++){
3116: max[j]=0.;
3117: min[j]=1.;
3118: }
3119: for(i=1;i<=nlstate;i++){
3120: sumnew=0;
3121: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3122: for(j=1; j<=nlstate; j++){
3123: prlim[i][j]= newm[i][j]/(1-sumnew);
3124: max[j]=FMAX(max[j],prlim[i][j]);
3125: min[j]=FMIN(min[j],prlim[i][j]);
3126: }
3127: }
3128:
1.126 brouard 3129: maxmax=0.;
1.209 brouard 3130: for(j=1; j<=nlstate; j++){
3131: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3132: maxmax=FMAX(maxmax,meandiff[j]);
3133: /* 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 3134: } /* j loop */
1.203 brouard 3135: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3136: /* 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 3137: if(maxmax < ftolpl){
1.209 brouard 3138: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3139: free_vector(min,1,nlstate);
3140: free_vector(max,1,nlstate);
3141: free_vector(meandiff,1,nlstate);
1.126 brouard 3142: return prlim;
3143: }
1.288 brouard 3144: } /* agefin loop */
1.208 brouard 3145: /* After some age loop it doesn't converge */
1.288 brouard 3146: if(!first){
3147: first=1;
3148: 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 3149: 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);
3150: }else if (first >=1 && first <10){
3151: 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);
3152: first++;
3153: }else if (first ==10){
3154: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
3155: 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");
3156: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3157: first++;
1.288 brouard 3158: }
3159:
1.209 brouard 3160: /* 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); */
3161: free_vector(min,1,nlstate);
3162: free_vector(max,1,nlstate);
3163: free_vector(meandiff,1,nlstate);
1.208 brouard 3164:
1.169 brouard 3165: return prlim; /* should not reach here */
1.126 brouard 3166: }
3167:
1.217 brouard 3168:
3169: /**** Back Prevalence limit (stable or period prevalence) ****************/
3170:
1.218 brouard 3171: /* 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) */
3172: /* 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 3173: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3174: {
1.264 brouard 3175: /* 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 3176: matrix by transitions matrix until convergence is reached with precision ftolpl */
3177: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3178: /* Wx is row vector: population in state 1, population in state 2, population dead */
3179: /* or prevalence in state 1, prevalence in state 2, 0 */
3180: /* newm is the matrix after multiplications, its rows are identical at a factor */
3181: /* Initial matrix pimij */
3182: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3183: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3184: /* 0, 0 , 1} */
3185: /*
3186: * and after some iteration: */
3187: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3188: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3189: /* 0, 0 , 1} */
3190: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3191: /* {0.51571254859325999, 0.4842874514067399, */
3192: /* 0.51326036147820708, 0.48673963852179264} */
3193: /* If we start from prlim again, prlim tends to a constant matrix */
3194:
1.332 brouard 3195: int i, ii,j,k, k1;
1.247 brouard 3196: int first=0;
1.217 brouard 3197: double *min, *max, *meandiff, maxmax,sumnew=0.;
3198: /* double **matprod2(); */ /* test */
3199: double **out, cov[NCOVMAX+1], **bmij();
3200: double **newm;
1.218 brouard 3201: double **dnewm, **doldm, **dsavm; /* for use */
3202: double **oldm, **savm; /* for use */
3203:
1.217 brouard 3204: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3205: int ncvloop=0;
3206:
3207: min=vector(1,nlstate);
3208: max=vector(1,nlstate);
3209: meandiff=vector(1,nlstate);
3210:
1.266 brouard 3211: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3212: oldm=oldms; savm=savms;
3213:
3214: /* Starting with matrix unity */
3215: for (ii=1;ii<=nlstate+ndeath;ii++)
3216: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3217: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3218: }
3219:
3220: cov[1]=1.;
3221:
3222: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3223: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3224: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3225: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3226: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3227: ncvloop++;
1.218 brouard 3228: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3229: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3230: /* Covariates have to be included here again */
3231: cov[2]=agefin;
1.319 brouard 3232: if(nagesqr==1){
1.217 brouard 3233: cov[3]= agefin*agefin;;
1.319 brouard 3234: }
1.332 brouard 3235: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3236: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3237: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3238: }else{
1.332 brouard 3239: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3240: }
1.332 brouard 3241: }/* End of loop on model equation */
3242:
3243: /* Old code */
3244:
3245: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3246: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3247: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3248: /* /\* 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)); *\/ */
3249: /* } */
3250: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3251: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3252: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3253: /* /\* /\\* 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])]); *\\/ *\/ */
3254: /* /\* } *\/ */
3255: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3256: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3257: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3258: /* /\* 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]); *\/ */
3259: /* } */
3260: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3261: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3262: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3263: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3264: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3265: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3266: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3267: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3268: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3269: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3270: /* } */
3271: /* /\* 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]); *\/ */
3272: /* } */
3273: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3274: /* /\* 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]); *\/ */
3275: /* if(Dummy[Tvard[k][1]]==0){ */
3276: /* if(Dummy[Tvard[k][2]]==0){ */
3277: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3278: /* }else{ */
3279: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3280: /* } */
3281: /* }else{ */
3282: /* if(Dummy[Tvard[k][2]]==0){ */
3283: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3284: /* }else{ */
3285: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3286: /* } */
3287: /* } */
3288: /* } */
1.217 brouard 3289:
3290: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3291: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3292: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3293: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3294: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3295: /* ij should be linked to the correct index of cov */
3296: /* age and covariate values ij are in 'cov', but we need to pass
3297: * ij for the observed prevalence at age and status and covariate
3298: * number: prevacurrent[(int)agefin][ii][ij]
3299: */
3300: /* 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 *\/ */
3301: /* 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 *\/ */
3302: 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 3303: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3304: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3305: /* for(i=1; i<=nlstate+ndeath; i++) { */
3306: /* printf("%d newm= ",i); */
3307: /* for(j=1;j<=nlstate+ndeath;j++) { */
3308: /* printf("%f ",newm[i][j]); */
3309: /* } */
3310: /* printf("oldm * "); */
3311: /* for(j=1;j<=nlstate+ndeath;j++) { */
3312: /* printf("%f ",oldm[i][j]); */
3313: /* } */
1.268 brouard 3314: /* printf(" bmmij "); */
1.266 brouard 3315: /* for(j=1;j<=nlstate+ndeath;j++) { */
3316: /* printf("%f ",pmmij[i][j]); */
3317: /* } */
3318: /* printf("\n"); */
3319: /* } */
3320: /* } */
1.217 brouard 3321: savm=oldm;
3322: oldm=newm;
1.266 brouard 3323:
1.217 brouard 3324: for(j=1; j<=nlstate; j++){
3325: max[j]=0.;
3326: min[j]=1.;
3327: }
3328: for(j=1; j<=nlstate; j++){
3329: for(i=1;i<=nlstate;i++){
1.234 brouard 3330: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3331: bprlim[i][j]= newm[i][j];
3332: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3333: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3334: }
3335: }
1.218 brouard 3336:
1.217 brouard 3337: maxmax=0.;
3338: for(i=1; i<=nlstate; i++){
1.318 brouard 3339: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3340: maxmax=FMAX(maxmax,meandiff[i]);
3341: /* 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 3342: } /* i loop */
1.217 brouard 3343: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3344: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3345: if(maxmax < ftolpl){
1.220 brouard 3346: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3347: free_vector(min,1,nlstate);
3348: free_vector(max,1,nlstate);
3349: free_vector(meandiff,1,nlstate);
3350: return bprlim;
3351: }
1.288 brouard 3352: } /* agefin loop */
1.217 brouard 3353: /* After some age loop it doesn't converge */
1.288 brouard 3354: if(!first){
1.247 brouard 3355: first=1;
3356: 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\
3357: 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);
3358: }
3359: 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 3360: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
3361: /* 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); */
3362: free_vector(min,1,nlstate);
3363: free_vector(max,1,nlstate);
3364: free_vector(meandiff,1,nlstate);
3365:
3366: return bprlim; /* should not reach here */
3367: }
3368:
1.126 brouard 3369: /*************** transition probabilities ***************/
3370:
3371: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3372: {
1.138 brouard 3373: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3374: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3375: model to the ncovmodel covariates (including constant and age).
3376: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3377: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3378: ncth covariate in the global vector x is given by the formula:
3379: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3380: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3381: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3382: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3383: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3384: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3385: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3386: */
3387: double s1, lnpijopii;
1.126 brouard 3388: /*double t34;*/
1.164 brouard 3389: int i,j, nc, ii, jj;
1.126 brouard 3390:
1.223 brouard 3391: for(i=1; i<= nlstate; i++){
3392: for(j=1; j<i;j++){
3393: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3394: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3395: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3396: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3397: }
3398: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3399: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3400: }
3401: for(j=i+1; j<=nlstate+ndeath;j++){
3402: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3403: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3404: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3405: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,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: }
1.218 brouard 3411:
1.223 brouard 3412: for(i=1; i<= nlstate; i++){
3413: s1=0;
3414: for(j=1; j<i; j++){
1.339 brouard 3415: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3416: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3417: }
3418: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3419: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3420: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3421: }
3422: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3423: ps[i][i]=1./(s1+1.);
3424: /* Computing other pijs */
3425: for(j=1; j<i; j++)
1.325 brouard 3426: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3427: for(j=i+1; j<=nlstate+ndeath; j++)
3428: ps[i][j]= exp(ps[i][j])*ps[i][i];
3429: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3430: } /* end i */
1.218 brouard 3431:
1.223 brouard 3432: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3433: for(jj=1; jj<= nlstate+ndeath; jj++){
3434: ps[ii][jj]=0;
3435: ps[ii][ii]=1;
3436: }
3437: }
1.294 brouard 3438:
3439:
1.223 brouard 3440: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3441: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3442: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3443: /* } */
3444: /* printf("\n "); */
3445: /* } */
3446: /* printf("\n ");printf("%lf ",cov[2]);*/
3447: /*
3448: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3449: goto end;*/
1.266 brouard 3450: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3451: }
3452:
1.218 brouard 3453: /*************** backward transition probabilities ***************/
3454:
3455: /* 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 ) */
3456: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3457: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3458: {
1.302 brouard 3459: /* 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 3460: * 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 3461: */
1.218 brouard 3462: int i, ii, j,k;
1.222 brouard 3463:
3464: double **out, **pmij();
3465: double sumnew=0.;
1.218 brouard 3466: double agefin;
1.292 brouard 3467: 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 3468: double **dnewm, **dsavm, **doldm;
3469: double **bbmij;
3470:
1.218 brouard 3471: doldm=ddoldms; /* global pointers */
1.222 brouard 3472: dnewm=ddnewms;
3473: dsavm=ddsavms;
1.318 brouard 3474:
3475: /* Debug */
3476: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3477: agefin=cov[2];
1.268 brouard 3478: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3479: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3480: the observed prevalence (with this covariate ij) at beginning of transition */
3481: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3482:
3483: /* P_x */
1.325 brouard 3484: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3485: /* outputs pmmij which is a stochastic matrix in row */
3486:
3487: /* Diag(w_x) */
1.292 brouard 3488: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3489: sumnew=0.;
1.269 brouard 3490: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3491: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3492: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3493: sumnew+=prevacurrent[(int)agefin][ii][ij];
3494: }
3495: if(sumnew >0.01){ /* At least some value in the prevalence */
3496: for (ii=1;ii<=nlstate+ndeath;ii++){
3497: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3498: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3499: }
3500: }else{
3501: for (ii=1;ii<=nlstate+ndeath;ii++){
3502: for (j=1;j<=nlstate+ndeath;j++)
3503: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3504: }
3505: /* if(sumnew <0.9){ */
3506: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3507: /* } */
3508: }
3509: k3=0.0; /* We put the last diagonal to 0 */
3510: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3511: doldm[ii][ii]= k3;
3512: }
3513: /* End doldm, At the end doldm is diag[(w_i)] */
3514:
1.292 brouard 3515: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3516: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3517:
1.292 brouard 3518: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3519: /* 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 3520: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3521: sumnew=0.;
1.222 brouard 3522: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3523: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3524: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3525: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3526: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3527: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3528: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3529: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3530: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3531: /* }else */
1.268 brouard 3532: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3533: } /*End ii */
3534: } /* 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 */
3535:
1.292 brouard 3536: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3537: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3538: /* end bmij */
1.266 brouard 3539: return ps; /*pointer is unchanged */
1.218 brouard 3540: }
1.217 brouard 3541: /*************** transition probabilities ***************/
3542:
1.218 brouard 3543: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3544: {
3545: /* According to parameters values stored in x and the covariate's values stored in cov,
3546: computes the probability to be observed in state j being in state i by appying the
3547: model to the ncovmodel covariates (including constant and age).
3548: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3549: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3550: ncth covariate in the global vector x is given by the formula:
3551: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3552: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3553: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3554: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3555: Outputs ps[i][j] the probability to be observed in j being in j according to
3556: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3557: */
3558: double s1, lnpijopii;
3559: /*double t34;*/
3560: int i,j, nc, ii, jj;
3561:
1.234 brouard 3562: for(i=1; i<= nlstate; i++){
3563: for(j=1; j<i;j++){
3564: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3565: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3566: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3567: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3568: }
3569: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3570: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3571: }
3572: for(j=i+1; j<=nlstate+ndeath;j++){
3573: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3574: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3575: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3576: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3577: }
3578: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3579: }
3580: }
3581:
3582: for(i=1; i<= nlstate; i++){
3583: s1=0;
3584: for(j=1; j<i; j++){
3585: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3586: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3587: }
3588: for(j=i+1; j<=nlstate+ndeath; j++){
3589: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3590: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3591: }
3592: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3593: ps[i][i]=1./(s1+1.);
3594: /* Computing other pijs */
3595: for(j=1; j<i; j++)
3596: ps[i][j]= exp(ps[i][j])*ps[i][i];
3597: for(j=i+1; j<=nlstate+ndeath; j++)
3598: ps[i][j]= exp(ps[i][j])*ps[i][i];
3599: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3600: } /* end i */
3601:
3602: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3603: for(jj=1; jj<= nlstate+ndeath; jj++){
3604: ps[ii][jj]=0;
3605: ps[ii][ii]=1;
3606: }
3607: }
1.296 brouard 3608: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3609: for(jj=1; jj<= nlstate+ndeath; jj++){
3610: s1=0.;
3611: for(ii=1; ii<= nlstate+ndeath; ii++){
3612: s1+=ps[ii][jj];
3613: }
3614: for(ii=1; ii<= nlstate; ii++){
3615: ps[ii][jj]=ps[ii][jj]/s1;
3616: }
3617: }
3618: /* Transposition */
3619: for(jj=1; jj<= nlstate+ndeath; jj++){
3620: for(ii=jj; ii<= nlstate+ndeath; ii++){
3621: s1=ps[ii][jj];
3622: ps[ii][jj]=ps[jj][ii];
3623: ps[jj][ii]=s1;
3624: }
3625: }
3626: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3627: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3628: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3629: /* } */
3630: /* printf("\n "); */
3631: /* } */
3632: /* printf("\n ");printf("%lf ",cov[2]);*/
3633: /*
3634: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3635: goto end;*/
3636: return ps;
1.217 brouard 3637: }
3638:
3639:
1.126 brouard 3640: /**************** Product of 2 matrices ******************/
3641:
1.145 brouard 3642: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3643: {
3644: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3645: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3646: /* in, b, out are matrice of pointers which should have been initialized
3647: before: only the contents of out is modified. The function returns
3648: a pointer to pointers identical to out */
1.145 brouard 3649: int i, j, k;
1.126 brouard 3650: for(i=nrl; i<= nrh; i++)
1.145 brouard 3651: for(k=ncolol; k<=ncoloh; k++){
3652: out[i][k]=0.;
3653: for(j=ncl; j<=nch; j++)
3654: out[i][k] +=in[i][j]*b[j][k];
3655: }
1.126 brouard 3656: return out;
3657: }
3658:
3659:
3660: /************* Higher Matrix Product ***************/
3661:
1.235 brouard 3662: 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 3663: {
1.336 brouard 3664: /* Already optimized with precov.
3665: 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 3666: 'nhstepm*hstepm*stepm' months (i.e. until
3667: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3668: nhstepm*hstepm matrices.
3669: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3670: (typically every 2 years instead of every month which is too big
3671: for the memory).
3672: Model is determined by parameters x and covariates have to be
3673: included manually here.
3674:
3675: */
3676:
1.330 brouard 3677: int i, j, d, h, k, k1;
1.131 brouard 3678: double **out, cov[NCOVMAX+1];
1.126 brouard 3679: double **newm;
1.187 brouard 3680: double agexact;
1.214 brouard 3681: double agebegin, ageend;
1.126 brouard 3682:
3683: /* Hstepm could be zero and should return the unit matrix */
3684: for (i=1;i<=nlstate+ndeath;i++)
3685: for (j=1;j<=nlstate+ndeath;j++){
3686: oldm[i][j]=(i==j ? 1.0 : 0.0);
3687: po[i][j][0]=(i==j ? 1.0 : 0.0);
3688: }
3689: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3690: for(h=1; h <=nhstepm; h++){
3691: for(d=1; d <=hstepm; d++){
3692: newm=savm;
3693: /* Covariates have to be included here again */
3694: cov[1]=1.;
1.214 brouard 3695: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3696: cov[2]=agexact;
1.319 brouard 3697: if(nagesqr==1){
1.227 brouard 3698: cov[3]= agexact*agexact;
1.319 brouard 3699: }
1.330 brouard 3700: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3701: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3702: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3703: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3704: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3705: }else{
3706: cov[2+nagesqr+k1]=precov[nres][k1];
3707: }
3708: }/* End of loop on model equation */
3709: /* Old code */
3710: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3711: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3712: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3713: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3714: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3715: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3716: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3717: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3718: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3719: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3720: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3721: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3722: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3723: /* /\* 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]])); *\/ */
3724: /* 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); */
3725: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3726: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3727: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3728: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3729: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3730: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3731: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3732: /* 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]]); */
3733: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3734: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3735: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3736: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3737: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3738: /* 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]); */
3739: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3740:
3741: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3742: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3743: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3744: /* /\* *\/ */
1.330 brouard 3745: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3746: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3747: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3748: /* /\*cptcovage=2 1 2 *\/ */
3749: /* /\*Tage[k]= 5 8 *\/ */
3750: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3751: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3752: /* 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]]); */
3753: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3754: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3755: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3756: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3757: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3758: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3759: /* /\* 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); *\/ */
3760: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3761: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3762: /* /\* } *\/ */
3763: /* /\* 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]); *\/ */
3764: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3765: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3766: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3767: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3768: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3769: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3770: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3771: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3772: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3773:
1.332 brouard 3774: /* /\* 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])]); *\/ */
3775: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3776: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3777: /* 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]]); */
3778: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3779:
3780: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3781: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3782: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3783: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3784: /* /\* 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]])]; *\/ */
3785: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3786: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3787: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3788: /* /\* } *\/ */
3789: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3790: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3791: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3792: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3793: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3794: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3795: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3796: /* /\* } *\/ */
3797: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3798: /* }/\*end of products *\/ */
3799: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3800: /* for (k=1; k<=cptcovn;k++) */
3801: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3802: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3803: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3804: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3805: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3806:
3807:
1.126 brouard 3808: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3809: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3810: /* right multiplication of oldm by the current matrix */
1.126 brouard 3811: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3812: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3813: /* if((int)age == 70){ */
3814: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3815: /* for(i=1; i<=nlstate+ndeath; i++) { */
3816: /* printf("%d pmmij ",i); */
3817: /* for(j=1;j<=nlstate+ndeath;j++) { */
3818: /* printf("%f ",pmmij[i][j]); */
3819: /* } */
3820: /* printf(" oldm "); */
3821: /* for(j=1;j<=nlstate+ndeath;j++) { */
3822: /* printf("%f ",oldm[i][j]); */
3823: /* } */
3824: /* printf("\n"); */
3825: /* } */
3826: /* } */
1.126 brouard 3827: savm=oldm;
3828: oldm=newm;
3829: }
3830: for(i=1; i<=nlstate+ndeath; i++)
3831: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3832: po[i][j][h]=newm[i][j];
3833: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3834: }
1.128 brouard 3835: /*printf("h=%d ",h);*/
1.126 brouard 3836: } /* end h */
1.267 brouard 3837: /* printf("\n H=%d \n",h); */
1.126 brouard 3838: return po;
3839: }
3840:
1.217 brouard 3841: /************* Higher Back Matrix Product ***************/
1.218 brouard 3842: /* 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 3843: 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 3844: {
1.332 brouard 3845: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3846: computes the transition matrix starting at age 'age' over
1.217 brouard 3847: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3848: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3849: nhstepm*hstepm matrices.
3850: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3851: (typically every 2 years instead of every month which is too big
1.217 brouard 3852: for the memory).
1.218 brouard 3853: Model is determined by parameters x and covariates have to be
1.266 brouard 3854: included manually here. Then we use a call to bmij(x and cov)
3855: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3856: */
1.217 brouard 3857:
1.332 brouard 3858: int i, j, d, h, k, k1;
1.266 brouard 3859: double **out, cov[NCOVMAX+1], **bmij();
3860: double **newm, ***newmm;
1.217 brouard 3861: double agexact;
3862: double agebegin, ageend;
1.222 brouard 3863: double **oldm, **savm;
1.217 brouard 3864:
1.266 brouard 3865: newmm=po; /* To be saved */
3866: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3867: /* Hstepm could be zero and should return the unit matrix */
3868: for (i=1;i<=nlstate+ndeath;i++)
3869: for (j=1;j<=nlstate+ndeath;j++){
3870: oldm[i][j]=(i==j ? 1.0 : 0.0);
3871: po[i][j][0]=(i==j ? 1.0 : 0.0);
3872: }
3873: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3874: for(h=1; h <=nhstepm; h++){
3875: for(d=1; d <=hstepm; d++){
3876: newm=savm;
3877: /* Covariates have to be included here again */
3878: cov[1]=1.;
1.271 brouard 3879: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3880: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3881: /* Debug */
3882: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3883: cov[2]=agexact;
1.332 brouard 3884: if(nagesqr==1){
1.222 brouard 3885: cov[3]= agexact*agexact;
1.332 brouard 3886: }
3887: /** New code */
3888: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3889: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3890: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3891: }else{
1.332 brouard 3892: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3893: }
1.332 brouard 3894: }/* End of loop on model equation */
3895: /** End of new code */
3896: /** This was old code */
3897: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3898: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3899: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3900: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3901: /* /\* 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)); *\/ */
3902: /* } */
3903: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3904: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3905: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3906: /* /\* 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]); *\/ */
3907: /* } */
3908: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3909: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3910: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3911: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3912: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3913: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3914: /* } */
3915: /* /\* 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]); *\/ */
3916: /* } */
3917: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3918: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3919: /* if(Dummy[Tvard[k][1]]==0){ */
3920: /* if(Dummy[Tvard[k][2]]==0){ */
3921: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3922: /* }else{ */
3923: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3924: /* } */
3925: /* }else{ */
3926: /* if(Dummy[Tvard[k][2]]==0){ */
3927: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3928: /* }else{ */
3929: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3930: /* } */
3931: /* } */
3932: /* } */
3933: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3934: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3935: /** End of old code */
3936:
1.218 brouard 3937: /* Careful transposed matrix */
1.266 brouard 3938: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3939: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3940: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3941: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3942: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3943: /* if((int)age == 70){ */
3944: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3945: /* for(i=1; i<=nlstate+ndeath; i++) { */
3946: /* printf("%d pmmij ",i); */
3947: /* for(j=1;j<=nlstate+ndeath;j++) { */
3948: /* printf("%f ",pmmij[i][j]); */
3949: /* } */
3950: /* printf(" oldm "); */
3951: /* for(j=1;j<=nlstate+ndeath;j++) { */
3952: /* printf("%f ",oldm[i][j]); */
3953: /* } */
3954: /* printf("\n"); */
3955: /* } */
3956: /* } */
3957: savm=oldm;
3958: oldm=newm;
3959: }
3960: for(i=1; i<=nlstate+ndeath; i++)
3961: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3962: po[i][j][h]=newm[i][j];
1.268 brouard 3963: /* if(h==nhstepm) */
3964: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3965: }
1.268 brouard 3966: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3967: } /* end h */
1.268 brouard 3968: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3969: return po;
3970: }
3971:
3972:
1.162 brouard 3973: #ifdef NLOPT
3974: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3975: double fret;
3976: double *xt;
3977: int j;
3978: myfunc_data *d2 = (myfunc_data *) pd;
3979: /* xt = (p1-1); */
3980: xt=vector(1,n);
3981: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3982:
3983: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3984: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3985: printf("Function = %.12lf ",fret);
3986: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3987: printf("\n");
3988: free_vector(xt,1,n);
3989: return fret;
3990: }
3991: #endif
1.126 brouard 3992:
3993: /*************** log-likelihood *************/
3994: double func( double *x)
3995: {
1.336 brouard 3996: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3997: int ioffset=0;
1.339 brouard 3998: int ipos=0,iposold=0,ncovv=0;
3999:
1.340 brouard 4000: double cotvarv, cotvarvold;
1.226 brouard 4001: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
4002: double **out;
4003: double lli; /* Individual log likelihood */
4004: int s1, s2;
1.228 brouard 4005: 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 4006:
1.226 brouard 4007: double bbh, survp;
4008: double agexact;
1.336 brouard 4009: double agebegin, ageend;
1.226 brouard 4010: /*extern weight */
4011: /* We are differentiating ll according to initial status */
4012: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4013: /*for(i=1;i<imx;i++)
4014: printf(" %d\n",s[4][i]);
4015: */
1.162 brouard 4016:
1.226 brouard 4017: ++countcallfunc;
1.162 brouard 4018:
1.226 brouard 4019: cov[1]=1.;
1.126 brouard 4020:
1.226 brouard 4021: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4022: ioffset=0;
1.226 brouard 4023: if(mle==1){
4024: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4025: /* Computes the values of the ncovmodel covariates of the model
4026: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4027: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4028: to be observed in j being in i according to the model.
4029: */
1.243 brouard 4030: ioffset=2+nagesqr ;
1.233 brouard 4031: /* Fixed */
1.345 brouard 4032: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4033: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4034: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4035: /* 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 4036: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4037: 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 4038: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4039: }
1.226 brouard 4040: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4041: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4042: has been calculated etc */
4043: /* For an individual i, wav[i] gives the number of effective waves */
4044: /* We compute the contribution to Likelihood of each effective transition
4045: mw[mi][i] is real wave of the mi th effectve wave */
4046: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4047: s2=s[mw[mi+1][i]][i];
1.341 brouard 4048: 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 4049: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4050: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4051: */
1.336 brouard 4052: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4053: /* Wave varying (but not age varying) */
1.339 brouard 4054: /* 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*\/ */
4055: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4056: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4057: /* } */
1.340 brouard 4058: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4059: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4060: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4061: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4062: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4063: }else{ /* fixed covariate */
1.345 brouard 4064: 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 4065: }
1.339 brouard 4066: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4067: cotvarvold=cotvarv;
4068: }else{ /* A second product */
4069: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4070: }
4071: iposold=ipos;
1.340 brouard 4072: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4073: }
1.339 brouard 4074: /* for products of time varying to be done */
1.234 brouard 4075: for (ii=1;ii<=nlstate+ndeath;ii++)
4076: for (j=1;j<=nlstate+ndeath;j++){
4077: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4078: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4079: }
1.336 brouard 4080:
4081: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4082: 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 4083: for(d=0; d<dh[mi][i]; d++){
4084: newm=savm;
4085: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4086: cov[2]=agexact;
4087: if(nagesqr==1)
4088: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 4089: /* for (kk=1; kk<=cptcovage;kk++) { */
4090: /* if(!FixedV[Tvar[Tage[kk]]]) */
4091: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
4092: /* else */
4093: /* 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) *\/ */
4094: /* } */
4095: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4096: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4097: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4098: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4099: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4100: }else{ /* fixed covariate */
4101: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4102: }
4103: if(ipos!=iposold){ /* Not a product or first of a product */
4104: cotvarvold=cotvarv;
4105: }else{ /* A second product */
4106: cotvarv=cotvarv*cotvarvold;
4107: }
4108: iposold=ipos;
4109: cov[ioffset+ipos]=cotvarv*agexact;
4110: /* For products */
1.234 brouard 4111: }
1.349 brouard 4112:
1.234 brouard 4113: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4114: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4115: savm=oldm;
4116: oldm=newm;
4117: } /* end mult */
4118:
4119: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4120: /* But now since version 0.9 we anticipate for bias at large stepm.
4121: * If stepm is larger than one month (smallest stepm) and if the exact delay
4122: * (in months) between two waves is not a multiple of stepm, we rounded to
4123: * the nearest (and in case of equal distance, to the lowest) interval but now
4124: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4125: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4126: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4127: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4128: * -stepm/2 to stepm/2 .
4129: * For stepm=1 the results are the same as for previous versions of Imach.
4130: * For stepm > 1 the results are less biased than in previous versions.
4131: */
1.234 brouard 4132: s1=s[mw[mi][i]][i];
4133: s2=s[mw[mi+1][i]][i];
4134: bbh=(double)bh[mi][i]/(double)stepm;
4135: /* bias bh is positive if real duration
4136: * is higher than the multiple of stepm and negative otherwise.
4137: */
4138: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4139: if( s2 > nlstate){
4140: /* i.e. if s2 is a death state and if the date of death is known
4141: then the contribution to the likelihood is the probability to
4142: die between last step unit time and current step unit time,
4143: which is also equal to probability to die before dh
4144: minus probability to die before dh-stepm .
4145: In version up to 0.92 likelihood was computed
4146: as if date of death was unknown. Death was treated as any other
4147: health state: the date of the interview describes the actual state
4148: and not the date of a change in health state. The former idea was
4149: to consider that at each interview the state was recorded
4150: (healthy, disable or death) and IMaCh was corrected; but when we
4151: introduced the exact date of death then we should have modified
4152: the contribution of an exact death to the likelihood. This new
4153: contribution is smaller and very dependent of the step unit
4154: stepm. It is no more the probability to die between last interview
4155: and month of death but the probability to survive from last
4156: interview up to one month before death multiplied by the
4157: probability to die within a month. Thanks to Chris
4158: Jackson for correcting this bug. Former versions increased
4159: mortality artificially. The bad side is that we add another loop
4160: which slows down the processing. The difference can be up to 10%
4161: lower mortality.
4162: */
4163: /* If, at the beginning of the maximization mostly, the
4164: cumulative probability or probability to be dead is
4165: constant (ie = 1) over time d, the difference is equal to
4166: 0. out[s1][3] = savm[s1][3]: probability, being at state
4167: s1 at precedent wave, to be dead a month before current
4168: wave is equal to probability, being at state s1 at
4169: precedent wave, to be dead at mont of the current
4170: wave. Then the observed probability (that this person died)
4171: is null according to current estimated parameter. In fact,
4172: it should be very low but not zero otherwise the log go to
4173: infinity.
4174: */
1.183 brouard 4175: /* #ifdef INFINITYORIGINAL */
4176: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4177: /* #else */
4178: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4179: /* lli=log(mytinydouble); */
4180: /* else */
4181: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4182: /* #endif */
1.226 brouard 4183: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4184:
1.226 brouard 4185: } else if ( s2==-1 ) { /* alive */
4186: for (j=1,survp=0. ; j<=nlstate; j++)
4187: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4188: /*survp += out[s1][j]; */
4189: lli= log(survp);
4190: }
1.336 brouard 4191: /* else if (s2==-4) { */
4192: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4193: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4194: /* lli= log(survp); */
4195: /* } */
4196: /* else if (s2==-5) { */
4197: /* for (j=1,survp=0. ; j<=2; j++) */
4198: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4199: /* lli= log(survp); */
4200: /* } */
1.226 brouard 4201: else{
4202: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4203: /* 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 */
4204: }
4205: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4206: /*if(lli ==000.0)*/
1.340 brouard 4207: /* 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 4208: ipmx +=1;
4209: sw += weight[i];
4210: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4211: /* if (lli < log(mytinydouble)){ */
4212: /* 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); */
4213: /* 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]); */
4214: /* } */
4215: } /* end of wave */
4216: } /* end of individual */
4217: } else if(mle==2){
4218: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4219: ioffset=2+nagesqr ;
4220: for (k=1; k<=ncovf;k++)
4221: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4222: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4223: for(k=1; k <= ncovv ; k++){
1.341 brouard 4224: 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 4225: }
1.226 brouard 4226: for (ii=1;ii<=nlstate+ndeath;ii++)
4227: for (j=1;j<=nlstate+ndeath;j++){
4228: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4229: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4230: }
4231: for(d=0; d<=dh[mi][i]; d++){
4232: newm=savm;
4233: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4234: cov[2]=agexact;
4235: if(nagesqr==1)
4236: cov[3]= agexact*agexact;
4237: for (kk=1; kk<=cptcovage;kk++) {
4238: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4239: }
4240: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4241: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4242: savm=oldm;
4243: oldm=newm;
4244: } /* end mult */
4245:
4246: s1=s[mw[mi][i]][i];
4247: s2=s[mw[mi+1][i]][i];
4248: bbh=(double)bh[mi][i]/(double)stepm;
4249: 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 */
4250: ipmx +=1;
4251: sw += weight[i];
4252: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4253: } /* end of wave */
4254: } /* end of individual */
4255: } else if(mle==3){ /* exponential inter-extrapolation */
4256: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4257: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4258: for(mi=1; mi<= wav[i]-1; mi++){
4259: for (ii=1;ii<=nlstate+ndeath;ii++)
4260: for (j=1;j<=nlstate+ndeath;j++){
4261: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4262: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4263: }
4264: for(d=0; d<dh[mi][i]; d++){
4265: newm=savm;
4266: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4267: cov[2]=agexact;
4268: if(nagesqr==1)
4269: cov[3]= agexact*agexact;
4270: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4271: if(!FixedV[Tvar[Tage[kk]]])
4272: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4273: else
1.341 brouard 4274: 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 4275: }
4276: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4277: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4278: savm=oldm;
4279: oldm=newm;
4280: } /* end mult */
4281:
4282: s1=s[mw[mi][i]][i];
4283: s2=s[mw[mi+1][i]][i];
4284: bbh=(double)bh[mi][i]/(double)stepm;
4285: 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 */
4286: ipmx +=1;
4287: sw += weight[i];
4288: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4289: } /* end of wave */
4290: } /* end of individual */
4291: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4292: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4293: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4294: for(mi=1; mi<= wav[i]-1; mi++){
4295: for (ii=1;ii<=nlstate+ndeath;ii++)
4296: for (j=1;j<=nlstate+ndeath;j++){
4297: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4298: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4299: }
4300: for(d=0; d<dh[mi][i]; d++){
4301: newm=savm;
4302: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4303: cov[2]=agexact;
4304: if(nagesqr==1)
4305: cov[3]= agexact*agexact;
4306: for (kk=1; kk<=cptcovage;kk++) {
4307: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4308: }
1.126 brouard 4309:
1.226 brouard 4310: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4311: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4312: savm=oldm;
4313: oldm=newm;
4314: } /* end mult */
4315:
4316: s1=s[mw[mi][i]][i];
4317: s2=s[mw[mi+1][i]][i];
4318: if( s2 > nlstate){
4319: lli=log(out[s1][s2] - savm[s1][s2]);
4320: } else if ( s2==-1 ) { /* alive */
4321: for (j=1,survp=0. ; j<=nlstate; j++)
4322: survp += out[s1][j];
4323: lli= log(survp);
4324: }else{
4325: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4326: }
4327: ipmx +=1;
4328: sw += weight[i];
4329: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4330: /* 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 4331: } /* end of wave */
4332: } /* end of individual */
4333: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4334: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4335: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4336: for(mi=1; mi<= wav[i]-1; mi++){
4337: for (ii=1;ii<=nlstate+ndeath;ii++)
4338: for (j=1;j<=nlstate+ndeath;j++){
4339: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4340: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4341: }
4342: for(d=0; d<dh[mi][i]; d++){
4343: newm=savm;
4344: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4345: cov[2]=agexact;
4346: if(nagesqr==1)
4347: cov[3]= agexact*agexact;
4348: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4349: if(!FixedV[Tvar[Tage[kk]]])
4350: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4351: else
1.341 brouard 4352: 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 4353: }
1.126 brouard 4354:
1.226 brouard 4355: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4356: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4357: savm=oldm;
4358: oldm=newm;
4359: } /* end mult */
4360:
4361: s1=s[mw[mi][i]][i];
4362: s2=s[mw[mi+1][i]][i];
4363: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4364: ipmx +=1;
4365: sw += weight[i];
4366: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4367: /*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]);*/
4368: } /* end of wave */
4369: } /* end of individual */
4370: } /* End of if */
4371: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4372: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4373: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4374: return -l;
1.126 brouard 4375: }
4376:
4377: /*************** log-likelihood *************/
4378: double funcone( double *x)
4379: {
1.228 brouard 4380: /* Same as func but slower because of a lot of printf and if */
1.349 brouard 4381: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4382: int ioffset=0;
1.339 brouard 4383: int ipos=0,iposold=0,ncovv=0;
4384:
1.340 brouard 4385: double cotvarv, cotvarvold;
1.131 brouard 4386: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4387: double **out;
4388: double lli; /* Individual log likelihood */
4389: double llt;
4390: int s1, s2;
1.228 brouard 4391: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4392:
1.126 brouard 4393: double bbh, survp;
1.187 brouard 4394: double agexact;
1.214 brouard 4395: double agebegin, ageend;
1.126 brouard 4396: /*extern weight */
4397: /* We are differentiating ll according to initial status */
4398: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4399: /*for(i=1;i<imx;i++)
4400: printf(" %d\n",s[4][i]);
4401: */
4402: cov[1]=1.;
4403:
4404: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4405: ioffset=0;
4406: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4407: /* Computes the values of the ncovmodel covariates of the model
4408: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4409: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4410: to be observed in j being in i according to the model.
4411: */
1.243 brouard 4412: /* ioffset=2+nagesqr+cptcovage; */
4413: ioffset=2+nagesqr;
1.232 brouard 4414: /* Fixed */
1.224 brouard 4415: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4416: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 4417: 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 4418: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4419: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4420: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4421: 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 4422: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4423: /* cov[2+6]=covar[Tvar[6]][i]; */
4424: /* cov[2+6]=covar[2][i]; V2 */
4425: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4426: /* cov[2+7]=covar[Tvar[7]][i]; */
4427: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4428: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4429: /* cov[2+9]=covar[Tvar[9]][i]; */
4430: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4431: }
1.336 brouard 4432: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4433: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4434: has been calculated etc */
4435: /* For an individual i, wav[i] gives the number of effective waves */
4436: /* We compute the contribution to Likelihood of each effective transition
4437: mw[mi][i] is real wave of the mi th effectve wave */
4438: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4439: s2=s[mw[mi+1][i]][i];
1.341 brouard 4440: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4441: */
4442: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4443: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4444: /* 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?)*\/ */
4445: /* } */
1.231 brouard 4446: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4447: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4448: /* } */
1.225 brouard 4449:
1.233 brouard 4450:
4451: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4452: /* 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 */
4453: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4454: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4455: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4456: /* } */
4457:
4458: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4459: /* model V1+V3+age*V1+age*V3+V1*V3 */
4460: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4461: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4462: /* We need the position of the time varying or product in the model */
4463: /* 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 */
4464: /* TvarVV gives the variable name */
1.340 brouard 4465: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4466: * k= 1 2 3 4 5 6 7 8 9
4467: * varying 1 2 3 4 5
4468: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4469: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4470: * TvarVVind 2 3 7 7 8 8 9 9
4471: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4472: */
1.345 brouard 4473: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 4474: * 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 4475: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 4476: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4477: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
4478: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
4479: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4480: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4481: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4482: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4483: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4484: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4485: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4486: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4487: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4488: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4489: * 12 13 14 15 16
4490: * 17 18 19 20 21
4491: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
4492: * 2 3 4 6 7
4493: * 9 11 12 13 14
4494: * cptcovage=5+5 total of covariates with age
4495: * Tage[cptcovage] age*V2=12 13 14 15 16
4496: *1 17 18 19 20 21 gives the position in model of covariates associated with age
4497: *3 Tage[cptcovage] age*V3*V2=6
4498: *3 age*V2=12 13 14 15 16
4499: *3 age*V6*V3=18 19 20 21
4500: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4501: * 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
4502: * 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
4503: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4504: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4505: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
4506: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
4507: * 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
4508: * Tvar= {2, 3, 4, 6, 7,
4509: * 9, 10, 11, 12, 13, 14,
4510: * Tvar[12]=2, 3, 4, 6, 7,
4511: * Tvar[17]=9, 11, 12, 13, 14}
4512: * Typevar[1]@21 = {0, 0, 0, 0, 0,
4513: * 2, 2, 2, 2, 2, 2,
4514: * 3 3, 2, 2, 2, 2, 2,
4515: * 1, 1, 1, 1, 1,
4516: * 3, 3, 3, 3, 3}
4517: * 3 2, 3, 3, 3, 3}
4518: * 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
4519: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4520: * 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}
4521: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4522: * cptcovprod=11 (6+5)
4523: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
4524: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
4525: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
4526: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
4527: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4528: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4529: * cptcovdageprod=5 for gnuplot printing
4530: * cptcovprodvage=6
4531: * ncova=15 1 2 3 4 5
4532: * 6 7 8 9 10 11 12 13 14 15
4533: * TvarA 2 3 4 6 7
4534: * 6 2 6 7 7 3 6 4 7 4
4535: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4536: * ncovf 1 2 3
1.349 brouard 4537: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4538: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4539: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4540: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4541: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4542: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4543: * 3 1 2 3 4 5 6 7 8 9 10 11 12
4544: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
4545: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
4546: * 3 cptcovprodvage=6
4547: * 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
4548: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
4549: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
4550: * TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
4551: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
4552: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4553: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
4554: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
4555: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
4556: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
4557: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
4558: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4559: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 4560: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
4561: * 2, 3, 4, 6, 7,
4562: * 6, 8, 9, 10, 11}
1.345 brouard 4563: * TvarFind[itv] 0 0 0
4564: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
4565: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4566: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4567: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 4568: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4569: */
4570:
1.349 brouard 4571: 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 */
4572: 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 4573: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4574: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4575: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4576: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.340 brouard 4577: }else{ /* fixed covariate */
1.345 brouard 4578: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
1.349 brouard 4579: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.340 brouard 4580: }
1.339 brouard 4581: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4582: cotvarvold=cotvarv;
4583: }else{ /* A second product */
4584: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4585: }
4586: iposold=ipos;
1.340 brouard 4587: cov[ioffset+ipos]=cotvarv;
1.339 brouard 4588: /* For products */
4589: }
4590: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4591: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4592: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4593: /* /\* 1 2 3 4 5 *\/ */
4594: /* /\*itv 1 *\/ */
4595: /* /\* TvarVInd[1]= 2 *\/ */
4596: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4597: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4598: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4599: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4600: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4601: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4602: /* /\* 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]); *\/ */
4603: /* } */
1.232 brouard 4604: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4605: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4606: /* /\* 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]); *\/ */
4607: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4608: /* } */
1.126 brouard 4609: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4610: for (j=1;j<=nlstate+ndeath;j++){
4611: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4612: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4613: }
1.214 brouard 4614:
4615: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4616: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4617: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4618: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4619: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4620: and mw[mi+1][i]. dh depends on stepm.*/
4621: newm=savm;
1.247 brouard 4622: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4623: cov[2]=agexact;
4624: if(nagesqr==1)
4625: cov[3]= agexact*agexact;
1.349 brouard 4626: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4627: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4628: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4629: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4630: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4631: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4632: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4633: }else{ /* fixed covariate */
4634: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4635: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4636: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4637: }
4638: if(ipos!=iposold){ /* Not a product or first of a product */
4639: cotvarvold=cotvarv;
4640: }else{ /* A second product */
4641: /* printf("DEBUG * \n"); */
4642: cotvarv=cotvarv*cotvarvold;
4643: }
4644: iposold=ipos;
4645: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4646: cov[ioffset+ipos]=cotvarv*agexact;
4647: /* For products */
1.242 brouard 4648: }
1.349 brouard 4649:
1.242 brouard 4650: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4651: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4652: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4653: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4654: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4655: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4656: savm=oldm;
4657: oldm=newm;
1.126 brouard 4658: } /* end mult */
1.336 brouard 4659: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4660: /* But now since version 0.9 we anticipate for bias at large stepm.
4661: * If stepm is larger than one month (smallest stepm) and if the exact delay
4662: * (in months) between two waves is not a multiple of stepm, we rounded to
4663: * the nearest (and in case of equal distance, to the lowest) interval but now
4664: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4665: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4666: * probability in order to take into account the bias as a fraction of the way
4667: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4668: * -stepm/2 to stepm/2 .
4669: * For stepm=1 the results are the same as for previous versions of Imach.
4670: * For stepm > 1 the results are less biased than in previous versions.
4671: */
1.126 brouard 4672: s1=s[mw[mi][i]][i];
4673: s2=s[mw[mi+1][i]][i];
1.217 brouard 4674: /* if(s2==-1){ */
1.268 brouard 4675: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4676: /* /\* exit(1); *\/ */
4677: /* } */
1.126 brouard 4678: bbh=(double)bh[mi][i]/(double)stepm;
4679: /* bias is positive if real duration
4680: * is higher than the multiple of stepm and negative otherwise.
4681: */
4682: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4683: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4684: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4685: for (j=1,survp=0. ; j<=nlstate; j++)
4686: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4687: lli= log(survp);
1.126 brouard 4688: }else if (mle==1){
1.242 brouard 4689: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4690: } else if(mle==2){
1.242 brouard 4691: 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 4692: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4693: 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 4694: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4695: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4696: } else{ /* mle=0 back to 1 */
1.242 brouard 4697: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4698: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4699: } /* End of if */
4700: ipmx +=1;
4701: sw += weight[i];
4702: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4703: /* Printing covariates values for each contribution for checking */
1.343 brouard 4704: /* 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 4705: if(globpr){
1.246 brouard 4706: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4707: %11.6f %11.6f %11.6f ", \
1.242 brouard 4708: 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 4709: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4710: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4711: /* %11.6f %11.6f %11.6f ", \ */
4712: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4713: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4714: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4715: llt +=ll[k]*gipmx/gsw;
4716: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4717: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4718: }
1.343 brouard 4719: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4720: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4721: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4722: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4723: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4724: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4725: }
4726: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4727: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4728: if(ipos!=iposold){ /* Not a product or first of a product */
4729: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4730: /* printf(" %g",cov[ioffset+ipos]); */
4731: }else{
4732: fprintf(ficresilk,"*");
4733: /* printf("*"); */
1.342 brouard 4734: }
1.343 brouard 4735: iposold=ipos;
4736: }
1.349 brouard 4737: /* for (kk=1; kk<=cptcovage;kk++) { */
4738: /* if(!FixedV[Tvar[Tage[kk]]]){ */
4739: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
4740: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
4741: /* }else{ */
4742: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4743: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
4744: /* } */
4745: /* } */
4746: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4747: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4748: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4749: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4750: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4751: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4752: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4753: }else{ /* fixed covariate */
4754: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4755: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4756: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4757: }
4758: if(ipos!=iposold){ /* Not a product or first of a product */
4759: cotvarvold=cotvarv;
4760: }else{ /* A second product */
4761: /* printf("DEBUG * \n"); */
4762: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4763: }
1.349 brouard 4764: cotvarv=cotvarv*agexact;
4765: fprintf(ficresilk," %g*age",cotvarv);
4766: iposold=ipos;
4767: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4768: cov[ioffset+ipos]=cotvarv;
4769: /* For products */
1.343 brouard 4770: }
4771: /* printf("\n"); */
1.342 brouard 4772: /* } /\* End debugILK *\/ */
4773: fprintf(ficresilk,"\n");
4774: } /* End if globpr */
1.335 brouard 4775: } /* end of wave */
4776: } /* end of individual */
4777: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4778: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4779: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4780: if(globpr==0){ /* First time we count the contributions and weights */
4781: gipmx=ipmx;
4782: gsw=sw;
4783: }
1.343 brouard 4784: return -l;
1.126 brouard 4785: }
4786:
4787:
4788: /*************** function likelione ***********/
1.292 brouard 4789: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4790: {
4791: /* This routine should help understanding what is done with
4792: the selection of individuals/waves and
4793: to check the exact contribution to the likelihood.
4794: Plotting could be done.
1.342 brouard 4795: */
4796: void pstamp(FILE *ficres);
1.343 brouard 4797: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4798:
4799: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4800: strcpy(fileresilk,"ILK_");
1.202 brouard 4801: strcat(fileresilk,fileresu);
1.126 brouard 4802: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4803: printf("Problem with resultfile: %s\n", fileresilk);
4804: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4805: }
1.342 brouard 4806: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4807: 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");
4808: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4809: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4810: for(k=1; k<=nlstate; k++)
4811: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4812: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4813:
4814: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4815: for(kf=1;kf <= ncovf; kf++){
4816: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4817: /* printf("V%d",Tvar[TvarFind[kf]]); */
4818: }
4819: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4820: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4821: if(ipos!=iposold){ /* Not a product or first of a product */
4822: /* printf(" %d",ipos); */
4823: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4824: }else{
4825: /* printf("*"); */
4826: fprintf(ficresilk,"*");
1.343 brouard 4827: }
1.342 brouard 4828: iposold=ipos;
4829: }
4830: for (kk=1; kk<=cptcovage;kk++) {
4831: if(!FixedV[Tvar[Tage[kk]]]){
4832: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4833: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4834: }else{
4835: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4836: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4837: }
4838: }
4839: /* } /\* End if debugILK *\/ */
4840: /* printf("\n"); */
4841: fprintf(ficresilk,"\n");
4842: } /* End glogpri */
1.126 brouard 4843:
1.292 brouard 4844: *fretone=(*func)(p);
1.126 brouard 4845: if(*globpri !=0){
4846: fclose(ficresilk);
1.205 brouard 4847: if (mle ==0)
4848: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4849: else if(mle >=1)
4850: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4851: 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 4852: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4853:
1.207 brouard 4854: 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 4855: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4856: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4857: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4858:
4859: for (k=1; k<= nlstate ; k++) {
4860: 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 \
4861: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4862: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 4863: kvar=Tvar[TvarFind[kf]]; /* variable */
4864: 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]]);
4865: 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);
4866: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 4867: }
4868: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4869: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4870: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4871: /* 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]); */
4872: if(ipos!=iposold){ /* Not a product or first of a product */
4873: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4874: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4875: 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) */
4876: 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> \
4877: <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);
4878: } /* End only for dummies time varying (single?) */
4879: }else{ /* Useless product */
4880: /* printf("*"); */
4881: /* fprintf(ficresilk,"*"); */
4882: }
4883: iposold=ipos;
4884: } /* For each time varying covariate */
4885: } /* End loop on states */
4886:
4887: /* if(debugILK){ */
4888: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4889: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4890: /* for (k=1; k<= nlstate ; k++) { */
4891: /* 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> \ */
4892: /* <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]]); */
4893: /* } */
4894: /* } */
4895: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4896: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4897: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4898: /* /\* 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]); *\/ */
4899: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4900: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4901: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4902: /* 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) *\/ */
4903: /* for (k=1; k<= nlstate ; k++) { */
4904: /* 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> \ */
4905: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4906: /* } /\* End state *\/ */
4907: /* } /\* End only for dummies time varying (single?) *\/ */
4908: /* }else{ /\* Useless product *\/ */
4909: /* /\* printf("*"); *\/ */
4910: /* /\* fprintf(ficresilk,"*"); *\/ */
4911: /* } */
4912: /* iposold=ipos; */
4913: /* } /\* For each time varying covariate *\/ */
4914: /* }/\* End debugILK *\/ */
1.207 brouard 4915: fflush(fichtm);
1.343 brouard 4916: }/* End globpri */
1.126 brouard 4917: return;
4918: }
4919:
4920:
4921: /*********** Maximum Likelihood Estimation ***************/
4922:
4923: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4924: {
1.319 brouard 4925: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4926: double **xi;
4927: double fret;
4928: double fretone; /* Only one call to likelihood */
4929: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4930:
4931: #ifdef NLOPT
4932: int creturn;
4933: nlopt_opt opt;
4934: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4935: double *lb;
4936: double minf; /* the minimum objective value, upon return */
4937: double * p1; /* Shifted parameters from 0 instead of 1 */
4938: myfunc_data dinst, *d = &dinst;
4939: #endif
4940:
4941:
1.126 brouard 4942: xi=matrix(1,npar,1,npar);
4943: for (i=1;i<=npar;i++)
4944: for (j=1;j<=npar;j++)
4945: xi[i][j]=(i==j ? 1.0 : 0.0);
4946: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4947: strcpy(filerespow,"POW_");
1.126 brouard 4948: strcat(filerespow,fileres);
4949: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4950: printf("Problem with resultfile: %s\n", filerespow);
4951: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4952: }
4953: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4954: for (i=1;i<=nlstate;i++)
4955: for(j=1;j<=nlstate+ndeath;j++)
4956: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4957: fprintf(ficrespow,"\n");
1.162 brouard 4958: #ifdef POWELL
1.319 brouard 4959: #ifdef LINMINORIGINAL
4960: #else /* LINMINORIGINAL */
4961:
4962: flatdir=ivector(1,npar);
4963: for (j=1;j<=npar;j++) flatdir[j]=0;
4964: #endif /*LINMINORIGINAL */
4965:
4966: #ifdef FLATSUP
4967: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4968: /* reorganizing p by suppressing flat directions */
4969: for(i=1, jk=1; i <=nlstate; i++){
4970: for(k=1; k <=(nlstate+ndeath); k++){
4971: if (k != i) {
4972: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4973: if(flatdir[jk]==1){
4974: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4975: }
4976: for(j=1; j <=ncovmodel; j++){
4977: printf("%12.7f ",p[jk]);
4978: jk++;
4979: }
4980: printf("\n");
4981: }
4982: }
4983: }
4984: /* skipping */
4985: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4986: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4987: for(k=1; k <=(nlstate+ndeath); k++){
4988: if (k != i) {
4989: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4990: if(flatdir[jk]==1){
4991: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4992: for(j=1; j <=ncovmodel; jk++,j++){
4993: printf(" p[%d]=%12.7f",jk, p[jk]);
4994: /*q[jjk]=p[jk];*/
4995: }
4996: }else{
4997: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4998: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4999: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
5000: /*q[jjk]=p[jk];*/
5001: }
5002: }
5003: printf("\n");
5004: }
5005: fflush(stdout);
5006: }
5007: }
5008: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5009: #else /* FLATSUP */
1.126 brouard 5010: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 5011: #endif /* FLATSUP */
5012:
5013: #ifdef LINMINORIGINAL
5014: #else
5015: free_ivector(flatdir,1,npar);
5016: #endif /* LINMINORIGINAL*/
5017: #endif /* POWELL */
1.126 brouard 5018:
1.162 brouard 5019: #ifdef NLOPT
5020: #ifdef NEWUOA
5021: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
5022: #else
5023: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
5024: #endif
5025: lb=vector(0,npar-1);
5026: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
5027: nlopt_set_lower_bounds(opt, lb);
5028: nlopt_set_initial_step1(opt, 0.1);
5029:
5030: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5031: d->function = func;
5032: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5033: nlopt_set_min_objective(opt, myfunc, d);
5034: nlopt_set_xtol_rel(opt, ftol);
5035: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5036: printf("nlopt failed! %d\n",creturn);
5037: }
5038: else {
5039: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5040: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5041: iter=1; /* not equal */
5042: }
5043: nlopt_destroy(opt);
5044: #endif
1.319 brouard 5045: #ifdef FLATSUP
5046: /* npared = npar -flatd/ncovmodel; */
5047: /* xired= matrix(1,npared,1,npared); */
5048: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5049: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5050: /* free_matrix(xire,1,npared,1,npared); */
5051: #else /* FLATSUP */
5052: #endif /* FLATSUP */
1.126 brouard 5053: free_matrix(xi,1,npar,1,npar);
5054: fclose(ficrespow);
1.203 brouard 5055: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5056: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5057: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5058:
5059: }
5060:
5061: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5062: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5063: {
5064: double **a,**y,*x,pd;
1.203 brouard 5065: /* double **hess; */
1.164 brouard 5066: int i, j;
1.126 brouard 5067: int *indx;
5068:
5069: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5070: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5071: void lubksb(double **a, int npar, int *indx, double b[]) ;
5072: void ludcmp(double **a, int npar, int *indx, double *d) ;
5073: double gompertz(double p[]);
1.203 brouard 5074: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5075:
5076: printf("\nCalculation of the hessian matrix. Wait...\n");
5077: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5078: for (i=1;i<=npar;i++){
1.203 brouard 5079: printf("%d-",i);fflush(stdout);
5080: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5081:
5082: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5083:
5084: /* printf(" %f ",p[i]);
5085: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5086: }
5087:
5088: for (i=1;i<=npar;i++) {
5089: for (j=1;j<=npar;j++) {
5090: if (j>i) {
1.203 brouard 5091: printf(".%d-%d",i,j);fflush(stdout);
5092: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5093: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5094:
5095: hess[j][i]=hess[i][j];
5096: /*printf(" %lf ",hess[i][j]);*/
5097: }
5098: }
5099: }
5100: printf("\n");
5101: fprintf(ficlog,"\n");
5102:
5103: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5104: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5105:
5106: a=matrix(1,npar,1,npar);
5107: y=matrix(1,npar,1,npar);
5108: x=vector(1,npar);
5109: indx=ivector(1,npar);
5110: for (i=1;i<=npar;i++)
5111: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5112: ludcmp(a,npar,indx,&pd);
5113:
5114: for (j=1;j<=npar;j++) {
5115: for (i=1;i<=npar;i++) x[i]=0;
5116: x[j]=1;
5117: lubksb(a,npar,indx,x);
5118: for (i=1;i<=npar;i++){
5119: matcov[i][j]=x[i];
5120: }
5121: }
5122:
5123: printf("\n#Hessian matrix#\n");
5124: fprintf(ficlog,"\n#Hessian matrix#\n");
5125: for (i=1;i<=npar;i++) {
5126: for (j=1;j<=npar;j++) {
1.203 brouard 5127: printf("%.6e ",hess[i][j]);
5128: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5129: }
5130: printf("\n");
5131: fprintf(ficlog,"\n");
5132: }
5133:
1.203 brouard 5134: /* printf("\n#Covariance matrix#\n"); */
5135: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5136: /* for (i=1;i<=npar;i++) { */
5137: /* for (j=1;j<=npar;j++) { */
5138: /* printf("%.6e ",matcov[i][j]); */
5139: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5140: /* } */
5141: /* printf("\n"); */
5142: /* fprintf(ficlog,"\n"); */
5143: /* } */
5144:
1.126 brouard 5145: /* Recompute Inverse */
1.203 brouard 5146: /* for (i=1;i<=npar;i++) */
5147: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5148: /* ludcmp(a,npar,indx,&pd); */
5149:
5150: /* printf("\n#Hessian matrix recomputed#\n"); */
5151:
5152: /* for (j=1;j<=npar;j++) { */
5153: /* for (i=1;i<=npar;i++) x[i]=0; */
5154: /* x[j]=1; */
5155: /* lubksb(a,npar,indx,x); */
5156: /* for (i=1;i<=npar;i++){ */
5157: /* y[i][j]=x[i]; */
5158: /* printf("%.3e ",y[i][j]); */
5159: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5160: /* } */
5161: /* printf("\n"); */
5162: /* fprintf(ficlog,"\n"); */
5163: /* } */
5164:
5165: /* Verifying the inverse matrix */
5166: #ifdef DEBUGHESS
5167: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5168:
1.203 brouard 5169: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5170: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5171:
5172: for (j=1;j<=npar;j++) {
5173: for (i=1;i<=npar;i++){
1.203 brouard 5174: printf("%.2f ",y[i][j]);
5175: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5176: }
5177: printf("\n");
5178: fprintf(ficlog,"\n");
5179: }
1.203 brouard 5180: #endif
1.126 brouard 5181:
5182: free_matrix(a,1,npar,1,npar);
5183: free_matrix(y,1,npar,1,npar);
5184: free_vector(x,1,npar);
5185: free_ivector(indx,1,npar);
1.203 brouard 5186: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5187:
5188:
5189: }
5190:
5191: /*************** hessian matrix ****************/
5192: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5193: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5194: int i;
5195: int l=1, lmax=20;
1.203 brouard 5196: double k1,k2, res, fx;
1.132 brouard 5197: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5198: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5199: int k=0,kmax=10;
5200: double l1;
5201:
5202: fx=func(x);
5203: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5204: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5205: l1=pow(10,l);
5206: delts=delt;
5207: for(k=1 ; k <kmax; k=k+1){
5208: delt = delta*(l1*k);
5209: p2[theta]=x[theta] +delt;
1.145 brouard 5210: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5211: p2[theta]=x[theta]-delt;
5212: k2=func(p2)-fx;
5213: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5214: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5215:
1.203 brouard 5216: #ifdef DEBUGHESSII
1.126 brouard 5217: 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);
5218: 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);
5219: #endif
5220: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5221: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5222: k=kmax;
5223: }
5224: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5225: k=kmax; l=lmax*10;
1.126 brouard 5226: }
5227: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5228: delts=delt;
5229: }
1.203 brouard 5230: } /* End loop k */
1.126 brouard 5231: }
5232: delti[theta]=delts;
5233: return res;
5234:
5235: }
5236:
1.203 brouard 5237: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5238: {
5239: int i;
1.164 brouard 5240: int l=1, lmax=20;
1.126 brouard 5241: double k1,k2,k3,k4,res,fx;
1.132 brouard 5242: double p2[MAXPARM+1];
1.203 brouard 5243: int k, kmax=1;
5244: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5245:
5246: int firstime=0;
1.203 brouard 5247:
1.126 brouard 5248: fx=func(x);
1.203 brouard 5249: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5250: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5251: p2[thetai]=x[thetai]+delti[thetai]*k;
5252: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5253: k1=func(p2)-fx;
5254:
1.203 brouard 5255: p2[thetai]=x[thetai]+delti[thetai]*k;
5256: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5257: k2=func(p2)-fx;
5258:
1.203 brouard 5259: p2[thetai]=x[thetai]-delti[thetai]*k;
5260: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5261: k3=func(p2)-fx;
5262:
1.203 brouard 5263: p2[thetai]=x[thetai]-delti[thetai]*k;
5264: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5265: k4=func(p2)-fx;
1.203 brouard 5266: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5267: if(k1*k2*k3*k4 <0.){
1.208 brouard 5268: firstime=1;
1.203 brouard 5269: kmax=kmax+10;
1.208 brouard 5270: }
5271: if(kmax >=10 || firstime ==1){
1.246 brouard 5272: 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);
5273: 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 5274: 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);
5275: 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);
5276: }
5277: #ifdef DEBUGHESSIJ
5278: v1=hess[thetai][thetai];
5279: v2=hess[thetaj][thetaj];
5280: cv12=res;
5281: /* Computing eigen value of Hessian matrix */
5282: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5283: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5284: if ((lc2 <0) || (lc1 <0) ){
5285: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5286: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5287: 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);
5288: 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);
5289: }
1.126 brouard 5290: #endif
5291: }
5292: return res;
5293: }
5294:
1.203 brouard 5295: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5296: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5297: /* { */
5298: /* int i; */
5299: /* int l=1, lmax=20; */
5300: /* double k1,k2,k3,k4,res,fx; */
5301: /* double p2[MAXPARM+1]; */
5302: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5303: /* int k=0,kmax=10; */
5304: /* double l1; */
5305:
5306: /* fx=func(x); */
5307: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5308: /* l1=pow(10,l); */
5309: /* delts=delt; */
5310: /* for(k=1 ; k <kmax; k=k+1){ */
5311: /* delt = delti*(l1*k); */
5312: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5313: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5314: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5315: /* k1=func(p2)-fx; */
5316:
5317: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5318: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5319: /* k2=func(p2)-fx; */
5320:
5321: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5322: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5323: /* k3=func(p2)-fx; */
5324:
5325: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5326: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5327: /* k4=func(p2)-fx; */
5328: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5329: /* #ifdef DEBUGHESSIJ */
5330: /* 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); */
5331: /* 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); */
5332: /* #endif */
5333: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5334: /* k=kmax; */
5335: /* } */
5336: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5337: /* k=kmax; l=lmax*10; */
5338: /* } */
5339: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5340: /* delts=delt; */
5341: /* } */
5342: /* } /\* End loop k *\/ */
5343: /* } */
5344: /* delti[theta]=delts; */
5345: /* return res; */
5346: /* } */
5347:
5348:
1.126 brouard 5349: /************** Inverse of matrix **************/
5350: void ludcmp(double **a, int n, int *indx, double *d)
5351: {
5352: int i,imax,j,k;
5353: double big,dum,sum,temp;
5354: double *vv;
5355:
5356: vv=vector(1,n);
5357: *d=1.0;
5358: for (i=1;i<=n;i++) {
5359: big=0.0;
5360: for (j=1;j<=n;j++)
5361: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5362: if (big == 0.0){
5363: printf(" Singular Hessian matrix at row %d:\n",i);
5364: for (j=1;j<=n;j++) {
5365: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5366: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5367: }
5368: fflush(ficlog);
5369: fclose(ficlog);
5370: nrerror("Singular matrix in routine ludcmp");
5371: }
1.126 brouard 5372: vv[i]=1.0/big;
5373: }
5374: for (j=1;j<=n;j++) {
5375: for (i=1;i<j;i++) {
5376: sum=a[i][j];
5377: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5378: a[i][j]=sum;
5379: }
5380: big=0.0;
5381: for (i=j;i<=n;i++) {
5382: sum=a[i][j];
5383: for (k=1;k<j;k++)
5384: sum -= a[i][k]*a[k][j];
5385: a[i][j]=sum;
5386: if ( (dum=vv[i]*fabs(sum)) >= big) {
5387: big=dum;
5388: imax=i;
5389: }
5390: }
5391: if (j != imax) {
5392: for (k=1;k<=n;k++) {
5393: dum=a[imax][k];
5394: a[imax][k]=a[j][k];
5395: a[j][k]=dum;
5396: }
5397: *d = -(*d);
5398: vv[imax]=vv[j];
5399: }
5400: indx[j]=imax;
5401: if (a[j][j] == 0.0) a[j][j]=TINY;
5402: if (j != n) {
5403: dum=1.0/(a[j][j]);
5404: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5405: }
5406: }
5407: free_vector(vv,1,n); /* Doesn't work */
5408: ;
5409: }
5410:
5411: void lubksb(double **a, int n, int *indx, double b[])
5412: {
5413: int i,ii=0,ip,j;
5414: double sum;
5415:
5416: for (i=1;i<=n;i++) {
5417: ip=indx[i];
5418: sum=b[ip];
5419: b[ip]=b[i];
5420: if (ii)
5421: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5422: else if (sum) ii=i;
5423: b[i]=sum;
5424: }
5425: for (i=n;i>=1;i--) {
5426: sum=b[i];
5427: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5428: b[i]=sum/a[i][i];
5429: }
5430: }
5431:
5432: void pstamp(FILE *fichier)
5433: {
1.196 brouard 5434: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5435: }
5436:
1.297 brouard 5437: void date2dmy(double date,double *day, double *month, double *year){
5438: double yp=0., yp1=0., yp2=0.;
5439:
5440: yp1=modf(date,&yp);/* extracts integral of date in yp and
5441: fractional in yp1 */
5442: *year=yp;
5443: yp2=modf((yp1*12),&yp);
5444: *month=yp;
5445: yp1=modf((yp2*30.5),&yp);
5446: *day=yp;
5447: if(*day==0) *day=1;
5448: if(*month==0) *month=1;
5449: }
5450:
1.253 brouard 5451:
5452:
1.126 brouard 5453: /************ Frequencies ********************/
1.251 brouard 5454: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5455: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5456: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5457: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5458: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5459: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5460: int iind=0, iage=0;
5461: int mi; /* Effective wave */
5462: int first;
5463: double ***freq; /* Frequencies */
1.268 brouard 5464: 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 */
5465: 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 5466: double *meanq, *stdq, *idq;
1.226 brouard 5467: double **meanqt;
5468: double *pp, **prop, *posprop, *pospropt;
5469: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5470: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5471: double agebegin, ageend;
5472:
5473: pp=vector(1,nlstate);
1.251 brouard 5474: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5475: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5476: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5477: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5478: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5479: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5480: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5481: meanqt=matrix(1,lastpass,1,nqtveff);
5482: strcpy(fileresp,"P_");
5483: strcat(fileresp,fileresu);
5484: /*strcat(fileresphtm,fileresu);*/
5485: if((ficresp=fopen(fileresp,"w"))==NULL) {
5486: printf("Problem with prevalence resultfile: %s\n", fileresp);
5487: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5488: exit(0);
5489: }
1.240 brouard 5490:
1.226 brouard 5491: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5492: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5493: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5494: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5495: fflush(ficlog);
5496: exit(70);
5497: }
5498: else{
5499: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5500: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5501: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5502: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5503: }
1.319 brouard 5504: 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 5505:
1.226 brouard 5506: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5507: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5508: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5509: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5510: fflush(ficlog);
5511: exit(70);
1.240 brouard 5512: } else{
1.226 brouard 5513: 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 5514: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5515: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5516: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5517: }
1.319 brouard 5518: 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 5519:
1.253 brouard 5520: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5521: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5522: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5523: j1=0;
1.126 brouard 5524:
1.227 brouard 5525: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5526: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5527: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5528: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5529:
5530:
1.226 brouard 5531: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5532: reference=low_education V1=0,V2=0
5533: med_educ V1=1 V2=0,
5534: high_educ V1=0 V2=1
1.330 brouard 5535: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5536: */
1.249 brouard 5537: dateintsum=0;
5538: k2cpt=0;
5539:
1.253 brouard 5540: if(cptcoveff == 0 )
1.265 brouard 5541: nl=1; /* Constant and age model only */
1.253 brouard 5542: else
5543: nl=2;
1.265 brouard 5544:
5545: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5546: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5547: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5548: * freq[s1][s2][iage] =0.
5549: * Loop on iind
5550: * ++freq[s1][s2][iage] weighted
5551: * end iind
5552: * if covariate and j!0
5553: * headers Variable on one line
5554: * endif cov j!=0
5555: * header of frequency table by age
5556: * Loop on age
5557: * pp[s1]+=freq[s1][s2][iage] weighted
5558: * pos+=freq[s1][s2][iage] weighted
5559: * Loop on s1 initial state
5560: * fprintf(ficresp
5561: * end s1
5562: * end age
5563: * if j!=0 computes starting values
5564: * end compute starting values
5565: * end j1
5566: * end nl
5567: */
1.253 brouard 5568: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5569: if(nj==1)
5570: j=0; /* First pass for the constant */
1.265 brouard 5571: else{
1.335 brouard 5572: 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 5573: }
1.251 brouard 5574: first=1;
1.332 brouard 5575: 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 5576: posproptt=0.;
1.330 brouard 5577: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5578: scanf("%d", i);*/
5579: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5580: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5581: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5582: freq[i][s2][m]=0;
1.251 brouard 5583:
5584: for (i=1; i<=nlstate; i++) {
1.240 brouard 5585: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5586: prop[i][m]=0;
5587: posprop[i]=0;
5588: pospropt[i]=0;
5589: }
1.283 brouard 5590: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5591: idq[z1]=0.;
5592: meanq[z1]=0.;
5593: stdq[z1]=0.;
1.283 brouard 5594: }
5595: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5596: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5597: /* meanqt[m][z1]=0.; */
5598: /* } */
5599: /* } */
1.251 brouard 5600: /* dateintsum=0; */
5601: /* k2cpt=0; */
5602:
1.265 brouard 5603: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5604: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5605: bool=1;
5606: if(j !=0){
5607: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5608: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5609: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5610: /* if(Tvaraff[z1] ==-20){ */
5611: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5612: /* }else if(Tvaraff[z1] ==-10){ */
5613: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5614: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5615: /* 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); */
5616: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5617: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5618: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5619: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5620: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5621: /* 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", */
5622: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5623: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5624: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5625: } /* Onlyf fixed */
5626: } /* end z1 */
1.335 brouard 5627: } /* cptcoveff > 0 */
1.251 brouard 5628: } /* end any */
5629: }/* end j==0 */
1.265 brouard 5630: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5631: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5632: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5633: m=mw[mi][iind];
5634: if(j!=0){
5635: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5636: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5637: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5638: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5639: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5640: 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 5641: value is -1, we don't select. It differs from the
5642: constant and age model which counts them. */
5643: bool=0; /* not selected */
5644: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5645: /* i1=Tvaraff[z1]; */
5646: /* i2=TnsdVar[i1]; */
5647: /* i3=nbcode[i1][i2]; */
5648: /* i4=covar[i1][iind]; */
5649: /* if(i4 != i3){ */
5650: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5651: bool=0;
5652: }
5653: }
5654: }
5655: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5656: } /* end j==0 */
5657: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5658: if(bool==1){ /*Selected */
1.251 brouard 5659: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5660: and mw[mi+1][iind]. dh depends on stepm. */
5661: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5662: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5663: if(m >=firstpass && m <=lastpass){
5664: k2=anint[m][iind]+(mint[m][iind]/12.);
5665: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5666: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5667: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5668: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5669: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5670: if (m<lastpass) {
5671: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5672: /* 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]); */
5673: if(s[m][iind]==-1)
5674: 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.));
5675: 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 5676: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5677: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5678: idq[z1]=idq[z1]+weight[iind];
5679: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5680: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5681: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5682: }
1.284 brouard 5683: }
1.251 brouard 5684: /* if((int)agev[m][iind] == 55) */
5685: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5686: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5687: 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 5688: }
1.251 brouard 5689: } /* end if between passes */
5690: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5691: dateintsum=dateintsum+k2; /* on all covariates ?*/
5692: k2cpt++;
5693: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5694: }
1.251 brouard 5695: }else{
5696: bool=1;
5697: }/* end bool 2 */
5698: } /* end m */
1.284 brouard 5699: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5700: /* idq[z1]=idq[z1]+weight[iind]; */
5701: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5702: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5703: /* } */
1.251 brouard 5704: } /* end bool */
5705: } /* end iind = 1 to imx */
1.319 brouard 5706: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5707: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5708:
5709:
5710: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5711: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5712: pstamp(ficresp);
1.335 brouard 5713: if (cptcoveff>0 && j!=0){
1.265 brouard 5714: pstamp(ficresp);
1.251 brouard 5715: printf( "\n#********** Variable ");
5716: fprintf(ficresp, "\n#********** Variable ");
5717: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5718: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5719: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5720: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5721: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5722: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5723: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5724: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5725: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5726: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5727: }else{
1.330 brouard 5728: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5729: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5730: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5731: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5732: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5733: }
5734: }
5735: printf( "**********\n#");
5736: fprintf(ficresp, "**********\n#");
5737: fprintf(ficresphtm, "**********</h3>\n");
5738: fprintf(ficresphtmfr, "**********</h3>\n");
5739: fprintf(ficlog, "**********\n");
5740: }
1.284 brouard 5741: /*
5742: Printing means of quantitative variables if any
5743: */
5744: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5745: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5746: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5747: if(weightopt==1){
5748: printf(" Weighted mean and standard deviation of");
5749: fprintf(ficlog," Weighted mean and standard deviation of");
5750: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5751: }
1.311 brouard 5752: /* mu = \frac{w x}{\sum w}
5753: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5754: */
5755: 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]));
5756: 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]));
5757: 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 5758: }
5759: /* for (z1=1; z1<= nqtveff; z1++) { */
5760: /* for(m=1;m<=lastpass;m++){ */
5761: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5762: /* } */
5763: /* } */
1.283 brouard 5764:
1.251 brouard 5765: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5766: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5767: fprintf(ficresp, " Age");
1.335 brouard 5768: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5769: 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]]);
5770: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5771: }
1.251 brouard 5772: for(i=1; i<=nlstate;i++) {
1.335 brouard 5773: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5774: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5775: }
1.335 brouard 5776: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5777: fprintf(ficresphtm, "\n");
5778:
5779: /* Header of frequency table by age */
5780: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5781: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5782: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5783: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5784: if(s2!=0 && m!=0)
5785: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5786: }
1.226 brouard 5787: }
1.251 brouard 5788: fprintf(ficresphtmfr, "\n");
5789:
5790: /* For each age */
5791: for(iage=iagemin; iage <= iagemax+3; iage++){
5792: fprintf(ficresphtm,"<tr>");
5793: if(iage==iagemax+1){
5794: fprintf(ficlog,"1");
5795: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5796: }else if(iage==iagemax+2){
5797: fprintf(ficlog,"0");
5798: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5799: }else if(iage==iagemax+3){
5800: fprintf(ficlog,"Total");
5801: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5802: }else{
1.240 brouard 5803: if(first==1){
1.251 brouard 5804: first=0;
5805: printf("See log file for details...\n");
5806: }
5807: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5808: fprintf(ficlog,"Age %d", iage);
5809: }
1.265 brouard 5810: for(s1=1; s1 <=nlstate ; s1++){
5811: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5812: pp[s1] += freq[s1][m][iage];
1.251 brouard 5813: }
1.265 brouard 5814: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5815: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5816: pos += freq[s1][m][iage];
5817: if(pp[s1]>=1.e-10){
1.251 brouard 5818: if(first==1){
1.265 brouard 5819: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5820: }
1.265 brouard 5821: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5822: }else{
5823: if(first==1)
1.265 brouard 5824: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5825: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5826: }
5827: }
5828:
1.265 brouard 5829: for(s1=1; s1 <=nlstate ; s1++){
5830: /* posprop[s1]=0; */
5831: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5832: pp[s1] += freq[s1][m][iage];
5833: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5834:
5835: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5836: pos += pp[s1]; /* pos is the total number of transitions until this age */
5837: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5838: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5839: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5840: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5841: }
5842:
5843: /* Writing ficresp */
1.335 brouard 5844: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5845: if( iage <= iagemax){
5846: fprintf(ficresp," %d",iage);
5847: }
5848: }else if( nj==2){
5849: if( iage <= iagemax){
5850: fprintf(ficresp," %d",iage);
1.335 brouard 5851: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5852: }
1.240 brouard 5853: }
1.265 brouard 5854: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5855: if(pos>=1.e-5){
1.251 brouard 5856: if(first==1)
1.265 brouard 5857: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5858: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5859: }else{
5860: if(first==1)
1.265 brouard 5861: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5862: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5863: }
5864: if( iage <= iagemax){
5865: if(pos>=1.e-5){
1.335 brouard 5866: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5867: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5868: }else if( nj==2){
5869: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5870: }
5871: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5872: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5873: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5874: } else{
1.335 brouard 5875: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5876: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5877: }
1.240 brouard 5878: }
1.265 brouard 5879: pospropt[s1] +=posprop[s1];
5880: } /* end loop s1 */
1.251 brouard 5881: /* pospropt=0.; */
1.265 brouard 5882: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5883: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5884: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5885: if(first==1){
1.265 brouard 5886: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5887: }
1.265 brouard 5888: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5889: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5890: }
1.265 brouard 5891: if(s1!=0 && m!=0)
5892: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5893: }
1.265 brouard 5894: } /* end loop s1 */
1.251 brouard 5895: posproptt=0.;
1.265 brouard 5896: for(s1=1; s1 <=nlstate; s1++){
5897: posproptt += pospropt[s1];
1.251 brouard 5898: }
5899: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5900: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5901: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5902: if(iage <= iagemax)
5903: fprintf(ficresp,"\n");
1.240 brouard 5904: }
1.251 brouard 5905: if(first==1)
5906: printf("Others in log...\n");
5907: fprintf(ficlog,"\n");
5908: } /* end loop age iage */
1.265 brouard 5909:
1.251 brouard 5910: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5911: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5912: if(posproptt < 1.e-5){
1.265 brouard 5913: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5914: }else{
1.265 brouard 5915: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5916: }
1.226 brouard 5917: }
1.251 brouard 5918: fprintf(ficresphtm,"</tr>\n");
5919: fprintf(ficresphtm,"</table>\n");
5920: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5921: if(posproptt < 1.e-5){
1.251 brouard 5922: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5923: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5924: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5925: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5926: invalidvarcomb[j1]=1;
1.226 brouard 5927: }else{
1.338 brouard 5928: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5929: invalidvarcomb[j1]=0;
1.226 brouard 5930: }
1.251 brouard 5931: fprintf(ficresphtmfr,"</table>\n");
5932: fprintf(ficlog,"\n");
5933: if(j!=0){
5934: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5935: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5936: for(k=1; k <=(nlstate+ndeath); k++){
5937: if (k != i) {
1.265 brouard 5938: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5939: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5940: if(j1==1){ /* All dummy covariates to zero */
5941: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5942: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5943: printf("%d%d ",i,k);
5944: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5945: 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]));
5946: 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]));
5947: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5948: }
1.253 brouard 5949: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5950: for(iage=iagemin; iage <= iagemax+3; iage++){
5951: x[iage]= (double)iage;
5952: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5953: /* 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 5954: }
1.268 brouard 5955: /* Some are not finite, but linreg will ignore these ages */
5956: no=0;
1.253 brouard 5957: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5958: pstart[s1]=b;
5959: pstart[s1-1]=a;
1.252 brouard 5960: }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 */
5961: 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]);
5962: 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 5963: 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 5964: printf("%d%d ",i,k);
5965: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5966: 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 5967: }else{ /* Other cases, like quantitative fixed or varying covariates */
5968: ;
5969: }
5970: /* printf("%12.7f )", param[i][jj][k]); */
5971: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5972: s1++;
1.251 brouard 5973: } /* end jj */
5974: } /* end k!= i */
5975: } /* end k */
1.265 brouard 5976: } /* end i, s1 */
1.251 brouard 5977: } /* end j !=0 */
5978: } /* end selected combination of covariate j1 */
5979: if(j==0){ /* We can estimate starting values from the occurences in each case */
5980: printf("#Freqsummary: Starting values for the constants:\n");
5981: fprintf(ficlog,"\n");
1.265 brouard 5982: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5983: for(k=1; k <=(nlstate+ndeath); k++){
5984: if (k != i) {
5985: printf("%d%d ",i,k);
5986: fprintf(ficlog,"%d%d ",i,k);
5987: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5988: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5989: if(jj==1){ /* Age has to be done */
1.265 brouard 5990: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5991: 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]));
5992: 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 5993: }
5994: /* printf("%12.7f )", param[i][jj][k]); */
5995: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5996: s1++;
1.250 brouard 5997: }
1.251 brouard 5998: printf("\n");
5999: fprintf(ficlog,"\n");
1.250 brouard 6000: }
6001: }
1.284 brouard 6002: } /* end of state i */
1.251 brouard 6003: printf("#Freqsummary\n");
6004: fprintf(ficlog,"\n");
1.265 brouard 6005: for(s1=-1; s1 <=nlstate+ndeath; s1++){
6006: for(s2=-1; s2 <=nlstate+ndeath; s2++){
6007: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
6008: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6009: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6010: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
6011: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
6012: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 6013: /* } */
6014: }
1.265 brouard 6015: } /* end loop s1 */
1.251 brouard 6016:
6017: printf("\n");
6018: fprintf(ficlog,"\n");
6019: } /* end j=0 */
1.249 brouard 6020: } /* end j */
1.252 brouard 6021:
1.253 brouard 6022: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 6023: for(i=1, jk=1; i <=nlstate; i++){
6024: for(j=1; j <=nlstate+ndeath; j++){
6025: if(j!=i){
6026: /*ca[0]= k+'a'-1;ca[1]='\0';*/
6027: printf("%1d%1d",i,j);
6028: fprintf(ficparo,"%1d%1d",i,j);
6029: for(k=1; k<=ncovmodel;k++){
6030: /* printf(" %lf",param[i][j][k]); */
6031: /* fprintf(ficparo," %lf",param[i][j][k]); */
6032: p[jk]=pstart[jk];
6033: printf(" %f ",pstart[jk]);
6034: fprintf(ficparo," %f ",pstart[jk]);
6035: jk++;
6036: }
6037: printf("\n");
6038: fprintf(ficparo,"\n");
6039: }
6040: }
6041: }
6042: } /* end mle=-2 */
1.226 brouard 6043: dateintmean=dateintsum/k2cpt;
1.296 brouard 6044: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6045:
1.226 brouard 6046: fclose(ficresp);
6047: fclose(ficresphtm);
6048: fclose(ficresphtmfr);
1.283 brouard 6049: free_vector(idq,1,nqfveff);
1.226 brouard 6050: free_vector(meanq,1,nqfveff);
1.284 brouard 6051: free_vector(stdq,1,nqfveff);
1.226 brouard 6052: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6053: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6054: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6055: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6056: free_vector(pospropt,1,nlstate);
6057: free_vector(posprop,1,nlstate);
1.251 brouard 6058: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6059: free_vector(pp,1,nlstate);
6060: /* End of freqsummary */
6061: }
1.126 brouard 6062:
1.268 brouard 6063: /* Simple linear regression */
6064: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6065:
6066: /* y=a+bx regression */
6067: double sumx = 0.0; /* sum of x */
6068: double sumx2 = 0.0; /* sum of x**2 */
6069: double sumxy = 0.0; /* sum of x * y */
6070: double sumy = 0.0; /* sum of y */
6071: double sumy2 = 0.0; /* sum of y**2 */
6072: double sume2 = 0.0; /* sum of square or residuals */
6073: double yhat;
6074:
6075: double denom=0;
6076: int i;
6077: int ne=*no;
6078:
6079: for ( i=ifi, ne=0;i<=ila;i++) {
6080: if(!isfinite(x[i]) || !isfinite(y[i])){
6081: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6082: continue;
6083: }
6084: ne=ne+1;
6085: sumx += x[i];
6086: sumx2 += x[i]*x[i];
6087: sumxy += x[i] * y[i];
6088: sumy += y[i];
6089: sumy2 += y[i]*y[i];
6090: denom = (ne * sumx2 - sumx*sumx);
6091: /* 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); */
6092: }
6093:
6094: denom = (ne * sumx2 - sumx*sumx);
6095: if (denom == 0) {
6096: // vertical, slope m is infinity
6097: *b = INFINITY;
6098: *a = 0;
6099: if (r) *r = 0;
6100: return 1;
6101: }
6102:
6103: *b = (ne * sumxy - sumx * sumy) / denom;
6104: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6105: if (r!=NULL) {
6106: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6107: sqrt((sumx2 - sumx*sumx/ne) *
6108: (sumy2 - sumy*sumy/ne));
6109: }
6110: *no=ne;
6111: for ( i=ifi, ne=0;i<=ila;i++) {
6112: if(!isfinite(x[i]) || !isfinite(y[i])){
6113: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6114: continue;
6115: }
6116: ne=ne+1;
6117: yhat = y[i] - *a -*b* x[i];
6118: sume2 += yhat * yhat ;
6119:
6120: denom = (ne * sumx2 - sumx*sumx);
6121: /* 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); */
6122: }
6123: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6124: *sa= *sb * sqrt(sumx2/ne);
6125:
6126: return 0;
6127: }
6128:
1.126 brouard 6129: /************ Prevalence ********************/
1.227 brouard 6130: 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)
6131: {
6132: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6133: in each health status at the date of interview (if between dateprev1 and dateprev2).
6134: We still use firstpass and lastpass as another selection.
6135: */
1.126 brouard 6136:
1.227 brouard 6137: int i, m, jk, j1, bool, z1,j, iv;
6138: int mi; /* Effective wave */
6139: int iage;
6140: double agebegin, ageend;
6141:
6142: double **prop;
6143: double posprop;
6144: double y2; /* in fractional years */
6145: int iagemin, iagemax;
6146: int first; /** to stop verbosity which is redirected to log file */
6147:
6148: iagemin= (int) agemin;
6149: iagemax= (int) agemax;
6150: /*pp=vector(1,nlstate);*/
1.251 brouard 6151: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6152: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6153: j1=0;
1.222 brouard 6154:
1.227 brouard 6155: /*j=cptcoveff;*/
6156: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6157:
1.288 brouard 6158: first=0;
1.335 brouard 6159: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6160: for (i=1; i<=nlstate; i++)
1.251 brouard 6161: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6162: prop[i][iage]=0.0;
6163: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6164: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6165: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6166:
6167: for (i=1; i<=imx; i++) { /* Each individual */
6168: bool=1;
6169: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6170: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6171: m=mw[mi][i];
6172: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6173: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6174: for (z1=1; z1<=cptcoveff; z1++){
6175: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6176: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6177: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6178: bool=0;
6179: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6180: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6181: bool=0;
6182: }
6183: }
6184: if(bool==1){ /* Otherwise we skip that wave/person */
6185: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6186: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6187: if(m >=firstpass && m <=lastpass){
6188: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6189: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6190: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6191: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6192: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6193: 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);
6194: exit(1);
6195: }
6196: if (s[m][i]>0 && s[m][i]<=nlstate) {
6197: /*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]]);*/
6198: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6199: prop[s[m][i]][iagemax+3] += weight[i];
6200: } /* end valid statuses */
6201: } /* end selection of dates */
6202: } /* end selection of waves */
6203: } /* end bool */
6204: } /* end wave */
6205: } /* end individual */
6206: for(i=iagemin; i <= iagemax+3; i++){
6207: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6208: posprop += prop[jk][i];
6209: }
6210:
6211: for(jk=1; jk <=nlstate ; jk++){
6212: if( i <= iagemax){
6213: if(posprop>=1.e-5){
6214: probs[i][jk][j1]= prop[jk][i]/posprop;
6215: } else{
1.288 brouard 6216: if(!first){
6217: first=1;
1.266 brouard 6218: 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]);
6219: }else{
1.288 brouard 6220: 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 6221: }
6222: }
6223: }
6224: }/* end jk */
6225: }/* end i */
1.222 brouard 6226: /*} *//* end i1 */
1.227 brouard 6227: } /* end j1 */
1.222 brouard 6228:
1.227 brouard 6229: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6230: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6231: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6232: } /* End of prevalence */
1.126 brouard 6233:
6234: /************* Waves Concatenation ***************/
6235:
6236: 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)
6237: {
1.298 brouard 6238: /* 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 6239: Death is a valid wave (if date is known).
6240: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6241: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6242: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6243: */
1.126 brouard 6244:
1.224 brouard 6245: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6246: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6247: double sum=0., jmean=0.;*/
1.224 brouard 6248: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6249: int j, k=0,jk, ju, jl;
6250: double sum=0.;
6251: first=0;
1.214 brouard 6252: firstwo=0;
1.217 brouard 6253: firsthree=0;
1.218 brouard 6254: firstfour=0;
1.164 brouard 6255: jmin=100000;
1.126 brouard 6256: jmax=-1;
6257: jmean=0.;
1.224 brouard 6258:
6259: /* Treating live states */
1.214 brouard 6260: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6261: mi=0; /* First valid wave */
1.227 brouard 6262: mli=0; /* Last valid wave */
1.309 brouard 6263: m=firstpass; /* Loop on waves */
6264: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6265: 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 */
6266: mli=m-1;/* mw[++mi][i]=m-1; */
6267: }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 6268: 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 6269: mli=m;
1.224 brouard 6270: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6271: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6272: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6273: }
1.309 brouard 6274: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6275: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6276: break;
1.224 brouard 6277: #else
1.317 brouard 6278: 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 6279: if(firsthree == 0){
1.302 brouard 6280: 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 6281: firsthree=1;
1.317 brouard 6282: }else if(firsthree >=1 && firsthree < 10){
6283: 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);
6284: firsthree++;
6285: }else if(firsthree == 10){
6286: printf("Information, too many Information flags: no more reported to log either\n");
6287: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6288: firsthree++;
6289: }else{
6290: firsthree++;
1.227 brouard 6291: }
1.309 brouard 6292: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6293: mli=m;
6294: }
6295: if(s[m][i]==-2){ /* Vital status is really unknown */
6296: nbwarn++;
1.309 brouard 6297: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6298: 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);
6299: 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);
6300: }
6301: break;
6302: }
6303: break;
1.224 brouard 6304: #endif
1.227 brouard 6305: }/* End m >= lastpass */
1.126 brouard 6306: }/* end while */
1.224 brouard 6307:
1.227 brouard 6308: /* 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 6309: /* After last pass */
1.224 brouard 6310: /* Treating death states */
1.214 brouard 6311: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6312: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6313: /* } */
1.126 brouard 6314: mi++; /* Death is another wave */
6315: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6316: /* Only death is a correct wave */
1.126 brouard 6317: mw[mi][i]=m;
1.257 brouard 6318: } /* else not in a death state */
1.224 brouard 6319: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6320: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6321: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6322: 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 6323: nbwarn++;
6324: if(firstfiv==0){
1.309 brouard 6325: 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 6326: firstfiv=1;
6327: }else{
1.309 brouard 6328: 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 6329: }
1.309 brouard 6330: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6331: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6332: nberr++;
6333: if(firstwo==0){
1.309 brouard 6334: 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 6335: firstwo=1;
6336: }
1.309 brouard 6337: 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 6338: }
1.257 brouard 6339: }else{ /* if date of interview is unknown */
1.227 brouard 6340: /* death is known but not confirmed by death status at any wave */
6341: if(firstfour==0){
1.309 brouard 6342: 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 6343: firstfour=1;
6344: }
1.309 brouard 6345: 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 6346: }
1.224 brouard 6347: } /* end if date of death is known */
6348: #endif
1.309 brouard 6349: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6350: /* wav[i]=mw[mi][i]; */
1.126 brouard 6351: if(mi==0){
6352: nbwarn++;
6353: if(first==0){
1.227 brouard 6354: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6355: first=1;
1.126 brouard 6356: }
6357: if(first==1){
1.227 brouard 6358: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6359: }
6360: } /* end mi==0 */
6361: } /* End individuals */
1.214 brouard 6362: /* wav and mw are no more changed */
1.223 brouard 6363:
1.317 brouard 6364: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6365: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6366:
6367:
1.126 brouard 6368: for(i=1; i<=imx; i++){
6369: for(mi=1; mi<wav[i];mi++){
6370: if (stepm <=0)
1.227 brouard 6371: dh[mi][i]=1;
1.126 brouard 6372: else{
1.260 brouard 6373: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6374: if (agedc[i] < 2*AGESUP) {
6375: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6376: if(j==0) j=1; /* Survives at least one month after exam */
6377: else if(j<0){
6378: nberr++;
6379: 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]);
6380: j=1; /* Temporary Dangerous patch */
6381: 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);
6382: 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]);
6383: 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);
6384: }
6385: k=k+1;
6386: if (j >= jmax){
6387: jmax=j;
6388: ijmax=i;
6389: }
6390: if (j <= jmin){
6391: jmin=j;
6392: ijmin=i;
6393: }
6394: sum=sum+j;
6395: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6396: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6397: }
6398: }
6399: else{
6400: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6401: /* 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 6402:
1.227 brouard 6403: k=k+1;
6404: if (j >= jmax) {
6405: jmax=j;
6406: ijmax=i;
6407: }
6408: else if (j <= jmin){
6409: jmin=j;
6410: ijmin=i;
6411: }
6412: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6413: /*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]);*/
6414: if(j<0){
6415: nberr++;
6416: 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]);
6417: 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]);
6418: }
6419: sum=sum+j;
6420: }
6421: jk= j/stepm;
6422: jl= j -jk*stepm;
6423: ju= j -(jk+1)*stepm;
6424: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6425: if(jl==0){
6426: dh[mi][i]=jk;
6427: bh[mi][i]=0;
6428: }else{ /* We want a negative bias in order to only have interpolation ie
6429: * to avoid the price of an extra matrix product in likelihood */
6430: dh[mi][i]=jk+1;
6431: bh[mi][i]=ju;
6432: }
6433: }else{
6434: if(jl <= -ju){
6435: dh[mi][i]=jk;
6436: bh[mi][i]=jl; /* bias is positive if real duration
6437: * is higher than the multiple of stepm and negative otherwise.
6438: */
6439: }
6440: else{
6441: dh[mi][i]=jk+1;
6442: bh[mi][i]=ju;
6443: }
6444: if(dh[mi][i]==0){
6445: dh[mi][i]=1; /* At least one step */
6446: bh[mi][i]=ju; /* At least one step */
6447: /* 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);*/
6448: }
6449: } /* end if mle */
1.126 brouard 6450: }
6451: } /* end wave */
6452: }
6453: jmean=sum/k;
6454: 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 6455: 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 6456: }
1.126 brouard 6457:
6458: /*********** Tricode ****************************/
1.220 brouard 6459: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6460: {
6461: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6462: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6463: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6464: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6465: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6466: */
1.130 brouard 6467:
1.242 brouard 6468: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6469: int modmaxcovj=0; /* Modality max of covariates j */
6470: int cptcode=0; /* Modality max of covariates j */
6471: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6472:
6473:
1.242 brouard 6474: /* cptcoveff=0; */
6475: /* *cptcov=0; */
1.126 brouard 6476:
1.242 brouard 6477: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6478: for (k=1; k <= maxncov; k++)
6479: for(j=1; j<=2; j++)
6480: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6481:
1.242 brouard 6482: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6483: 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 6484: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6485: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 6486: 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 6487: switch(Fixed[k]) {
6488: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6489: modmaxcovj=0;
6490: modmincovj=0;
1.242 brouard 6491: 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 6492: /* 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 6493: ij=(int)(covar[Tvar[k]][i]);
6494: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6495: * If product of Vn*Vm, still boolean *:
6496: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6497: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6498: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6499: modality of the nth covariate of individual i. */
6500: if (ij > modmaxcovj)
6501: modmaxcovj=ij;
6502: else if (ij < modmincovj)
6503: modmincovj=ij;
1.287 brouard 6504: if (ij <0 || ij >1 ){
1.311 brouard 6505: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6506: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6507: fflush(ficlog);
6508: exit(1);
1.287 brouard 6509: }
6510: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6511: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6512: exit(1);
6513: }else
6514: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6515: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6516: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6517: /* getting the maximum value of the modality of the covariate
6518: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6519: female ies 1, then modmaxcovj=1.
6520: */
6521: } /* end for loop on individuals i */
6522: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6523: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6524: cptcode=modmaxcovj;
6525: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6526: /*for (i=0; i<=cptcode; i++) {*/
6527: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6528: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6529: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6530: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6531: if( j != -1){
6532: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6533: covariate for which somebody answered excluding
6534: undefined. Usually 2: 0 and 1. */
6535: }
6536: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6537: covariate for which somebody answered including
6538: undefined. Usually 3: -1, 0 and 1. */
6539: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6540: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6541: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6542:
1.242 brouard 6543: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6544: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6545: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6546: /* modmincovj=3; modmaxcovj = 7; */
6547: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6548: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6549: /* defining two dummy variables: variables V1_1 and V1_2.*/
6550: /* nbcode[Tvar[j]][ij]=k; */
6551: /* nbcode[Tvar[j]][1]=0; */
6552: /* nbcode[Tvar[j]][2]=1; */
6553: /* nbcode[Tvar[j]][3]=2; */
6554: /* To be continued (not working yet). */
6555: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6556:
6557: /* 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*/
6558: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6559: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6560: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6561: /*, could be restored in the future */
6562: 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 6563: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6564: break;
6565: }
6566: ij++;
1.287 brouard 6567: 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 6568: cptcode = ij; /* New max modality for covar j */
6569: } /* end of loop on modality i=-1 to 1 or more */
6570: break;
6571: case 1: /* Testing on varying covariate, could be simple and
6572: * should look at waves or product of fixed *
6573: * varying. No time to test -1, assuming 0 and 1 only */
6574: ij=0;
6575: for(i=0; i<=1;i++){
6576: nbcode[Tvar[k]][++ij]=i;
6577: }
6578: break;
6579: default:
6580: break;
6581: } /* end switch */
6582: } /* end dummy test */
1.349 brouard 6583: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6584: 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 6585: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6586: printf("Error k=%d \n",k);
6587: exit(1);
6588: }
1.311 brouard 6589: if(isnan(covar[Tvar[k]][i])){
6590: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6591: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6592: fflush(ficlog);
6593: exit(1);
6594: }
6595: }
1.335 brouard 6596: } /* end Quanti */
1.287 brouard 6597: } /* 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 6598:
6599: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6600: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6601: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6602: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6603: 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 */
6604: 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 */
6605: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6606: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6607:
6608: ij=0;
6609: /* 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 6610: 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 */
6611: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6612: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6613: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6614: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6615: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6616: /* 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 6617: /* If product not in single variable we don't print results */
6618: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6619: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6620: /* k= 1 2 3 4 5 6 7 8 9 */
6621: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6622: /* ij 1 2 3 */
6623: /* Tvaraff[ij]= 4 3 1 */
6624: /* Tmodelind[ij]=2 3 9 */
6625: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6626: 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*/
6627: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6628: 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 */
6629: if(Fixed[k]!=0)
6630: anyvaryingduminmodel=1;
6631: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6632: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6633: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6634: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6635: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6636: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6637: }
6638: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6639: /* ij--; */
6640: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6641: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6642: * because they can be excluded from the model and real
6643: * if in the model but excluded because missing values, but how to get k from ij?*/
6644: for(j=ij+1; j<= cptcovt; j++){
6645: Tvaraff[j]=0;
6646: Tmodelind[j]=0;
6647: }
6648: for(j=ntveff+1; j<= cptcovt; j++){
6649: TmodelInvind[j]=0;
6650: }
6651: /* To be sorted */
6652: ;
6653: }
1.126 brouard 6654:
1.145 brouard 6655:
1.126 brouard 6656: /*********** Health Expectancies ****************/
6657:
1.235 brouard 6658: 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 6659:
6660: {
6661: /* Health expectancies, no variances */
1.329 brouard 6662: /* cij is the combination in the list of combination of dummy covariates */
6663: /* strstart is a string of time at start of computing */
1.164 brouard 6664: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6665: int nhstepma, nstepma; /* Decreasing with age */
6666: double age, agelim, hf;
6667: double ***p3mat;
6668: double eip;
6669:
1.238 brouard 6670: /* pstamp(ficreseij); */
1.126 brouard 6671: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6672: fprintf(ficreseij,"# Age");
6673: for(i=1; i<=nlstate;i++){
6674: for(j=1; j<=nlstate;j++){
6675: fprintf(ficreseij," e%1d%1d ",i,j);
6676: }
6677: fprintf(ficreseij," e%1d. ",i);
6678: }
6679: fprintf(ficreseij,"\n");
6680:
6681:
6682: if(estepm < stepm){
6683: printf ("Problem %d lower than %d\n",estepm, stepm);
6684: }
6685: else hstepm=estepm;
6686: /* We compute the life expectancy from trapezoids spaced every estepm months
6687: * This is mainly to measure the difference between two models: for example
6688: * if stepm=24 months pijx are given only every 2 years and by summing them
6689: * we are calculating an estimate of the Life Expectancy assuming a linear
6690: * progression in between and thus overestimating or underestimating according
6691: * to the curvature of the survival function. If, for the same date, we
6692: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6693: * to compare the new estimate of Life expectancy with the same linear
6694: * hypothesis. A more precise result, taking into account a more precise
6695: * curvature will be obtained if estepm is as small as stepm. */
6696:
6697: /* For example we decided to compute the life expectancy with the smallest unit */
6698: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6699: nhstepm is the number of hstepm from age to agelim
6700: nstepm is the number of stepm from age to agelin.
1.270 brouard 6701: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6702: and note for a fixed period like estepm months */
6703: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6704: survival function given by stepm (the optimization length). Unfortunately it
6705: means that if the survival funtion is printed only each two years of age and if
6706: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6707: results. So we changed our mind and took the option of the best precision.
6708: */
6709: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6710:
6711: agelim=AGESUP;
6712: /* If stepm=6 months */
6713: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6714: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6715:
6716: /* nhstepm age range expressed in number of stepm */
6717: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6718: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6719: /* if (stepm >= YEARM) hstepm=1;*/
6720: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6721: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6722:
6723: for (age=bage; age<=fage; age ++){
6724: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6725: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6726: /* if (stepm >= YEARM) hstepm=1;*/
6727: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6728:
6729: /* If stepm=6 months */
6730: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6731: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6732: /* 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 6733: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6734:
6735: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6736:
6737: printf("%d|",(int)age);fflush(stdout);
6738: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6739:
6740: /* Computing expectancies */
6741: for(i=1; i<=nlstate;i++)
6742: for(j=1; j<=nlstate;j++)
6743: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6744: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6745:
6746: /* 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]);*/
6747:
6748: }
6749:
6750: fprintf(ficreseij,"%3.0f",age );
6751: for(i=1; i<=nlstate;i++){
6752: eip=0;
6753: for(j=1; j<=nlstate;j++){
6754: eip +=eij[i][j][(int)age];
6755: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6756: }
6757: fprintf(ficreseij,"%9.4f", eip );
6758: }
6759: fprintf(ficreseij,"\n");
6760:
6761: }
6762: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6763: printf("\n");
6764: fprintf(ficlog,"\n");
6765:
6766: }
6767:
1.235 brouard 6768: 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 6769:
6770: {
6771: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6772: to initial status i, ei. .
1.126 brouard 6773: */
1.336 brouard 6774: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6775: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6776: int nhstepma, nstepma; /* Decreasing with age */
6777: double age, agelim, hf;
6778: double ***p3matp, ***p3matm, ***varhe;
6779: double **dnewm,**doldm;
6780: double *xp, *xm;
6781: double **gp, **gm;
6782: double ***gradg, ***trgradg;
6783: int theta;
6784:
6785: double eip, vip;
6786:
6787: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6788: xp=vector(1,npar);
6789: xm=vector(1,npar);
6790: dnewm=matrix(1,nlstate*nlstate,1,npar);
6791: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6792:
6793: pstamp(ficresstdeij);
6794: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6795: fprintf(ficresstdeij,"# Age");
6796: for(i=1; i<=nlstate;i++){
6797: for(j=1; j<=nlstate;j++)
6798: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6799: fprintf(ficresstdeij," e%1d. ",i);
6800: }
6801: fprintf(ficresstdeij,"\n");
6802:
6803: pstamp(ficrescveij);
6804: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6805: fprintf(ficrescveij,"# Age");
6806: for(i=1; i<=nlstate;i++)
6807: for(j=1; j<=nlstate;j++){
6808: cptj= (j-1)*nlstate+i;
6809: for(i2=1; i2<=nlstate;i2++)
6810: for(j2=1; j2<=nlstate;j2++){
6811: cptj2= (j2-1)*nlstate+i2;
6812: if(cptj2 <= cptj)
6813: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6814: }
6815: }
6816: fprintf(ficrescveij,"\n");
6817:
6818: if(estepm < stepm){
6819: printf ("Problem %d lower than %d\n",estepm, stepm);
6820: }
6821: else hstepm=estepm;
6822: /* We compute the life expectancy from trapezoids spaced every estepm months
6823: * This is mainly to measure the difference between two models: for example
6824: * if stepm=24 months pijx are given only every 2 years and by summing them
6825: * we are calculating an estimate of the Life Expectancy assuming a linear
6826: * progression in between and thus overestimating or underestimating according
6827: * to the curvature of the survival function. If, for the same date, we
6828: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6829: * to compare the new estimate of Life expectancy with the same linear
6830: * hypothesis. A more precise result, taking into account a more precise
6831: * curvature will be obtained if estepm is as small as stepm. */
6832:
6833: /* For example we decided to compute the life expectancy with the smallest unit */
6834: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6835: nhstepm is the number of hstepm from age to agelim
6836: nstepm is the number of stepm from age to agelin.
6837: Look at hpijx to understand the reason of that which relies in memory size
6838: and note for a fixed period like estepm months */
6839: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6840: survival function given by stepm (the optimization length). Unfortunately it
6841: means that if the survival funtion is printed only each two years of age and if
6842: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6843: results. So we changed our mind and took the option of the best precision.
6844: */
6845: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6846:
6847: /* If stepm=6 months */
6848: /* nhstepm age range expressed in number of stepm */
6849: agelim=AGESUP;
6850: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6851: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6852: /* if (stepm >= YEARM) hstepm=1;*/
6853: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6854:
6855: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6856: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6857: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6858: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6859: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6860: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6861:
6862: for (age=bage; age<=fage; age ++){
6863: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6864: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6865: /* if (stepm >= YEARM) hstepm=1;*/
6866: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6867:
1.126 brouard 6868: /* If stepm=6 months */
6869: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6870: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6871:
6872: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6873:
1.126 brouard 6874: /* Computing Variances of health expectancies */
6875: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6876: decrease memory allocation */
6877: for(theta=1; theta <=npar; theta++){
6878: for(i=1; i<=npar; i++){
1.222 brouard 6879: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6880: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6881: }
1.235 brouard 6882: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6883: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6884:
1.126 brouard 6885: for(j=1; j<= nlstate; j++){
1.222 brouard 6886: for(i=1; i<=nlstate; i++){
6887: for(h=0; h<=nhstepm-1; h++){
6888: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6889: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6890: }
6891: }
1.126 brouard 6892: }
1.218 brouard 6893:
1.126 brouard 6894: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6895: for(h=0; h<=nhstepm-1; h++){
6896: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6897: }
1.126 brouard 6898: }/* End theta */
6899:
6900:
6901: for(h=0; h<=nhstepm-1; h++)
6902: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6903: for(theta=1; theta <=npar; theta++)
6904: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6905:
1.218 brouard 6906:
1.222 brouard 6907: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6908: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6909: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6910:
1.222 brouard 6911: printf("%d|",(int)age);fflush(stdout);
6912: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6913: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6914: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6915: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6916: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6917: for(ij=1;ij<=nlstate*nlstate;ij++)
6918: for(ji=1;ji<=nlstate*nlstate;ji++)
6919: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6920: }
6921: }
1.320 brouard 6922: /* if((int)age ==50){ */
6923: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6924: /* } */
1.126 brouard 6925: /* Computing expectancies */
1.235 brouard 6926: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6927: for(i=1; i<=nlstate;i++)
6928: for(j=1; j<=nlstate;j++)
1.222 brouard 6929: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6930: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6931:
1.222 brouard 6932: /* 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 6933:
1.222 brouard 6934: }
1.269 brouard 6935:
6936: /* Standard deviation of expectancies ij */
1.126 brouard 6937: fprintf(ficresstdeij,"%3.0f",age );
6938: for(i=1; i<=nlstate;i++){
6939: eip=0.;
6940: vip=0.;
6941: for(j=1; j<=nlstate;j++){
1.222 brouard 6942: eip += eij[i][j][(int)age];
6943: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6944: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6945: 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 6946: }
6947: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6948: }
6949: fprintf(ficresstdeij,"\n");
1.218 brouard 6950:
1.269 brouard 6951: /* Variance of expectancies ij */
1.126 brouard 6952: fprintf(ficrescveij,"%3.0f",age );
6953: for(i=1; i<=nlstate;i++)
6954: for(j=1; j<=nlstate;j++){
1.222 brouard 6955: cptj= (j-1)*nlstate+i;
6956: for(i2=1; i2<=nlstate;i2++)
6957: for(j2=1; j2<=nlstate;j2++){
6958: cptj2= (j2-1)*nlstate+i2;
6959: if(cptj2 <= cptj)
6960: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6961: }
1.126 brouard 6962: }
6963: fprintf(ficrescveij,"\n");
1.218 brouard 6964:
1.126 brouard 6965: }
6966: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6967: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6968: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6969: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6970: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6971: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6972: printf("\n");
6973: fprintf(ficlog,"\n");
1.218 brouard 6974:
1.126 brouard 6975: free_vector(xm,1,npar);
6976: free_vector(xp,1,npar);
6977: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6978: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6979: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6980: }
1.218 brouard 6981:
1.126 brouard 6982: /************ Variance ******************/
1.235 brouard 6983: 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 6984: {
1.279 brouard 6985: /** Variance of health expectancies
6986: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6987: * double **newm;
6988: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6989: */
1.218 brouard 6990:
6991: /* int movingaverage(); */
6992: double **dnewm,**doldm;
6993: double **dnewmp,**doldmp;
6994: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6995: int first=0;
1.218 brouard 6996: int k;
6997: double *xp;
1.279 brouard 6998: double **gp, **gm; /**< for var eij */
6999: double ***gradg, ***trgradg; /**< for var eij */
7000: double **gradgp, **trgradgp; /**< for var p point j */
7001: double *gpp, *gmp; /**< for var p point j */
7002: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 7003: double ***p3mat;
7004: double age,agelim, hf;
7005: /* double ***mobaverage; */
7006: int theta;
7007: char digit[4];
7008: char digitp[25];
7009:
7010: char fileresprobmorprev[FILENAMELENGTH];
7011:
7012: if(popbased==1){
7013: if(mobilav!=0)
7014: strcpy(digitp,"-POPULBASED-MOBILAV_");
7015: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
7016: }
7017: else
7018: strcpy(digitp,"-STABLBASED_");
1.126 brouard 7019:
1.218 brouard 7020: /* if (mobilav!=0) { */
7021: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7022: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
7023: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
7024: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
7025: /* } */
7026: /* } */
7027:
7028: strcpy(fileresprobmorprev,"PRMORPREV-");
7029: sprintf(digit,"%-d",ij);
7030: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7031: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7032: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7033: strcat(fileresprobmorprev,fileresu);
7034: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7035: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7036: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7037: }
7038: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7039: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7040: pstamp(ficresprobmorprev);
7041: 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 7042: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7043:
7044: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7045: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7046: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7047: /* } */
7048: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7049: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7050: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7051: }
1.337 brouard 7052: /* for(j=1;j<=cptcoveff;j++) */
7053: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7054: fprintf(ficresprobmorprev,"\n");
7055:
1.218 brouard 7056: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7057: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7058: fprintf(ficresprobmorprev," p.%-d SE",j);
7059: for(i=1; i<=nlstate;i++)
7060: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7061: }
7062: fprintf(ficresprobmorprev,"\n");
7063:
7064: fprintf(ficgp,"\n# Routine varevsij");
7065: fprintf(ficgp,"\nunset title \n");
7066: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7067: 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");
7068: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7069:
1.218 brouard 7070: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7071: pstamp(ficresvij);
7072: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7073: if(popbased==1)
7074: 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);
7075: else
7076: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7077: fprintf(ficresvij,"# Age");
7078: for(i=1; i<=nlstate;i++)
7079: for(j=1; j<=nlstate;j++)
7080: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7081: fprintf(ficresvij,"\n");
7082:
7083: xp=vector(1,npar);
7084: dnewm=matrix(1,nlstate,1,npar);
7085: doldm=matrix(1,nlstate,1,nlstate);
7086: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7087: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7088:
7089: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7090: gpp=vector(nlstate+1,nlstate+ndeath);
7091: gmp=vector(nlstate+1,nlstate+ndeath);
7092: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7093:
1.218 brouard 7094: if(estepm < stepm){
7095: printf ("Problem %d lower than %d\n",estepm, stepm);
7096: }
7097: else hstepm=estepm;
7098: /* For example we decided to compute the life expectancy with the smallest unit */
7099: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7100: nhstepm is the number of hstepm from age to agelim
7101: nstepm is the number of stepm from age to agelim.
7102: Look at function hpijx to understand why because of memory size limitations,
7103: we decided (b) to get a life expectancy respecting the most precise curvature of the
7104: survival function given by stepm (the optimization length). Unfortunately it
7105: means that if the survival funtion is printed every two years of age and if
7106: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7107: results. So we changed our mind and took the option of the best precision.
7108: */
7109: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7110: agelim = AGESUP;
7111: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7112: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7113: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7114: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7115: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7116: gp=matrix(0,nhstepm,1,nlstate);
7117: gm=matrix(0,nhstepm,1,nlstate);
7118:
7119:
7120: for(theta=1; theta <=npar; theta++){
7121: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7122: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7123: }
1.279 brouard 7124: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7125: * returns into prlim .
1.288 brouard 7126: */
1.242 brouard 7127: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7128:
7129: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7130: if (popbased==1) {
7131: if(mobilav ==0){
7132: for(i=1; i<=nlstate;i++)
7133: prlim[i][i]=probs[(int)age][i][ij];
7134: }else{ /* mobilav */
7135: for(i=1; i<=nlstate;i++)
7136: prlim[i][i]=mobaverage[(int)age][i][ij];
7137: }
7138: }
1.295 brouard 7139: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7140: */
7141: 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 7142: /**< 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 7143: * at horizon h in state j including mortality.
7144: */
1.218 brouard 7145: for(j=1; j<= nlstate; j++){
7146: for(h=0; h<=nhstepm; h++){
7147: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7148: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7149: }
7150: }
1.279 brouard 7151: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7152: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7153: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7154: */
7155: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7156: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7157: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7158: }
7159:
7160: /* Again with minus shift */
1.218 brouard 7161:
7162: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7163: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7164:
1.242 brouard 7165: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7166:
7167: if (popbased==1) {
7168: if(mobilav ==0){
7169: for(i=1; i<=nlstate;i++)
7170: prlim[i][i]=probs[(int)age][i][ij];
7171: }else{ /* mobilav */
7172: for(i=1; i<=nlstate;i++)
7173: prlim[i][i]=mobaverage[(int)age][i][ij];
7174: }
7175: }
7176:
1.235 brouard 7177: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7178:
7179: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7180: for(h=0; h<=nhstepm; h++){
7181: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7182: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7183: }
7184: }
7185: /* This for computing probability of death (h=1 means
7186: computed over hstepm matrices product = hstepm*stepm months)
7187: as a weighted average of prlim.
7188: */
7189: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7190: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7191: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7192: }
1.279 brouard 7193: /* end shifting computations */
7194:
7195: /**< Computing gradient matrix at horizon h
7196: */
1.218 brouard 7197: for(j=1; j<= nlstate; j++) /* vareij */
7198: for(h=0; h<=nhstepm; h++){
7199: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7200: }
1.279 brouard 7201: /**< Gradient of overall mortality p.3 (or p.j)
7202: */
7203: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7204: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7205: }
7206:
7207: } /* End theta */
1.279 brouard 7208:
7209: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7210: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7211:
7212: for(h=0; h<=nhstepm; h++) /* veij */
7213: for(j=1; j<=nlstate;j++)
7214: for(theta=1; theta <=npar; theta++)
7215: trgradg[h][j][theta]=gradg[h][theta][j];
7216:
7217: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7218: for(theta=1; theta <=npar; theta++)
7219: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7220: /**< as well as its transposed matrix
7221: */
1.218 brouard 7222:
7223: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7224: for(i=1;i<=nlstate;i++)
7225: for(j=1;j<=nlstate;j++)
7226: vareij[i][j][(int)age] =0.;
1.279 brouard 7227:
7228: /* Computing trgradg by matcov by gradg at age and summing over h
7229: * and k (nhstepm) formula 15 of article
7230: * Lievre-Brouard-Heathcote
7231: */
7232:
1.218 brouard 7233: for(h=0;h<=nhstepm;h++){
7234: for(k=0;k<=nhstepm;k++){
7235: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7236: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7237: for(i=1;i<=nlstate;i++)
7238: for(j=1;j<=nlstate;j++)
7239: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7240: }
7241: }
7242:
1.279 brouard 7243: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7244: * p.j overall mortality formula 49 but computed directly because
7245: * we compute the grad (wix pijx) instead of grad (pijx),even if
7246: * wix is independent of theta.
7247: */
1.218 brouard 7248: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7249: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7250: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7251: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7252: varppt[j][i]=doldmp[j][i];
7253: /* end ppptj */
7254: /* x centered again */
7255:
1.242 brouard 7256: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7257:
7258: if (popbased==1) {
7259: if(mobilav ==0){
7260: for(i=1; i<=nlstate;i++)
7261: prlim[i][i]=probs[(int)age][i][ij];
7262: }else{ /* mobilav */
7263: for(i=1; i<=nlstate;i++)
7264: prlim[i][i]=mobaverage[(int)age][i][ij];
7265: }
7266: }
7267:
7268: /* This for computing probability of death (h=1 means
7269: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7270: as a weighted average of prlim.
7271: */
1.235 brouard 7272: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7273: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7274: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7275: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7276: }
7277: /* end probability of death */
7278:
7279: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7280: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7281: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7282: for(i=1; i<=nlstate;i++){
7283: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7284: }
7285: }
7286: fprintf(ficresprobmorprev,"\n");
7287:
7288: fprintf(ficresvij,"%.0f ",age );
7289: for(i=1; i<=nlstate;i++)
7290: for(j=1; j<=nlstate;j++){
7291: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7292: }
7293: fprintf(ficresvij,"\n");
7294: free_matrix(gp,0,nhstepm,1,nlstate);
7295: free_matrix(gm,0,nhstepm,1,nlstate);
7296: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7297: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7298: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7299: } /* End age */
7300: free_vector(gpp,nlstate+1,nlstate+ndeath);
7301: free_vector(gmp,nlstate+1,nlstate+ndeath);
7302: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7303: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7304: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7305: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7306: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7307: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7308: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7309: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7310: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7311: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7312: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7313: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7314: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7315: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7316: 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);
7317: /* 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 7318: */
1.218 brouard 7319: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7320: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7321:
1.218 brouard 7322: free_vector(xp,1,npar);
7323: free_matrix(doldm,1,nlstate,1,nlstate);
7324: free_matrix(dnewm,1,nlstate,1,npar);
7325: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7326: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7327: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7328: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7329: fclose(ficresprobmorprev);
7330: fflush(ficgp);
7331: fflush(fichtm);
7332: } /* end varevsij */
1.126 brouard 7333:
7334: /************ Variance of prevlim ******************/
1.269 brouard 7335: 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 7336: {
1.205 brouard 7337: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7338: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7339:
1.268 brouard 7340: double **dnewmpar,**doldm;
1.126 brouard 7341: int i, j, nhstepm, hstepm;
7342: double *xp;
7343: double *gp, *gm;
7344: double **gradg, **trgradg;
1.208 brouard 7345: double **mgm, **mgp;
1.126 brouard 7346: double age,agelim;
7347: int theta;
7348:
7349: pstamp(ficresvpl);
1.288 brouard 7350: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7351: fprintf(ficresvpl,"# Age ");
7352: if(nresult >=1)
7353: fprintf(ficresvpl," Result# ");
1.126 brouard 7354: for(i=1; i<=nlstate;i++)
7355: fprintf(ficresvpl," %1d-%1d",i,i);
7356: fprintf(ficresvpl,"\n");
7357:
7358: xp=vector(1,npar);
1.268 brouard 7359: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7360: doldm=matrix(1,nlstate,1,nlstate);
7361:
7362: hstepm=1*YEARM; /* Every year of age */
7363: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7364: agelim = AGESUP;
7365: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7366: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7367: if (stepm >= YEARM) hstepm=1;
7368: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7369: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7370: mgp=matrix(1,npar,1,nlstate);
7371: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7372: gp=vector(1,nlstate);
7373: gm=vector(1,nlstate);
7374:
7375: for(theta=1; theta <=npar; theta++){
7376: for(i=1; i<=npar; i++){ /* Computes gradient */
7377: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7378: }
1.288 brouard 7379: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7380: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7381: /* else */
7382: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7383: for(i=1;i<=nlstate;i++){
1.126 brouard 7384: gp[i] = prlim[i][i];
1.208 brouard 7385: mgp[theta][i] = prlim[i][i];
7386: }
1.126 brouard 7387: for(i=1; i<=npar; i++) /* Computes gradient */
7388: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7389: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7390: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7391: /* else */
7392: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7393: for(i=1;i<=nlstate;i++){
1.126 brouard 7394: gm[i] = prlim[i][i];
1.208 brouard 7395: mgm[theta][i] = prlim[i][i];
7396: }
1.126 brouard 7397: for(i=1;i<=nlstate;i++)
7398: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7399: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7400: } /* End theta */
7401:
7402: trgradg =matrix(1,nlstate,1,npar);
7403:
7404: for(j=1; j<=nlstate;j++)
7405: for(theta=1; theta <=npar; theta++)
7406: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7407: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7408: /* printf("\nmgm mgp %d ",(int)age); */
7409: /* for(j=1; j<=nlstate;j++){ */
7410: /* printf(" %d ",j); */
7411: /* for(theta=1; theta <=npar; theta++) */
7412: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7413: /* printf("\n "); */
7414: /* } */
7415: /* } */
7416: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7417: /* printf("\n gradg %d ",(int)age); */
7418: /* for(j=1; j<=nlstate;j++){ */
7419: /* printf("%d ",j); */
7420: /* for(theta=1; theta <=npar; theta++) */
7421: /* printf("%d %lf ",theta,gradg[theta][j]); */
7422: /* printf("\n "); */
7423: /* } */
7424: /* } */
1.126 brouard 7425:
7426: for(i=1;i<=nlstate;i++)
7427: varpl[i][(int)age] =0.;
1.209 brouard 7428: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7429: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7430: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7431: }else{
1.268 brouard 7432: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7433: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7434: }
1.126 brouard 7435: for(i=1;i<=nlstate;i++)
7436: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7437:
7438: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7439: if(nresult >=1)
7440: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7441: for(i=1; i<=nlstate;i++){
1.126 brouard 7442: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7443: /* for(j=1;j<=nlstate;j++) */
7444: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7445: }
1.126 brouard 7446: fprintf(ficresvpl,"\n");
7447: free_vector(gp,1,nlstate);
7448: free_vector(gm,1,nlstate);
1.208 brouard 7449: free_matrix(mgm,1,npar,1,nlstate);
7450: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7451: free_matrix(gradg,1,npar,1,nlstate);
7452: free_matrix(trgradg,1,nlstate,1,npar);
7453: } /* End age */
7454:
7455: free_vector(xp,1,npar);
7456: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7457: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7458:
7459: }
7460:
7461:
7462: /************ Variance of backprevalence limit ******************/
1.269 brouard 7463: 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 7464: {
7465: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7466: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7467:
7468: double **dnewmpar,**doldm;
7469: int i, j, nhstepm, hstepm;
7470: double *xp;
7471: double *gp, *gm;
7472: double **gradg, **trgradg;
7473: double **mgm, **mgp;
7474: double age,agelim;
7475: int theta;
7476:
7477: pstamp(ficresvbl);
7478: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7479: fprintf(ficresvbl,"# Age ");
7480: if(nresult >=1)
7481: fprintf(ficresvbl," Result# ");
7482: for(i=1; i<=nlstate;i++)
7483: fprintf(ficresvbl," %1d-%1d",i,i);
7484: fprintf(ficresvbl,"\n");
7485:
7486: xp=vector(1,npar);
7487: dnewmpar=matrix(1,nlstate,1,npar);
7488: doldm=matrix(1,nlstate,1,nlstate);
7489:
7490: hstepm=1*YEARM; /* Every year of age */
7491: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7492: agelim = AGEINF;
7493: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7494: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7495: if (stepm >= YEARM) hstepm=1;
7496: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7497: gradg=matrix(1,npar,1,nlstate);
7498: mgp=matrix(1,npar,1,nlstate);
7499: mgm=matrix(1,npar,1,nlstate);
7500: gp=vector(1,nlstate);
7501: gm=vector(1,nlstate);
7502:
7503: for(theta=1; theta <=npar; theta++){
7504: for(i=1; i<=npar; i++){ /* Computes gradient */
7505: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7506: }
7507: if(mobilavproj > 0 )
7508: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7509: else
7510: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7511: for(i=1;i<=nlstate;i++){
7512: gp[i] = bprlim[i][i];
7513: mgp[theta][i] = bprlim[i][i];
7514: }
7515: for(i=1; i<=npar; i++) /* Computes gradient */
7516: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7517: if(mobilavproj > 0 )
7518: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7519: else
7520: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7521: for(i=1;i<=nlstate;i++){
7522: gm[i] = bprlim[i][i];
7523: mgm[theta][i] = bprlim[i][i];
7524: }
7525: for(i=1;i<=nlstate;i++)
7526: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7527: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7528: } /* End theta */
7529:
7530: trgradg =matrix(1,nlstate,1,npar);
7531:
7532: for(j=1; j<=nlstate;j++)
7533: for(theta=1; theta <=npar; theta++)
7534: trgradg[j][theta]=gradg[theta][j];
7535: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7536: /* printf("\nmgm mgp %d ",(int)age); */
7537: /* for(j=1; j<=nlstate;j++){ */
7538: /* printf(" %d ",j); */
7539: /* for(theta=1; theta <=npar; theta++) */
7540: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7541: /* printf("\n "); */
7542: /* } */
7543: /* } */
7544: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7545: /* printf("\n gradg %d ",(int)age); */
7546: /* for(j=1; j<=nlstate;j++){ */
7547: /* printf("%d ",j); */
7548: /* for(theta=1; theta <=npar; theta++) */
7549: /* printf("%d %lf ",theta,gradg[theta][j]); */
7550: /* printf("\n "); */
7551: /* } */
7552: /* } */
7553:
7554: for(i=1;i<=nlstate;i++)
7555: varbpl[i][(int)age] =0.;
7556: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7557: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7558: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7559: }else{
7560: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7561: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7562: }
7563: for(i=1;i<=nlstate;i++)
7564: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7565:
7566: fprintf(ficresvbl,"%.0f ",age );
7567: if(nresult >=1)
7568: fprintf(ficresvbl,"%d ",nres );
7569: for(i=1; i<=nlstate;i++)
7570: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7571: fprintf(ficresvbl,"\n");
7572: free_vector(gp,1,nlstate);
7573: free_vector(gm,1,nlstate);
7574: free_matrix(mgm,1,npar,1,nlstate);
7575: free_matrix(mgp,1,npar,1,nlstate);
7576: free_matrix(gradg,1,npar,1,nlstate);
7577: free_matrix(trgradg,1,nlstate,1,npar);
7578: } /* End age */
7579:
7580: free_vector(xp,1,npar);
7581: free_matrix(doldm,1,nlstate,1,npar);
7582: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7583:
7584: }
7585:
7586: /************ Variance of one-step probabilities ******************/
7587: 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 7588: {
7589: int i, j=0, k1, l1, tj;
7590: int k2, l2, j1, z1;
7591: int k=0, l;
7592: int first=1, first1, first2;
1.326 brouard 7593: int nres=0; /* New */
1.222 brouard 7594: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7595: double **dnewm,**doldm;
7596: double *xp;
7597: double *gp, *gm;
7598: double **gradg, **trgradg;
7599: double **mu;
7600: double age, cov[NCOVMAX+1];
7601: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7602: int theta;
7603: char fileresprob[FILENAMELENGTH];
7604: char fileresprobcov[FILENAMELENGTH];
7605: char fileresprobcor[FILENAMELENGTH];
7606: double ***varpij;
7607:
7608: strcpy(fileresprob,"PROB_");
7609: strcat(fileresprob,fileres);
7610: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7611: printf("Problem with resultfile: %s\n", fileresprob);
7612: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7613: }
7614: strcpy(fileresprobcov,"PROBCOV_");
7615: strcat(fileresprobcov,fileresu);
7616: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7617: printf("Problem with resultfile: %s\n", fileresprobcov);
7618: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7619: }
7620: strcpy(fileresprobcor,"PROBCOR_");
7621: strcat(fileresprobcor,fileresu);
7622: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7623: printf("Problem with resultfile: %s\n", fileresprobcor);
7624: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7625: }
7626: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7627: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7628: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7629: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7630: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7631: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7632: pstamp(ficresprob);
7633: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7634: fprintf(ficresprob,"# Age");
7635: pstamp(ficresprobcov);
7636: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7637: fprintf(ficresprobcov,"# Age");
7638: pstamp(ficresprobcor);
7639: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7640: fprintf(ficresprobcor,"# Age");
1.126 brouard 7641:
7642:
1.222 brouard 7643: for(i=1; i<=nlstate;i++)
7644: for(j=1; j<=(nlstate+ndeath);j++){
7645: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7646: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7647: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7648: }
7649: /* fprintf(ficresprob,"\n");
7650: fprintf(ficresprobcov,"\n");
7651: fprintf(ficresprobcor,"\n");
7652: */
7653: xp=vector(1,npar);
7654: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7655: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7656: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7657: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7658: first=1;
7659: fprintf(ficgp,"\n# Routine varprob");
7660: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7661: fprintf(fichtm,"\n");
7662:
1.288 brouard 7663: 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 7664: 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);
7665: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7666: and drawn. It helps understanding how is the covariance between two incidences.\
7667: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7668: 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 7669: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7670: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7671: standard deviations wide on each axis. <br>\
7672: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7673: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7674: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7675:
1.222 brouard 7676: cov[1]=1;
7677: /* tj=cptcoveff; */
1.225 brouard 7678: tj = (int) pow(2,cptcoveff);
1.222 brouard 7679: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7680: j1=0;
1.332 brouard 7681:
7682: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7683: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7684: /* 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 7685: if(tj != 1 && TKresult[nres]!= j1)
7686: continue;
7687:
7688: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7689: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7690: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7691: if (cptcovn>0) {
1.334 brouard 7692: fprintf(ficresprob, "\n#********** Variable ");
7693: fprintf(ficresprobcov, "\n#********** Variable ");
7694: fprintf(ficgp, "\n#********** Variable ");
7695: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7696: fprintf(ficresprobcor, "\n#********** Variable ");
7697:
7698: /* Including quantitative variables of the resultline to be done */
7699: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7700: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7701: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7702: /* 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 7703: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7704: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7705: 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 */
7706: 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 */
7707: 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 */
7708: 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 */
7709: 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 */
7710: fprintf(ficresprob,"fixed ");
7711: fprintf(ficresprobcov,"fixed ");
7712: fprintf(ficgp,"fixed ");
7713: fprintf(fichtmcov,"fixed ");
7714: fprintf(ficresprobcor,"fixed ");
7715: }else{
7716: fprintf(ficresprob,"varyi ");
7717: fprintf(ficresprobcov,"varyi ");
7718: fprintf(ficgp,"varyi ");
7719: fprintf(fichtmcov,"varyi ");
7720: fprintf(ficresprobcor,"varyi ");
7721: }
7722: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7723: /* For each selected (single) quantitative value */
1.337 brouard 7724: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7725: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7726: fprintf(ficresprob,"fixed ");
7727: fprintf(ficresprobcov,"fixed ");
7728: fprintf(ficgp,"fixed ");
7729: fprintf(fichtmcov,"fixed ");
7730: fprintf(ficresprobcor,"fixed ");
7731: }else{
7732: fprintf(ficresprob,"varyi ");
7733: fprintf(ficresprobcov,"varyi ");
7734: fprintf(ficgp,"varyi ");
7735: fprintf(fichtmcov,"varyi ");
7736: fprintf(ficresprobcor,"varyi ");
7737: }
7738: }else{
7739: 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 */
7740: 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 */
7741: exit(1);
7742: }
7743: } /* End loop on variable of this resultline */
7744: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7745: fprintf(ficresprob, "**********\n#\n");
7746: fprintf(ficresprobcov, "**********\n#\n");
7747: fprintf(ficgp, "**********\n#\n");
7748: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7749: fprintf(ficresprobcor, "**********\n#");
7750: if(invalidvarcomb[j1]){
7751: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7752: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7753: continue;
7754: }
7755: }
7756: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7757: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7758: gp=vector(1,(nlstate)*(nlstate+ndeath));
7759: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7760: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7761: cov[2]=age;
7762: if(nagesqr==1)
7763: cov[3]= age*age;
1.334 brouard 7764: /* New code end of combination but for each resultline */
7765: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 7766: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7767: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7768: }else{
1.334 brouard 7769: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7770: }
1.334 brouard 7771: }/* End of loop on model equation */
7772: /* Old code */
7773: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7774: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7775: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7776: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7777: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7778: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7779: /* * 1 1 1 1 1 */
7780: /* * 2 2 1 1 1 */
7781: /* * 3 1 2 1 1 */
7782: /* *\/ */
7783: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7784: /* } */
7785: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7786: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7787: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7788: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7789: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7790: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7791: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7792: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7793: /* 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]); */
7794: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7795: /* /\* exit(1); *\/ */
7796: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7797: /* } */
7798: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7799: /* } */
7800: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7801: /* if(Dummy[Tvard[k][1]]==0){ */
7802: /* if(Dummy[Tvard[k][2]]==0){ */
7803: /* 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]])]; */
7804: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7805: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7806: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7807: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7808: /* } */
7809: /* }else{ */
7810: /* if(Dummy[Tvard[k][2]]==0){ */
7811: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7812: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7813: /* }else{ */
7814: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7815: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7816: /* } */
7817: /* } */
7818: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7819: /* } */
1.326 brouard 7820: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7821: for(theta=1; theta <=npar; theta++){
7822: for(i=1; i<=npar; i++)
7823: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7824:
1.222 brouard 7825: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7826:
1.222 brouard 7827: k=0;
7828: for(i=1; i<= (nlstate); i++){
7829: for(j=1; j<=(nlstate+ndeath);j++){
7830: k=k+1;
7831: gp[k]=pmmij[i][j];
7832: }
7833: }
1.220 brouard 7834:
1.222 brouard 7835: for(i=1; i<=npar; i++)
7836: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7837:
1.222 brouard 7838: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7839: k=0;
7840: for(i=1; i<=(nlstate); i++){
7841: for(j=1; j<=(nlstate+ndeath);j++){
7842: k=k+1;
7843: gm[k]=pmmij[i][j];
7844: }
7845: }
1.220 brouard 7846:
1.222 brouard 7847: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7848: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7849: }
1.126 brouard 7850:
1.222 brouard 7851: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7852: for(theta=1; theta <=npar; theta++)
7853: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7854:
1.222 brouard 7855: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7856: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7857:
1.222 brouard 7858: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7859:
1.222 brouard 7860: k=0;
7861: for(i=1; i<=(nlstate); i++){
7862: for(j=1; j<=(nlstate+ndeath);j++){
7863: k=k+1;
7864: mu[k][(int) age]=pmmij[i][j];
7865: }
7866: }
7867: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7868: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7869: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7870:
1.222 brouard 7871: /*printf("\n%d ",(int)age);
7872: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7873: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7874: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7875: }*/
1.220 brouard 7876:
1.222 brouard 7877: fprintf(ficresprob,"\n%d ",(int)age);
7878: fprintf(ficresprobcov,"\n%d ",(int)age);
7879: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7880:
1.222 brouard 7881: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7882: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7883: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7884: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7885: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7886: }
7887: i=0;
7888: for (k=1; k<=(nlstate);k++){
7889: for (l=1; l<=(nlstate+ndeath);l++){
7890: i++;
7891: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7892: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7893: for (j=1; j<=i;j++){
7894: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7895: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7896: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7897: }
7898: }
7899: }/* end of loop for state */
7900: } /* end of loop for age */
7901: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7902: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7903: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7904: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7905:
7906: /* Confidence intervalle of pij */
7907: /*
7908: fprintf(ficgp,"\nunset parametric;unset label");
7909: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7910: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7911: 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);
7912: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7913: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7914: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7915: */
7916:
7917: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7918: first1=1;first2=2;
7919: for (k2=1; k2<=(nlstate);k2++){
7920: for (l2=1; l2<=(nlstate+ndeath);l2++){
7921: if(l2==k2) continue;
7922: j=(k2-1)*(nlstate+ndeath)+l2;
7923: for (k1=1; k1<=(nlstate);k1++){
7924: for (l1=1; l1<=(nlstate+ndeath);l1++){
7925: if(l1==k1) continue;
7926: i=(k1-1)*(nlstate+ndeath)+l1;
7927: if(i<=j) continue;
7928: for (age=bage; age<=fage; age ++){
7929: if ((int)age %5==0){
7930: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7931: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7932: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7933: mu1=mu[i][(int) age]/stepm*YEARM ;
7934: mu2=mu[j][(int) age]/stepm*YEARM;
7935: c12=cv12/sqrt(v1*v2);
7936: /* Computing eigen value of matrix of covariance */
7937: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7938: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7939: if ((lc2 <0) || (lc1 <0) ){
7940: if(first2==1){
7941: first1=0;
7942: 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);
7943: }
7944: 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);
7945: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7946: /* lc2=fabs(lc2); */
7947: }
1.220 brouard 7948:
1.222 brouard 7949: /* Eigen vectors */
1.280 brouard 7950: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7951: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7952: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7953: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7954: }else
7955: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7956: /*v21=sqrt(1.-v11*v11); *//* error */
7957: v21=(lc1-v1)/cv12*v11;
7958: v12=-v21;
7959: v22=v11;
7960: tnalp=v21/v11;
7961: if(first1==1){
7962: first1=0;
7963: 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);
7964: }
7965: 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);
7966: /*printf(fignu*/
7967: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7968: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7969: if(first==1){
7970: first=0;
7971: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7972: fprintf(ficgp,"\nset parametric;unset label");
7973: 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);
7974: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7975: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7976: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7977: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7978: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7979: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7980: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7981: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7982: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7983: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7984: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7985: 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 7986: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7987: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7988: }else{
7989: first=0;
7990: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7991: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7992: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7993: 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 7994: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7995: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7996: }/* if first */
7997: } /* age mod 5 */
7998: } /* end loop age */
7999: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8000: first=1;
8001: } /*l12 */
8002: } /* k12 */
8003: } /*l1 */
8004: }/* k1 */
1.332 brouard 8005: } /* loop on combination of covariates j1 */
1.326 brouard 8006: } /* loop on nres */
1.222 brouard 8007: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
8008: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
8009: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
8010: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
8011: free_vector(xp,1,npar);
8012: fclose(ficresprob);
8013: fclose(ficresprobcov);
8014: fclose(ficresprobcor);
8015: fflush(ficgp);
8016: fflush(fichtmcov);
8017: }
1.126 brouard 8018:
8019:
8020: /******************* Printing html file ***********/
1.201 brouard 8021: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8022: int lastpass, int stepm, int weightopt, char model[],\
8023: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 8024: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
8025: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
8026: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 8027: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 8028: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8029: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8030: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8031: </ul>");
1.319 brouard 8032: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8033: /* </ul>", model); */
1.214 brouard 8034: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8035: 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",
8036: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8037: 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 8038: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8039: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8040: fprintf(fichtm,"\
8041: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8042: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8043: fprintf(fichtm,"\
1.217 brouard 8044: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8045: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8046: fprintf(fichtm,"\
1.288 brouard 8047: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8048: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8049: fprintf(fichtm,"\
1.288 brouard 8050: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8051: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8052: fprintf(fichtm,"\
1.211 brouard 8053: - (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 8054: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8055: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8056: if(prevfcast==1){
8057: fprintf(fichtm,"\
8058: - Prevalence projections by age and states: \
1.201 brouard 8059: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8060: }
1.126 brouard 8061:
8062:
1.225 brouard 8063: m=pow(2,cptcoveff);
1.222 brouard 8064: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8065:
1.317 brouard 8066: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8067:
8068: jj1=0;
8069:
8070: fprintf(fichtm," \n<ul>");
1.337 brouard 8071: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8072: /* k1=nres; */
1.338 brouard 8073: k1=TKresult[nres];
8074: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8075: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8076: /* if(m != 1 && TKresult[nres]!= k1) */
8077: /* continue; */
1.264 brouard 8078: jj1++;
8079: if (cptcovn > 0) {
8080: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8081: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8082: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8083: }
1.337 brouard 8084: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8085: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8086: /* } */
8087: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8088: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8089: /* } */
1.264 brouard 8090: fprintf(fichtm,"\">");
8091:
8092: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8093: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8094: for (cpt=1; cpt<=cptcovs;cpt++){
8095: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8096: }
1.337 brouard 8097: /* fprintf(fichtm,"************ Results for covariates"); */
8098: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8099: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8100: /* } */
8101: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8102: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8103: /* } */
1.264 brouard 8104: if(invalidvarcomb[k1]){
8105: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8106: continue;
8107: }
8108: fprintf(fichtm,"</a></li>");
8109: } /* cptcovn >0 */
8110: }
1.317 brouard 8111: fprintf(fichtm," \n</ul>");
1.264 brouard 8112:
1.222 brouard 8113: jj1=0;
1.237 brouard 8114:
1.337 brouard 8115: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8116: /* k1=nres; */
1.338 brouard 8117: k1=TKresult[nres];
8118: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8119: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8120: /* if(m != 1 && TKresult[nres]!= k1) */
8121: /* continue; */
1.220 brouard 8122:
1.222 brouard 8123: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8124: jj1++;
8125: if (cptcovn > 0) {
1.264 brouard 8126: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8127: for (cpt=1; cpt<=cptcovs;cpt++){
8128: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8129: }
1.337 brouard 8130: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8131: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8132: /* } */
1.264 brouard 8133: fprintf(fichtm,"\"</a>");
8134:
1.222 brouard 8135: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8136: for (cpt=1; cpt<=cptcovs;cpt++){
8137: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8138: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8139: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8140: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8141: }
1.230 brouard 8142: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8143: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8144: if(invalidvarcomb[k1]){
8145: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8146: printf("\nCombination (%d) ignored because no cases \n",k1);
8147: continue;
8148: }
8149: }
8150: /* aij, bij */
1.259 brouard 8151: 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 8152: <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 8153: /* Pij */
1.241 brouard 8154: 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> \
8155: <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 8156: /* Quasi-incidences */
8157: 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 8158: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8159: 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 8160: 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> \
8161: <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 8162: /* Survival functions (period) in state j */
8163: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8164: 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);
8165: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8166: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8167: }
8168: /* State specific survival functions (period) */
8169: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8170: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8171: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8172: <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);
8173: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8174: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8175: }
1.288 brouard 8176: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8177: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8178: 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 8179: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8180: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8181: }
1.296 brouard 8182: if(prevbcast==1){
1.288 brouard 8183: /* Backward prevalence in each health state */
1.222 brouard 8184: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8185: 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);
8186: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8187: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8188: }
1.217 brouard 8189: }
1.222 brouard 8190: if(prevfcast==1){
1.288 brouard 8191: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8192: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8193: 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);
8194: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8195: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8196: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8197: }
8198: }
1.296 brouard 8199: if(prevbcast==1){
1.268 brouard 8200: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8201: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8202: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8203: 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 \
8204: 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 8205: 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);
8206: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8207: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8208: }
8209: }
1.220 brouard 8210:
1.222 brouard 8211: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8212: 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);
8213: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8214: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8215: }
8216: /* } /\* end i1 *\/ */
1.337 brouard 8217: }/* End k1=nres */
1.222 brouard 8218: fprintf(fichtm,"</ul>");
1.126 brouard 8219:
1.222 brouard 8220: fprintf(fichtm,"\
1.126 brouard 8221: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8222: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8223: - 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 8224: But because parameters are usually highly correlated (a higher incidence of disability \
8225: and a higher incidence of recovery can give very close observed transition) it might \
8226: be very useful to look not only at linear confidence intervals estimated from the \
8227: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8228: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8229: covariance matrix of the one-step probabilities. \
8230: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8231:
1.222 brouard 8232: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8233: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8234: fprintf(fichtm,"\
1.126 brouard 8235: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8236: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8237:
1.222 brouard 8238: fprintf(fichtm,"\
1.126 brouard 8239: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8240: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8241: fprintf(fichtm,"\
1.126 brouard 8242: - 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): \
8243: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8244: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8245: fprintf(fichtm,"\
1.126 brouard 8246: - (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): \
8247: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8248: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8249: fprintf(fichtm,"\
1.288 brouard 8250: - 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 8251: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8252: fprintf(fichtm,"\
1.128 brouard 8253: - 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 8254: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8255: fprintf(fichtm,"\
1.288 brouard 8256: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8257: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8258:
8259: /* if(popforecast==1) fprintf(fichtm,"\n */
8260: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8261: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8262: /* <br>",fileres,fileres,fileres,fileres); */
8263: /* else */
1.338 brouard 8264: /* 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 8265: fflush(fichtm);
1.126 brouard 8266:
1.225 brouard 8267: m=pow(2,cptcoveff);
1.222 brouard 8268: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8269:
1.317 brouard 8270: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8271:
8272: jj1=0;
8273:
8274: fprintf(fichtm," \n<ul>");
1.337 brouard 8275: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8276: /* k1=nres; */
1.338 brouard 8277: k1=TKresult[nres];
1.337 brouard 8278: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8279: /* if(m != 1 && TKresult[nres]!= k1) */
8280: /* continue; */
1.317 brouard 8281: jj1++;
8282: if (cptcovn > 0) {
8283: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8284: for (cpt=1; cpt<=cptcovs;cpt++){
8285: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8286: }
8287: fprintf(fichtm,"\">");
8288:
8289: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8290: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8291: for (cpt=1; cpt<=cptcovs;cpt++){
8292: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8293: }
8294: if(invalidvarcomb[k1]){
8295: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8296: continue;
8297: }
8298: fprintf(fichtm,"</a></li>");
8299: } /* cptcovn >0 */
1.337 brouard 8300: } /* End nres */
1.317 brouard 8301: fprintf(fichtm," \n</ul>");
8302:
1.222 brouard 8303: jj1=0;
1.237 brouard 8304:
1.241 brouard 8305: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8306: /* k1=nres; */
1.338 brouard 8307: k1=TKresult[nres];
8308: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8309: /* for(k1=1; k1<=m;k1++){ */
8310: /* if(m != 1 && TKresult[nres]!= k1) */
8311: /* continue; */
1.222 brouard 8312: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8313: jj1++;
1.126 brouard 8314: if (cptcovn > 0) {
1.317 brouard 8315: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8316: for (cpt=1; cpt<=cptcovs;cpt++){
8317: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8318: }
8319: fprintf(fichtm,"\"</a>");
8320:
1.126 brouard 8321: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8322: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8323: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8324: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8325: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8326: }
1.237 brouard 8327:
1.338 brouard 8328: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8329:
1.222 brouard 8330: if(invalidvarcomb[k1]){
8331: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8332: continue;
8333: }
1.337 brouard 8334: } /* If cptcovn >0 */
1.126 brouard 8335: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8336: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8337: 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);
8338: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8339: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8340: }
8341: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8342: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8343: true period expectancies (those weighted with period prevalences are also\
8344: drawn in addition to the population based expectancies computed using\
1.314 brouard 8345: 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);
8346: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8347: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8348: /* } /\* end i1 *\/ */
1.241 brouard 8349: }/* End nres */
1.222 brouard 8350: fprintf(fichtm,"</ul>");
8351: fflush(fichtm);
1.126 brouard 8352: }
8353:
8354: /******************* Gnuplot file **************/
1.296 brouard 8355: 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 8356:
8357: char dirfileres[132],optfileres[132];
1.264 brouard 8358: char gplotcondition[132], gplotlabel[132];
1.343 brouard 8359: 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 8360: int lv=0, vlv=0, kl=0;
1.130 brouard 8361: int ng=0;
1.201 brouard 8362: int vpopbased;
1.223 brouard 8363: int ioffset; /* variable offset for columns */
1.270 brouard 8364: int iyearc=1; /* variable column for year of projection */
8365: int iagec=1; /* variable column for age of projection */
1.235 brouard 8366: int nres=0; /* Index of resultline */
1.266 brouard 8367: int istart=1; /* For starting graphs in projections */
1.219 brouard 8368:
1.126 brouard 8369: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8370: /* printf("Problem with file %s",optionfilegnuplot); */
8371: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8372: /* } */
8373:
8374: /*#ifdef windows */
8375: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8376: /*#endif */
1.225 brouard 8377: m=pow(2,cptcoveff);
1.126 brouard 8378:
1.274 brouard 8379: /* diagram of the model */
8380: fprintf(ficgp,"\n#Diagram of the model \n");
8381: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8382: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8383: 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);
8384:
1.343 brouard 8385: 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 8386: fprintf(ficgp,"\n#show arrow\nunset label\n");
8387: 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);
8388: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8389: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8390: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8391: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8392:
1.202 brouard 8393: /* Contribution to likelihood */
8394: /* Plot the probability implied in the likelihood */
1.223 brouard 8395: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8396: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8397: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8398: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8399: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8400: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8401: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8402: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8403: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8404: 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));
8405: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8406: 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));
8407: for (i=1; i<= nlstate ; i ++) {
8408: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8409: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8410: 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);
8411: for (j=2; j<= nlstate+ndeath ; j ++) {
8412: 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);
8413: }
8414: fprintf(ficgp,";\nset out; unset ylabel;\n");
8415: }
8416: /* 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 */
8417: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8418: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8419: fprintf(ficgp,"\nset out;unset log\n");
8420: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8421:
1.343 brouard 8422: /* Plot the probability implied in the likelihood by covariate value */
8423: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8424: /* if(debugILK==1){ */
8425: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8426: kvar=Tvar[TvarFind[kf]]; /* variable name */
8427: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 8428: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
8429: k=19+kf;/*offset because there are 19 columns in the ILK_ file */
1.343 brouard 8430: for (i=1; i<= nlstate ; i ++) {
8431: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8432: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8433: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8434: 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);
8435: for (j=2; j<= nlstate+ndeath ; j ++) {
8436: 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);
8437: }
8438: }else{
8439: 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);
8440: for (j=2; j<= nlstate+ndeath ; j ++) {
8441: 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);
8442: }
1.343 brouard 8443: }
8444: fprintf(ficgp,";\nset out; unset ylabel;\n");
8445: }
8446: } /* End of each covariate dummy */
8447: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8448: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8449: * kmodel = 1 2 3 4 5 6 7 8 9
8450: * varying 1 2 3 4 5
8451: * ncovv 1 2 3 4 5 6 7 8
8452: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8453: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8454: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8455: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8456: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8457: */
8458: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8459: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8460: /* 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]); */
8461: if(ipos!=iposold){ /* Not a product or first of a product */
8462: /* printf(" %d",ipos); */
8463: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8464: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8465: kk++; /* Position of the ncovv column in ILK_ */
8466: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8467: 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) */
8468: for (i=1; i<= nlstate ; i ++) {
8469: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8470: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8471:
1.348 brouard 8472: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8473: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8474: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8475: 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);
8476: for (j=2; j<= nlstate+ndeath ; j ++) {
8477: 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);
8478: }
8479: }else{
8480: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8481: 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);
8482: for (j=2; j<= nlstate+ndeath ; j ++) {
8483: 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);
8484: }
8485: }
8486: fprintf(ficgp,";\nset out; unset ylabel;\n");
8487: }
8488: }/* End if dummy varying */
8489: }else{ /*Product */
8490: /* printf("*"); */
8491: /* fprintf(ficresilk,"*"); */
8492: }
8493: iposold=ipos;
8494: } /* For each time varying covariate */
8495: /* } /\* debugILK==1 *\/ */
8496: /* 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 */
8497: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8498: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8499: fprintf(ficgp,"\nset out;unset log\n");
8500: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8501:
8502:
8503:
1.126 brouard 8504: strcpy(dirfileres,optionfilefiname);
8505: strcpy(optfileres,"vpl");
1.223 brouard 8506: /* 1eme*/
1.238 brouard 8507: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8508: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8509: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8510: k1=TKresult[nres];
1.338 brouard 8511: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8512: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8513: /* if(m != 1 && TKresult[nres]!= k1) */
8514: /* continue; */
1.238 brouard 8515: /* We are interested in selected combination by the resultline */
1.246 brouard 8516: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8517: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8518: strcpy(gplotlabel,"(");
1.337 brouard 8519: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8520: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8521: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8522:
8523: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8524: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8525: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8526: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8527: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8528: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8529: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8530: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8531: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8532: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8533: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8534: /* } */
8535: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8536: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8537: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8538: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8539: }
8540: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8541: /* printf("\n#\n"); */
1.238 brouard 8542: fprintf(ficgp,"\n#\n");
8543: if(invalidvarcomb[k1]){
1.260 brouard 8544: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8545: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8546: continue;
8547: }
1.235 brouard 8548:
1.241 brouard 8549: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8550: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8551: /* 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 8552: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8553: 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);
8554: /* 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); */
8555: /* k1-1 error should be nres-1*/
1.238 brouard 8556: for (i=1; i<= nlstate ; i ++) {
8557: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8558: else fprintf(ficgp," %%*lf (%%*lf)");
8559: }
1.288 brouard 8560: 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 8561: for (i=1; i<= nlstate ; i ++) {
8562: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8563: else fprintf(ficgp," %%*lf (%%*lf)");
8564: }
1.260 brouard 8565: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8566: for (i=1; i<= nlstate ; i ++) {
8567: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8568: else fprintf(ficgp," %%*lf (%%*lf)");
8569: }
1.265 brouard 8570: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8571:
8572: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8573: if(cptcoveff ==0){
1.271 brouard 8574: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8575: }else{
8576: kl=0;
8577: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8578: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8579: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8580: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8581: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8582: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8583: vlv= nbcode[Tvaraff[k]][lv];
8584: kl++;
8585: /* 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 *\/ */
8586: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8587: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8588: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8589: if(k==cptcoveff){
8590: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8591: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8592: }else{
8593: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8594: kl++;
8595: }
8596: } /* end covariate */
8597: } /* end if no covariate */
8598:
1.296 brouard 8599: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8600: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8601: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8602: if(cptcoveff ==0){
1.245 brouard 8603: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8604: }else{
8605: kl=0;
8606: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8607: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8608: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8609: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8610: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8611: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8612: /* vlv= nbcode[Tvaraff[k]][lv]; */
8613: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8614: kl++;
1.238 brouard 8615: /* 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 *\/ */
8616: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8617: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8618: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8619: if(k==cptcoveff){
1.245 brouard 8620: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8621: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8622: }else{
1.332 brouard 8623: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8624: kl++;
8625: }
8626: } /* end covariate */
8627: } /* end if no covariate */
1.296 brouard 8628: if(prevbcast == 1){
1.268 brouard 8629: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8630: /* k1-1 error should be nres-1*/
8631: for (i=1; i<= nlstate ; i ++) {
8632: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8633: else fprintf(ficgp," %%*lf (%%*lf)");
8634: }
1.271 brouard 8635: 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 8636: for (i=1; i<= nlstate ; i ++) {
8637: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8638: else fprintf(ficgp," %%*lf (%%*lf)");
8639: }
1.276 brouard 8640: 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 8641: for (i=1; i<= nlstate ; i ++) {
8642: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8643: else fprintf(ficgp," %%*lf (%%*lf)");
8644: }
1.274 brouard 8645: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8646: } /* end if backprojcast */
1.296 brouard 8647: } /* end if prevbcast */
1.276 brouard 8648: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8649: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8650: } /* nres */
1.337 brouard 8651: /* } /\* k1 *\/ */
1.201 brouard 8652: } /* cpt */
1.235 brouard 8653:
8654:
1.126 brouard 8655: /*2 eme*/
1.337 brouard 8656: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8657: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8658: k1=TKresult[nres];
1.338 brouard 8659: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8660: /* if(m != 1 && TKresult[nres]!= k1) */
8661: /* continue; */
1.238 brouard 8662: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8663: strcpy(gplotlabel,"(");
1.337 brouard 8664: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8665: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8666: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8667: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8668: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8669: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8670: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8671: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8672: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8673: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8674: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8675: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8676: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8677: /* } */
8678: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8679: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8680: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8681: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8682: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8683: }
1.264 brouard 8684: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8685: fprintf(ficgp,"\n#\n");
1.223 brouard 8686: if(invalidvarcomb[k1]){
8687: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8688: continue;
8689: }
1.219 brouard 8690:
1.241 brouard 8691: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8692: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8693: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8694: if(vpopbased==0){
1.238 brouard 8695: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8696: }else
1.238 brouard 8697: fprintf(ficgp,"\nreplot ");
8698: for (i=1; i<= nlstate+1 ; i ++) {
8699: k=2*i;
1.261 brouard 8700: 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 8701: for (j=1; j<= nlstate+1 ; j ++) {
8702: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8703: else fprintf(ficgp," %%*lf (%%*lf)");
8704: }
8705: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8706: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8707: 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 8708: for (j=1; j<= nlstate+1 ; j ++) {
8709: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8710: else fprintf(ficgp," %%*lf (%%*lf)");
8711: }
8712: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8713: 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 8714: for (j=1; j<= nlstate+1 ; j ++) {
8715: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8716: else fprintf(ficgp," %%*lf (%%*lf)");
8717: }
8718: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8719: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8720: } /* state */
8721: } /* vpopbased */
1.264 brouard 8722: 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 8723: } /* end nres */
1.337 brouard 8724: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8725:
8726:
8727: /*3eme*/
1.337 brouard 8728: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8729: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8730: k1=TKresult[nres];
1.338 brouard 8731: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8732: /* if(m != 1 && TKresult[nres]!= k1) */
8733: /* continue; */
1.238 brouard 8734:
1.332 brouard 8735: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8736: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8737: strcpy(gplotlabel,"(");
1.337 brouard 8738: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8739: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8740: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8741: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8742: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8743: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8744: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8745: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8746: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8747: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8748: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8749: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8750: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8751: /* } */
8752: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8753: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8754: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8755: }
1.264 brouard 8756: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8757: fprintf(ficgp,"\n#\n");
8758: if(invalidvarcomb[k1]){
8759: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8760: continue;
8761: }
8762:
8763: /* k=2+nlstate*(2*cpt-2); */
8764: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8765: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8766: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8767: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8768: 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 8769: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8770: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8771: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8772: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8773: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8774: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8775:
1.238 brouard 8776: */
8777: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8778: 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 8779: /* 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 8780:
1.238 brouard 8781: }
1.261 brouard 8782: 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 8783: }
1.264 brouard 8784: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8785: } /* end nres */
1.337 brouard 8786: /* } /\* end kl 3eme *\/ */
1.126 brouard 8787:
1.223 brouard 8788: /* 4eme */
1.201 brouard 8789: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8790: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8791: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8792: k1=TKresult[nres];
1.338 brouard 8793: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8794: /* if(m != 1 && TKresult[nres]!= k1) */
8795: /* continue; */
1.238 brouard 8796: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8797: strcpy(gplotlabel,"(");
1.337 brouard 8798: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8799: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8800: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8801: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8802: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8803: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8804: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8805: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8806: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8807: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8808: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8809: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8810: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8811: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8812: /* } */
8813: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8814: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8815: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8816: }
1.264 brouard 8817: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8818: fprintf(ficgp,"\n#\n");
8819: if(invalidvarcomb[k1]){
8820: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8821: continue;
1.223 brouard 8822: }
1.238 brouard 8823:
1.241 brouard 8824: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8825: 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 8826: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8827: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8828: k=3;
8829: for (i=1; i<= nlstate ; i ++){
8830: if(i==1){
8831: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8832: }else{
8833: fprintf(ficgp,", '' ");
8834: }
8835: l=(nlstate+ndeath)*(i-1)+1;
8836: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8837: for (j=2; j<= nlstate+ndeath ; j ++)
8838: fprintf(ficgp,"+$%d",k+l+j-1);
8839: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8840: } /* nlstate */
1.264 brouard 8841: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8842: } /* end cpt state*/
8843: } /* end nres */
1.337 brouard 8844: /* } /\* end covariate k1 *\/ */
1.238 brouard 8845:
1.220 brouard 8846: /* 5eme */
1.201 brouard 8847: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8848: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8849: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8850: k1=TKresult[nres];
1.338 brouard 8851: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8852: /* if(m != 1 && TKresult[nres]!= k1) */
8853: /* continue; */
1.238 brouard 8854: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8855: strcpy(gplotlabel,"(");
1.238 brouard 8856: 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 8857: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8858: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8859: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8860: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8861: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8862: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8863: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8864: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8865: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8866: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8867: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8868: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8869: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8870: /* } */
8871: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8872: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8873: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8874: }
1.264 brouard 8875: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8876: fprintf(ficgp,"\n#\n");
8877: if(invalidvarcomb[k1]){
8878: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8879: continue;
8880: }
1.227 brouard 8881:
1.241 brouard 8882: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8883: 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 8884: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8885: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8886: k=3;
8887: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8888: if(j==1)
8889: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8890: else
8891: fprintf(ficgp,", '' ");
8892: l=(nlstate+ndeath)*(cpt-1) +j;
8893: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8894: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8895: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8896: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8897: } /* nlstate */
8898: fprintf(ficgp,", '' ");
8899: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8900: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8901: l=(nlstate+ndeath)*(cpt-1) +j;
8902: if(j < nlstate)
8903: fprintf(ficgp,"$%d +",k+l);
8904: else
8905: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8906: }
1.264 brouard 8907: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8908: } /* end cpt state*/
1.337 brouard 8909: /* } /\* end covariate *\/ */
1.238 brouard 8910: } /* end nres */
1.227 brouard 8911:
1.220 brouard 8912: /* 6eme */
1.202 brouard 8913: /* CV preval stable (period) for each covariate */
1.337 brouard 8914: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8915: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8916: k1=TKresult[nres];
1.338 brouard 8917: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8918: /* if(m != 1 && TKresult[nres]!= k1) */
8919: /* continue; */
1.255 brouard 8920: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8921: strcpy(gplotlabel,"(");
1.288 brouard 8922: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8923: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8924: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8925: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8926: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8927: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8928: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8929: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8930: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8931: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8932: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8933: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8934: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8935: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8936: /* } */
8937: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8938: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8939: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8940: }
1.264 brouard 8941: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8942: fprintf(ficgp,"\n#\n");
1.223 brouard 8943: if(invalidvarcomb[k1]){
1.227 brouard 8944: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8945: continue;
1.223 brouard 8946: }
1.227 brouard 8947:
1.241 brouard 8948: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8949: 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 8950: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8951: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8952: k=3; /* Offset */
1.255 brouard 8953: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8954: if(i==1)
8955: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8956: else
8957: fprintf(ficgp,", '' ");
1.255 brouard 8958: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8959: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8960: for (j=2; j<= nlstate ; j ++)
8961: fprintf(ficgp,"+$%d",k+l+j-1);
8962: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8963: } /* nlstate */
1.264 brouard 8964: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8965: } /* end cpt state*/
8966: } /* end covariate */
1.227 brouard 8967:
8968:
1.220 brouard 8969: /* 7eme */
1.296 brouard 8970: if(prevbcast == 1){
1.288 brouard 8971: /* CV backward prevalence for each covariate */
1.337 brouard 8972: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8973: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8974: k1=TKresult[nres];
1.338 brouard 8975: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8976: /* if(m != 1 && TKresult[nres]!= k1) */
8977: /* continue; */
1.268 brouard 8978: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8979: strcpy(gplotlabel,"(");
1.288 brouard 8980: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8981: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8982: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8983: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8984: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8985: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8986: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8987: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8988: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8989: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8990: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8991: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8992: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8993: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8994: /* } */
8995: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8996: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8997: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8998: }
1.264 brouard 8999: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9000: fprintf(ficgp,"\n#\n");
9001: if(invalidvarcomb[k1]){
9002: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9003: continue;
9004: }
9005:
1.241 brouard 9006: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 9007: 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 9008: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 9009: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 9010: k=3; /* Offset */
1.268 brouard 9011: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 9012: if(i==1)
9013: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
9014: else
9015: fprintf(ficgp,", '' ");
9016: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 9017: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 9018: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
9019: /* 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 9020: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 9021: /* for (j=2; j<= nlstate ; j ++) */
9022: /* fprintf(ficgp,"+$%d",k+l+j-1); */
9023: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 9024: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 9025: } /* nlstate */
1.264 brouard 9026: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 9027: } /* end cpt state*/
9028: } /* end covariate */
1.296 brouard 9029: } /* End if prevbcast */
1.218 brouard 9030:
1.223 brouard 9031: /* 8eme */
1.218 brouard 9032: if(prevfcast==1){
1.288 brouard 9033: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9034:
1.337 brouard 9035: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9036: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9037: k1=TKresult[nres];
1.338 brouard 9038: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9039: /* if(m != 1 && TKresult[nres]!= k1) */
9040: /* continue; */
1.211 brouard 9041: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9042: strcpy(gplotlabel,"(");
1.288 brouard 9043: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9044: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9045: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9046: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9047: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9048: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9049: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9050: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9051: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9052: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9053: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9054: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9055: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9056: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9057: /* } */
9058: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9059: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9060: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9061: }
1.264 brouard 9062: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9063: fprintf(ficgp,"\n#\n");
9064: if(invalidvarcomb[k1]){
9065: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9066: continue;
9067: }
9068:
9069: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9070: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9071: 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 9072: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9073: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9074:
9075: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9076: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9077: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9078: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9079: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9080: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9081: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9082: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9083: if(i==istart){
1.227 brouard 9084: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9085: }else{
9086: fprintf(ficgp,",\\\n '' ");
9087: }
9088: if(cptcoveff ==0){ /* No covariate */
9089: ioffset=2; /* Age is in 2 */
9090: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9091: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9092: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9093: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9094: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9095: if(i==nlstate+1){
1.270 brouard 9096: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9097: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9098: fprintf(ficgp,",\\\n '' ");
9099: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9100: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9101: offyear, \
1.268 brouard 9102: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9103: }else
1.227 brouard 9104: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9105: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9106: }else{ /* more than 2 covariates */
1.270 brouard 9107: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9108: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9109: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9110: iyearc=ioffset-1;
9111: iagec=ioffset;
1.227 brouard 9112: fprintf(ficgp," u %d:(",ioffset);
9113: kl=0;
9114: strcpy(gplotcondition,"(");
1.351 brouard 9115: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 9116: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 9117: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9118: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9119: lv=Tvresult[nres][k];
9120: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 9121: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9122: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9123: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9124: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 9125: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 9126: kl++;
1.351 brouard 9127: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9128: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 9129: kl++;
1.351 brouard 9130: if(k <cptcovs && cptcovs>1)
1.227 brouard 9131: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9132: }
9133: strcpy(gplotcondition+strlen(gplotcondition),")");
9134: /* 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 *\/ */
9135: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9136: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9137: /* '' 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*/
9138: if(i==nlstate+1){
1.270 brouard 9139: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9140: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9141: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9142: fprintf(ficgp," u %d:(",iagec);
9143: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9144: iyearc, iagec, offyear, \
9145: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9146: /* '' 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 9147: }else{
9148: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9149: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9150: }
9151: } /* end if covariate */
9152: } /* nlstate */
1.264 brouard 9153: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9154: } /* end cpt state*/
9155: } /* end covariate */
9156: } /* End if prevfcast */
1.227 brouard 9157:
1.296 brouard 9158: if(prevbcast==1){
1.268 brouard 9159: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9160:
1.337 brouard 9161: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9162: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9163: k1=TKresult[nres];
1.338 brouard 9164: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9165: /* if(m != 1 && TKresult[nres]!= k1) */
9166: /* continue; */
1.268 brouard 9167: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9168: strcpy(gplotlabel,"(");
9169: 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 9170: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9171: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9172: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9173: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9174: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9175: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9176: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9177: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9178: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9179: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9180: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9181: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9182: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9183: /* } */
9184: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9185: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9186: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9187: }
9188: strcpy(gplotlabel+strlen(gplotlabel),")");
9189: fprintf(ficgp,"\n#\n");
9190: if(invalidvarcomb[k1]){
9191: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9192: continue;
9193: }
9194:
9195: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9196: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9197: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9198: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9199: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9200:
9201: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9202: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9203: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9204: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9205: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9206: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9207: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9208: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9209: if(i==istart){
9210: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9211: }else{
9212: fprintf(ficgp,",\\\n '' ");
9213: }
1.351 brouard 9214: /* if(cptcoveff ==0){ /\* No covariate *\/ */
9215: if(cptcovs ==0){ /* No covariate */
1.268 brouard 9216: ioffset=2; /* Age is in 2 */
9217: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9218: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9219: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9220: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9221: fprintf(ficgp," u %d:(", ioffset);
9222: if(i==nlstate+1){
1.270 brouard 9223: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9224: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9225: fprintf(ficgp,",\\\n '' ");
9226: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9227: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9228: offbyear, \
9229: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9230: }else
9231: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9232: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9233: }else{ /* more than 2 covariates */
1.270 brouard 9234: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9235: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9236: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9237: iyearc=ioffset-1;
9238: iagec=ioffset;
1.268 brouard 9239: fprintf(ficgp," u %d:(",ioffset);
9240: kl=0;
9241: strcpy(gplotcondition,"(");
1.337 brouard 9242: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9243: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9244: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9245: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9246: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9247: lv=Tvresult[nres][k];
9248: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9249: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9250: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9251: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9252: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9253: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9254: kl++;
9255: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9256: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9257: kl++;
1.338 brouard 9258: if(k <cptcovs && cptcovs>1)
1.337 brouard 9259: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9260: }
1.268 brouard 9261: }
9262: strcpy(gplotcondition+strlen(gplotcondition),")");
9263: /* 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 *\/ */
9264: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9265: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9266: /* '' 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*/
9267: if(i==nlstate+1){
1.270 brouard 9268: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9269: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9270: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9271: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9272: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9273: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9274: iyearc,iagec,offbyear, \
9275: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9276: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9277: }else{
9278: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9279: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9280: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9281: }
9282: } /* end if covariate */
9283: } /* nlstate */
9284: fprintf(ficgp,"\nset out; unset label;\n");
9285: } /* end cpt state*/
9286: } /* end covariate */
1.296 brouard 9287: } /* End if prevbcast */
1.268 brouard 9288:
1.227 brouard 9289:
1.238 brouard 9290: /* 9eme writing MLE parameters */
9291: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9292: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9293: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9294: for(k=1; k <=(nlstate+ndeath); k++){
9295: if (k != i) {
1.227 brouard 9296: fprintf(ficgp,"# current state %d\n",k);
9297: for(j=1; j <=ncovmodel; j++){
9298: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9299: jk++;
9300: }
9301: fprintf(ficgp,"\n");
1.126 brouard 9302: }
9303: }
1.223 brouard 9304: }
1.187 brouard 9305: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9306:
1.145 brouard 9307: /*goto avoid;*/
1.238 brouard 9308: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9309: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9310: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9311: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9312: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9313: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9314: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9315: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9316: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9317: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9318: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9319: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9320: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9321: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9322: fprintf(ficgp,"#\n");
1.223 brouard 9323: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9324: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9325: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9326: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 9327: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
9328: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 9329: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9330: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9331: /* k1=nres; */
1.338 brouard 9332: k1=TKresult[nres];
9333: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9334: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9335: strcpy(gplotlabel,"(");
1.276 brouard 9336: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9337: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9338: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9339: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9340: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9341: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9342: }
9343: /* if(m != 1 && TKresult[nres]!= k1) */
9344: /* continue; */
9345: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9346: /* strcpy(gplotlabel,"("); */
9347: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9348: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9349: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9350: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9351: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9352: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9353: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9354: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9355: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9356: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9357: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9358: /* } */
9359: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9360: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9361: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9362: /* } */
1.264 brouard 9363: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9364: fprintf(ficgp,"\n#\n");
1.264 brouard 9365: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9366: fprintf(ficgp,"\nset key outside ");
9367: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9368: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9369: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9370: if (ng==1){
9371: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9372: fprintf(ficgp,"\nunset log y");
9373: }else if (ng==2){
9374: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9375: fprintf(ficgp,"\nset log y");
9376: }else if (ng==3){
9377: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9378: fprintf(ficgp,"\nset log y");
9379: }else
9380: fprintf(ficgp,"\nunset title ");
9381: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9382: i=1;
9383: for(k2=1; k2<=nlstate; k2++) {
9384: k3=i;
9385: for(k=1; k<=(nlstate+ndeath); k++) {
9386: if (k != k2){
9387: switch( ng) {
9388: case 1:
9389: if(nagesqr==0)
9390: fprintf(ficgp," p%d+p%d*x",i,i+1);
9391: else /* nagesqr =1 */
9392: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9393: break;
9394: case 2: /* ng=2 */
9395: if(nagesqr==0)
9396: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9397: else /* nagesqr =1 */
9398: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9399: break;
9400: case 3:
9401: if(nagesqr==0)
9402: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9403: else /* nagesqr =1 */
9404: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9405: break;
9406: }
9407: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9408: ijp=1; /* product no age */
9409: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9410: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9411: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9412: switch(Typevar[j]){
9413: case 1:
9414: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9415: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9416: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9417: if(DummyV[j]==0){/* Bug valgrind */
9418: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9419: }else{ /* quantitative */
9420: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9421: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9422: }
9423: ij++;
1.268 brouard 9424: }
1.237 brouard 9425: }
1.329 brouard 9426: }
9427: break;
9428: case 2:
9429: if(cptcovprod >0){
9430: if(j==Tprod[ijp]) { /* */
9431: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9432: if(ijp <=cptcovprod) { /* Product */
9433: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9434: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9435: /* 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)]); */
9436: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9437: }else{ /* Vn is dummy and Vm is quanti */
9438: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9439: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9440: }
9441: }else{ /* Vn*Vm Vn is quanti */
9442: if(DummyV[Tvard[ijp][2]]==0){
9443: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9444: }else{ /* Both quanti */
9445: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9446: }
1.268 brouard 9447: }
1.329 brouard 9448: ijp++;
1.237 brouard 9449: }
1.329 brouard 9450: } /* end Tprod */
9451: }
9452: break;
1.349 brouard 9453: case 3:
9454: if(cptcovdageprod >0){
9455: /* if(j==Tprod[ijp]) { */ /* not necessary */
9456: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 9457: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
9458: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9459: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9460: /* 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)]); */
9461: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9462: }else{ /* Vn is dummy and Vm is quanti */
9463: /* 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 9464: 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 9465: }
1.350 brouard 9466: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 9467: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 9468: 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 9469: }else{ /* Both quanti */
1.350 brouard 9470: 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 9471: }
9472: }
9473: ijp++;
9474: }
9475: /* } */ /* end Tprod */
9476: }
9477: break;
1.329 brouard 9478: case 0:
9479: /* simple covariate */
1.264 brouard 9480: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9481: if(Dummy[j]==0){
9482: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9483: }else{ /* quantitative */
9484: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9485: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9486: }
1.329 brouard 9487: /* end simple */
9488: break;
9489: default:
9490: break;
9491: } /* end switch */
1.237 brouard 9492: } /* end j */
1.329 brouard 9493: }else{ /* k=k2 */
9494: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9495: fprintf(ficgp," (1.");i=i-ncovmodel;
9496: }else
9497: i=i-ncovmodel;
1.223 brouard 9498: }
1.227 brouard 9499:
1.223 brouard 9500: if(ng != 1){
9501: fprintf(ficgp,")/(1");
1.227 brouard 9502:
1.264 brouard 9503: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9504: if(nagesqr==0)
1.264 brouard 9505: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9506: else /* nagesqr =1 */
1.264 brouard 9507: 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 9508:
1.223 brouard 9509: ij=1;
1.329 brouard 9510: ijp=1;
9511: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9512: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9513: switch(Typevar[j]){
9514: case 1:
9515: if(cptcovage >0){
9516: if(j==Tage[ij]) { /* Bug valgrind */
9517: if(ij <=cptcovage) { /* Bug valgrind */
9518: if(DummyV[j]==0){/* Bug valgrind */
9519: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9520: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9521: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9522: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9523: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9524: }else{ /* quantitative */
9525: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9526: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9527: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9528: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9529: }
9530: ij++;
9531: }
9532: }
9533: }
9534: break;
9535: case 2:
9536: if(cptcovprod >0){
9537: if(j==Tprod[ijp]) { /* */
9538: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9539: if(ijp <=cptcovprod) { /* Product */
9540: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9541: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9542: /* 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)]); */
9543: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9544: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9545: }else{ /* Vn is dummy and Vm is quanti */
9546: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9547: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9548: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9549: }
9550: }else{ /* Vn*Vm Vn is quanti */
9551: if(DummyV[Tvard[ijp][2]]==0){
9552: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9553: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9554: }else{ /* Both quanti */
9555: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9556: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9557: }
9558: }
9559: ijp++;
9560: }
9561: } /* end Tprod */
9562: } /* end if */
9563: break;
1.349 brouard 9564: case 3:
9565: if(cptcovdageprod >0){
9566: /* if(j==Tprod[ijp]) { /\* *\/ */
9567: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9568: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 9569: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9570: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9571: /* 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 9572: 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 9573: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9574: }else{ /* Vn is dummy and Vm is quanti */
9575: /* 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 9576: 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 9577: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9578: }
9579: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 9580: if(DummyV[Tvardk[ijp][2]]==0){
9581: 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 9582: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9583: }else{ /* Both quanti */
1.350 brouard 9584: 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 9585: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9586: }
9587: }
9588: ijp++;
9589: }
9590: /* } /\* end Tprod *\/ */
9591: } /* end if */
9592: break;
1.329 brouard 9593: case 0:
9594: /* simple covariate */
9595: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9596: if(Dummy[j]==0){
9597: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9598: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9599: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9600: }else{ /* quantitative */
9601: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9602: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9603: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9604: }
9605: /* end simple */
9606: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9607: break;
9608: default:
9609: break;
9610: } /* end switch */
1.223 brouard 9611: }
9612: fprintf(ficgp,")");
9613: }
9614: fprintf(ficgp,")");
9615: if(ng ==2)
1.276 brouard 9616: 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 9617: else /* ng= 3 */
1.276 brouard 9618: 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 9619: }else{ /* end ng <> 1 */
1.223 brouard 9620: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9621: 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 9622: }
9623: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9624: fprintf(ficgp,",");
9625: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9626: fprintf(ficgp,",");
9627: i=i+ncovmodel;
9628: } /* end k */
9629: } /* end k2 */
1.276 brouard 9630: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9631: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9632: } /* end resultline */
1.223 brouard 9633: } /* end ng */
9634: /* avoid: */
9635: fflush(ficgp);
1.126 brouard 9636: } /* end gnuplot */
9637:
9638:
9639: /*************** Moving average **************/
1.219 brouard 9640: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9641: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9642:
1.222 brouard 9643: int i, cpt, cptcod;
9644: int modcovmax =1;
9645: int mobilavrange, mob;
9646: int iage=0;
1.288 brouard 9647: int firstA1=0, firstA2=0;
1.222 brouard 9648:
1.266 brouard 9649: double sum=0., sumr=0.;
1.222 brouard 9650: double age;
1.266 brouard 9651: double *sumnewp, *sumnewm, *sumnewmr;
9652: double *agemingood, *agemaxgood;
9653: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9654:
9655:
1.278 brouard 9656: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9657: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9658:
9659: sumnewp = vector(1,ncovcombmax);
9660: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9661: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9662: agemingood = vector(1,ncovcombmax);
1.266 brouard 9663: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9664: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9665: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9666:
9667: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9668: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9669: sumnewp[cptcod]=0.;
1.266 brouard 9670: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9671: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9672: }
9673: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9674:
1.266 brouard 9675: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9676: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9677: else mobilavrange=mobilav;
9678: for (age=bage; age<=fage; age++)
9679: for (i=1; i<=nlstate;i++)
9680: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9681: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9682: /* We keep the original values on the extreme ages bage, fage and for
9683: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9684: we use a 5 terms etc. until the borders are no more concerned.
9685: */
9686: for (mob=3;mob <=mobilavrange;mob=mob+2){
9687: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9688: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9689: sumnewm[cptcod]=0.;
9690: for (i=1; i<=nlstate;i++){
1.222 brouard 9691: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9692: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9693: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9694: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9695: }
9696: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9697: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9698: } /* end i */
9699: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9700: } /* end cptcod */
1.222 brouard 9701: }/* end age */
9702: }/* end mob */
1.266 brouard 9703: }else{
9704: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9705: return -1;
1.266 brouard 9706: }
9707:
9708: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9709: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9710: if(invalidvarcomb[cptcod]){
9711: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9712: continue;
9713: }
1.219 brouard 9714:
1.266 brouard 9715: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9716: sumnewm[cptcod]=0.;
9717: sumnewmr[cptcod]=0.;
9718: for (i=1; i<=nlstate;i++){
9719: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9720: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9721: }
9722: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9723: agemingoodr[cptcod]=age;
9724: }
9725: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9726: agemingood[cptcod]=age;
9727: }
9728: } /* age */
9729: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9730: sumnewm[cptcod]=0.;
1.266 brouard 9731: sumnewmr[cptcod]=0.;
1.222 brouard 9732: for (i=1; i<=nlstate;i++){
9733: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9734: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9735: }
9736: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9737: agemaxgoodr[cptcod]=age;
1.222 brouard 9738: }
9739: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9740: agemaxgood[cptcod]=age;
9741: }
9742: } /* age */
9743: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9744: /* but they will change */
1.288 brouard 9745: firstA1=0;firstA2=0;
1.266 brouard 9746: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9747: sumnewm[cptcod]=0.;
9748: sumnewmr[cptcod]=0.;
9749: for (i=1; i<=nlstate;i++){
9750: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9751: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9752: }
9753: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9754: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9755: agemaxgoodr[cptcod]=age; /* age min */
9756: for (i=1; i<=nlstate;i++)
9757: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9758: }else{ /* bad we change the value with the values of good ages */
9759: for (i=1; i<=nlstate;i++){
9760: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9761: } /* i */
9762: } /* end bad */
9763: }else{
9764: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9765: agemaxgood[cptcod]=age;
9766: }else{ /* bad we change the value with the values of good ages */
9767: for (i=1; i<=nlstate;i++){
9768: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9769: } /* i */
9770: } /* end bad */
9771: }/* end else */
9772: sum=0.;sumr=0.;
9773: for (i=1; i<=nlstate;i++){
9774: sum+=mobaverage[(int)age][i][cptcod];
9775: sumr+=probs[(int)age][i][cptcod];
9776: }
9777: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9778: if(!firstA1){
9779: firstA1=1;
9780: 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);
9781: }
9782: 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 9783: } /* end bad */
9784: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9785: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9786: if(!firstA2){
9787: firstA2=1;
9788: 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);
9789: }
9790: 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 9791: } /* end bad */
9792: }/* age */
1.266 brouard 9793:
9794: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9795: sumnewm[cptcod]=0.;
1.266 brouard 9796: sumnewmr[cptcod]=0.;
1.222 brouard 9797: for (i=1; i<=nlstate;i++){
9798: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9799: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9800: }
9801: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9802: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9803: agemingoodr[cptcod]=age;
9804: for (i=1; i<=nlstate;i++)
9805: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9806: }else{ /* bad we change the value with the values of good ages */
9807: for (i=1; i<=nlstate;i++){
9808: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9809: } /* i */
9810: } /* end bad */
9811: }else{
9812: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9813: agemingood[cptcod]=age;
9814: }else{ /* bad */
9815: for (i=1; i<=nlstate;i++){
9816: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9817: } /* i */
9818: } /* end bad */
9819: }/* end else */
9820: sum=0.;sumr=0.;
9821: for (i=1; i<=nlstate;i++){
9822: sum+=mobaverage[(int)age][i][cptcod];
9823: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9824: }
1.266 brouard 9825: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9826: 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 9827: } /* end bad */
9828: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9829: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9830: 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 9831: } /* end bad */
9832: }/* age */
1.266 brouard 9833:
1.222 brouard 9834:
9835: for (age=bage; age<=fage; age++){
1.235 brouard 9836: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9837: sumnewp[cptcod]=0.;
9838: sumnewm[cptcod]=0.;
9839: for (i=1; i<=nlstate;i++){
9840: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9841: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9842: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9843: }
9844: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9845: }
9846: /* printf("\n"); */
9847: /* } */
1.266 brouard 9848:
1.222 brouard 9849: /* brutal averaging */
1.266 brouard 9850: /* for (i=1; i<=nlstate;i++){ */
9851: /* for (age=1; age<=bage; age++){ */
9852: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9853: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9854: /* } */
9855: /* for (age=fage; age<=AGESUP; age++){ */
9856: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9857: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9858: /* } */
9859: /* } /\* end i status *\/ */
9860: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9861: /* for (age=1; age<=AGESUP; age++){ */
9862: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9863: /* mobaverage[(int)age][i][cptcod]=0.; */
9864: /* } */
9865: /* } */
1.222 brouard 9866: }/* end cptcod */
1.266 brouard 9867: free_vector(agemaxgoodr,1, ncovcombmax);
9868: free_vector(agemaxgood,1, ncovcombmax);
9869: free_vector(agemingood,1, ncovcombmax);
9870: free_vector(agemingoodr,1, ncovcombmax);
9871: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9872: free_vector(sumnewm,1, ncovcombmax);
9873: free_vector(sumnewp,1, ncovcombmax);
9874: return 0;
9875: }/* End movingaverage */
1.218 brouard 9876:
1.126 brouard 9877:
1.296 brouard 9878:
1.126 brouard 9879: /************** Forecasting ******************/
1.296 brouard 9880: /* 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)*/
9881: 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){
9882: /* dateintemean, mean date of interviews
9883: dateprojd, year, month, day of starting projection
9884: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9885: agemin, agemax range of age
9886: dateprev1 dateprev2 range of dates during which prevalence is computed
9887: */
1.296 brouard 9888: /* double anprojd, mprojd, jprojd; */
9889: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9890: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9891: double agec; /* generic age */
1.296 brouard 9892: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9893: double *popeffectif,*popcount;
9894: double ***p3mat;
1.218 brouard 9895: /* double ***mobaverage; */
1.126 brouard 9896: char fileresf[FILENAMELENGTH];
9897:
9898: agelim=AGESUP;
1.211 brouard 9899: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9900: in each health status at the date of interview (if between dateprev1 and dateprev2).
9901: We still use firstpass and lastpass as another selection.
9902: */
1.214 brouard 9903: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9904: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9905:
1.201 brouard 9906: strcpy(fileresf,"F_");
9907: strcat(fileresf,fileresu);
1.126 brouard 9908: if((ficresf=fopen(fileresf,"w"))==NULL) {
9909: printf("Problem with forecast resultfile: %s\n", fileresf);
9910: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9911: }
1.235 brouard 9912: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9913: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9914:
1.225 brouard 9915: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9916:
9917:
9918: stepsize=(int) (stepm+YEARM-1)/YEARM;
9919: if (stepm<=12) stepsize=1;
9920: if(estepm < stepm){
9921: printf ("Problem %d lower than %d\n",estepm, stepm);
9922: }
1.270 brouard 9923: else{
9924: hstepm=estepm;
9925: }
9926: if(estepm > stepm){ /* Yes every two year */
9927: stepsize=2;
9928: }
1.296 brouard 9929: hstepm=hstepm/stepm;
1.126 brouard 9930:
1.296 brouard 9931:
9932: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9933: /* fractional in yp1 *\/ */
9934: /* aintmean=yp; */
9935: /* yp2=modf((yp1*12),&yp); */
9936: /* mintmean=yp; */
9937: /* yp1=modf((yp2*30.5),&yp); */
9938: /* jintmean=yp; */
9939: /* if(jintmean==0) jintmean=1; */
9940: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9941:
1.296 brouard 9942:
9943: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9944: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9945: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 9946: /* i1=pow(2,cptcoveff); */
9947: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 9948:
1.296 brouard 9949: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9950:
9951: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9952:
1.126 brouard 9953: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 9954: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9955: k=TKresult[nres];
9956: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
9957: /* 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) *\/ */
9958: /* if(i1 != 1 && TKresult[nres]!= k) */
9959: /* continue; */
9960: /* if(invalidvarcomb[k]){ */
9961: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
9962: /* continue; */
9963: /* } */
1.227 brouard 9964: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 9965: for(j=1;j<=cptcovs;j++){
9966: /* for(j=1;j<=cptcoveff;j++) { */
9967: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
9968: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9969: /* } */
9970: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9971: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9972: /* } */
9973: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 9974: }
1.351 brouard 9975:
1.227 brouard 9976: fprintf(ficresf," yearproj age");
9977: for(j=1; j<=nlstate+ndeath;j++){
9978: for(i=1; i<=nlstate;i++)
9979: fprintf(ficresf," p%d%d",i,j);
9980: fprintf(ficresf," wp.%d",j);
9981: }
1.296 brouard 9982: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9983: fprintf(ficresf,"\n");
1.296 brouard 9984: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9985: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9986: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9987: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9988: nhstepm = nhstepm/hstepm;
9989: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9990: oldm=oldms;savm=savms;
1.268 brouard 9991: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9992: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9993: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9994: for (h=0; h<=nhstepm; h++){
9995: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9996: break;
9997: }
9998: }
9999: fprintf(ficresf,"\n");
1.351 brouard 10000: /* for(j=1;j<=cptcoveff;j++) */
10001: for(j=1;j<=cptcovs;j++)
10002: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 10003: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 10004: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 10005: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 10006:
10007: for(j=1; j<=nlstate+ndeath;j++) {
10008: ppij=0.;
10009: for(i=1; i<=nlstate;i++) {
1.278 brouard 10010: if (mobilav>=1)
10011: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
10012: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
10013: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
10014: }
1.268 brouard 10015: fprintf(ficresf," %.3f", p3mat[i][j][h]);
10016: } /* end i */
10017: fprintf(ficresf," %.3f", ppij);
10018: }/* end j */
1.227 brouard 10019: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10020: } /* end agec */
1.266 brouard 10021: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
10022: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 10023: } /* end yearp */
10024: } /* end k */
1.219 brouard 10025:
1.126 brouard 10026: fclose(ficresf);
1.215 brouard 10027: printf("End of Computing forecasting \n");
10028: fprintf(ficlog,"End of Computing forecasting\n");
10029:
1.126 brouard 10030: }
10031:
1.269 brouard 10032: /************** Back Forecasting ******************/
1.296 brouard 10033: /* 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){ */
10034: 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){
10035: /* back1, year, month, day of starting backprojection
1.267 brouard 10036: agemin, agemax range of age
10037: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 10038: anback2 year of end of backprojection (same day and month as back1).
10039: prevacurrent and prev are prevalences.
1.267 brouard 10040: */
10041: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
10042: double agec; /* generic age */
1.302 brouard 10043: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10044: double *popeffectif,*popcount;
10045: double ***p3mat;
10046: /* double ***mobaverage; */
10047: char fileresfb[FILENAMELENGTH];
10048:
1.268 brouard 10049: agelim=AGEINF;
1.267 brouard 10050: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10051: in each health status at the date of interview (if between dateprev1 and dateprev2).
10052: We still use firstpass and lastpass as another selection.
10053: */
10054: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10055: /* firstpass, lastpass, stepm, weightopt, model); */
10056:
10057: /*Do we need to compute prevalence again?*/
10058:
10059: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10060:
10061: strcpy(fileresfb,"FB_");
10062: strcat(fileresfb,fileresu);
10063: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10064: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10065: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10066: }
10067: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10068: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10069:
10070: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10071:
10072:
10073: stepsize=(int) (stepm+YEARM-1)/YEARM;
10074: if (stepm<=12) stepsize=1;
10075: if(estepm < stepm){
10076: printf ("Problem %d lower than %d\n",estepm, stepm);
10077: }
1.270 brouard 10078: else{
10079: hstepm=estepm;
10080: }
10081: if(estepm >= stepm){ /* Yes every two year */
10082: stepsize=2;
10083: }
1.267 brouard 10084:
10085: hstepm=hstepm/stepm;
1.296 brouard 10086: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10087: /* fractional in yp1 *\/ */
10088: /* aintmean=yp; */
10089: /* yp2=modf((yp1*12),&yp); */
10090: /* mintmean=yp; */
10091: /* yp1=modf((yp2*30.5),&yp); */
10092: /* jintmean=yp; */
10093: /* if(jintmean==0) jintmean=1; */
10094: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10095:
1.351 brouard 10096: /* i1=pow(2,cptcoveff); */
10097: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 10098:
1.296 brouard 10099: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10100: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10101:
10102: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10103:
1.351 brouard 10104: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10105: k=TKresult[nres];
10106: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
10107: /* for(k=1; k<=i1;k++){ */
10108: /* if(i1 != 1 && TKresult[nres]!= k) */
10109: /* continue; */
10110: /* if(invalidvarcomb[k]){ */
10111: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
10112: /* continue; */
10113: /* } */
1.268 brouard 10114: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 10115: for(j=1;j<=cptcovs;j++){
10116: /* for(j=1;j<=cptcoveff;j++) { */
10117: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10118: /* } */
10119: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 10120: }
1.351 brouard 10121: /* fprintf(ficrespij,"******\n"); */
10122: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10123: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10124: /* } */
1.267 brouard 10125: fprintf(ficresfb," yearbproj age");
10126: for(j=1; j<=nlstate+ndeath;j++){
10127: for(i=1; i<=nlstate;i++)
1.268 brouard 10128: fprintf(ficresfb," b%d%d",i,j);
10129: fprintf(ficresfb," b.%d",j);
1.267 brouard 10130: }
1.296 brouard 10131: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10132: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10133: fprintf(ficresfb,"\n");
1.296 brouard 10134: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10135: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10136: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10137: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10138: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10139: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10140: nhstepm = nhstepm/hstepm;
10141: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10142: oldm=oldms;savm=savms;
1.268 brouard 10143: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10144: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10145: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10146: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10147: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10148: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10149: for (h=0; h<=nhstepm; h++){
1.268 brouard 10150: if (h*hstepm/YEARM*stepm ==-yearp) {
10151: break;
10152: }
10153: }
10154: fprintf(ficresfb,"\n");
1.351 brouard 10155: /* for(j=1;j<=cptcoveff;j++) */
10156: for(j=1;j<=cptcovs;j++)
10157: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10158: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 10159: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10160: for(i=1; i<=nlstate+ndeath;i++) {
10161: ppij=0.;ppi=0.;
10162: for(j=1; j<=nlstate;j++) {
10163: /* if (mobilav==1) */
1.269 brouard 10164: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10165: ppi=ppi+prevacurrent[(int)agec][j][k];
10166: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10167: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10168: /* else { */
10169: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10170: /* } */
1.268 brouard 10171: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10172: } /* end j */
10173: if(ppi <0.99){
10174: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10175: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10176: }
10177: fprintf(ficresfb," %.3f", ppij);
10178: }/* end j */
1.267 brouard 10179: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10180: } /* end agec */
10181: } /* end yearp */
10182: } /* end k */
1.217 brouard 10183:
1.267 brouard 10184: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10185:
1.267 brouard 10186: fclose(ficresfb);
10187: printf("End of Computing Back forecasting \n");
10188: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10189:
1.267 brouard 10190: }
1.217 brouard 10191:
1.269 brouard 10192: /* Variance of prevalence limit: varprlim */
10193: 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 10194: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10195:
10196: char fileresvpl[FILENAMELENGTH];
10197: FILE *ficresvpl;
10198: double **oldm, **savm;
10199: double **varpl; /* Variances of prevalence limits by age */
10200: int i1, k, nres, j ;
10201:
10202: strcpy(fileresvpl,"VPL_");
10203: strcat(fileresvpl,fileresu);
10204: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10205: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10206: exit(0);
10207: }
1.288 brouard 10208: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10209: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10210:
10211: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10212: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10213:
10214: i1=pow(2,cptcoveff);
10215: if (cptcovn < 1){i1=1;}
10216:
1.337 brouard 10217: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10218: k=TKresult[nres];
1.338 brouard 10219: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10220: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10221: if(i1 != 1 && TKresult[nres]!= k)
10222: continue;
10223: fprintf(ficresvpl,"\n#****** ");
10224: printf("\n#****** ");
10225: fprintf(ficlog,"\n#****** ");
1.337 brouard 10226: for(j=1;j<=cptcovs;j++) {
10227: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10228: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10229: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10230: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10231: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10232: }
1.337 brouard 10233: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10234: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10235: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10236: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10237: /* } */
1.269 brouard 10238: fprintf(ficresvpl,"******\n");
10239: printf("******\n");
10240: fprintf(ficlog,"******\n");
10241:
10242: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10243: oldm=oldms;savm=savms;
10244: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10245: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10246: /*}*/
10247: }
10248:
10249: fclose(ficresvpl);
1.288 brouard 10250: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10251: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10252:
10253: }
10254: /* Variance of back prevalence: varbprlim */
10255: 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){
10256: /*------- Variance of back (stable) prevalence------*/
10257:
10258: char fileresvbl[FILENAMELENGTH];
10259: FILE *ficresvbl;
10260:
10261: double **oldm, **savm;
10262: double **varbpl; /* Variances of back prevalence limits by age */
10263: int i1, k, nres, j ;
10264:
10265: strcpy(fileresvbl,"VBL_");
10266: strcat(fileresvbl,fileresu);
10267: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10268: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10269: exit(0);
10270: }
10271: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10272: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10273:
10274:
10275: i1=pow(2,cptcoveff);
10276: if (cptcovn < 1){i1=1;}
10277:
1.337 brouard 10278: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10279: k=TKresult[nres];
1.338 brouard 10280: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10281: /* for(k=1; k<=i1;k++){ */
10282: /* if(i1 != 1 && TKresult[nres]!= k) */
10283: /* continue; */
1.269 brouard 10284: fprintf(ficresvbl,"\n#****** ");
10285: printf("\n#****** ");
10286: fprintf(ficlog,"\n#****** ");
1.337 brouard 10287: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10288: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10289: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10290: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10291: /* for(j=1;j<=cptcoveff;j++) { */
10292: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10293: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10294: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10295: /* } */
10296: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10297: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10298: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10299: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10300: }
10301: fprintf(ficresvbl,"******\n");
10302: printf("******\n");
10303: fprintf(ficlog,"******\n");
10304:
10305: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10306: oldm=oldms;savm=savms;
10307:
10308: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10309: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10310: /*}*/
10311: }
10312:
10313: fclose(ficresvbl);
10314: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10315: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10316:
10317: } /* End of varbprlim */
10318:
1.126 brouard 10319: /************** Forecasting *****not tested NB*************/
1.227 brouard 10320: /* 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 10321:
1.227 brouard 10322: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10323: /* int *popage; */
10324: /* double calagedatem, agelim, kk1, kk2; */
10325: /* double *popeffectif,*popcount; */
10326: /* double ***p3mat,***tabpop,***tabpopprev; */
10327: /* /\* double ***mobaverage; *\/ */
10328: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10329:
1.227 brouard 10330: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10331: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10332: /* agelim=AGESUP; */
10333: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10334:
1.227 brouard 10335: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10336:
10337:
1.227 brouard 10338: /* strcpy(filerespop,"POP_"); */
10339: /* strcat(filerespop,fileresu); */
10340: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10341: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10342: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10343: /* } */
10344: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10345: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10346:
1.227 brouard 10347: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10348:
1.227 brouard 10349: /* /\* if (mobilav!=0) { *\/ */
10350: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10351: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10352: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10353: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10354: /* /\* } *\/ */
10355: /* /\* } *\/ */
1.126 brouard 10356:
1.227 brouard 10357: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10358: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10359:
1.227 brouard 10360: /* agelim=AGESUP; */
1.126 brouard 10361:
1.227 brouard 10362: /* hstepm=1; */
10363: /* hstepm=hstepm/stepm; */
1.218 brouard 10364:
1.227 brouard 10365: /* if (popforecast==1) { */
10366: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10367: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10368: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10369: /* } */
10370: /* popage=ivector(0,AGESUP); */
10371: /* popeffectif=vector(0,AGESUP); */
10372: /* popcount=vector(0,AGESUP); */
1.126 brouard 10373:
1.227 brouard 10374: /* i=1; */
10375: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10376:
1.227 brouard 10377: /* imx=i; */
10378: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10379: /* } */
1.218 brouard 10380:
1.227 brouard 10381: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10382: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10383: /* k=k+1; */
10384: /* fprintf(ficrespop,"\n#******"); */
10385: /* for(j=1;j<=cptcoveff;j++) { */
10386: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10387: /* } */
10388: /* fprintf(ficrespop,"******\n"); */
10389: /* fprintf(ficrespop,"# Age"); */
10390: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10391: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10392:
1.227 brouard 10393: /* for (cpt=0; cpt<=0;cpt++) { */
10394: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10395:
1.227 brouard 10396: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10397: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10398: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10399:
1.227 brouard 10400: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10401: /* oldm=oldms;savm=savms; */
10402: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10403:
1.227 brouard 10404: /* for (h=0; h<=nhstepm; h++){ */
10405: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10406: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10407: /* } */
10408: /* for(j=1; j<=nlstate+ndeath;j++) { */
10409: /* kk1=0.;kk2=0; */
10410: /* for(i=1; i<=nlstate;i++) { */
10411: /* if (mobilav==1) */
10412: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10413: /* else { */
10414: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10415: /* } */
10416: /* } */
10417: /* if (h==(int)(calagedatem+12*cpt)){ */
10418: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10419: /* /\*fprintf(ficrespop," %.3f", kk1); */
10420: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10421: /* } */
10422: /* } */
10423: /* for(i=1; i<=nlstate;i++){ */
10424: /* kk1=0.; */
10425: /* for(j=1; j<=nlstate;j++){ */
10426: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10427: /* } */
10428: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10429: /* } */
1.218 brouard 10430:
1.227 brouard 10431: /* if (h==(int)(calagedatem+12*cpt)) */
10432: /* for(j=1; j<=nlstate;j++) */
10433: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10434: /* } */
10435: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10436: /* } */
10437: /* } */
1.218 brouard 10438:
1.227 brouard 10439: /* /\******\/ */
1.218 brouard 10440:
1.227 brouard 10441: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10442: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10443: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10444: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10445: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10446:
1.227 brouard 10447: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10448: /* oldm=oldms;savm=savms; */
10449: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10450: /* for (h=0; h<=nhstepm; h++){ */
10451: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10452: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10453: /* } */
10454: /* for(j=1; j<=nlstate+ndeath;j++) { */
10455: /* kk1=0.;kk2=0; */
10456: /* for(i=1; i<=nlstate;i++) { */
10457: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10458: /* } */
10459: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10460: /* } */
10461: /* } */
10462: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10463: /* } */
10464: /* } */
10465: /* } */
10466: /* } */
1.218 brouard 10467:
1.227 brouard 10468: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10469:
1.227 brouard 10470: /* if (popforecast==1) { */
10471: /* free_ivector(popage,0,AGESUP); */
10472: /* free_vector(popeffectif,0,AGESUP); */
10473: /* free_vector(popcount,0,AGESUP); */
10474: /* } */
10475: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10476: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10477: /* fclose(ficrespop); */
10478: /* } /\* End of popforecast *\/ */
1.218 brouard 10479:
1.126 brouard 10480: int fileappend(FILE *fichier, char *optionfich)
10481: {
10482: if((fichier=fopen(optionfich,"a"))==NULL) {
10483: printf("Problem with file: %s\n", optionfich);
10484: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10485: return (0);
10486: }
10487: fflush(fichier);
10488: return (1);
10489: }
10490:
10491:
10492: /**************** function prwizard **********************/
10493: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10494: {
10495:
10496: /* Wizard to print covariance matrix template */
10497:
1.164 brouard 10498: char ca[32], cb[32];
10499: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10500: int numlinepar;
10501:
10502: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10503: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10504: for(i=1; i <=nlstate; i++){
10505: jj=0;
10506: for(j=1; j <=nlstate+ndeath; j++){
10507: if(j==i) continue;
10508: jj++;
10509: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10510: printf("%1d%1d",i,j);
10511: fprintf(ficparo,"%1d%1d",i,j);
10512: for(k=1; k<=ncovmodel;k++){
10513: /* printf(" %lf",param[i][j][k]); */
10514: /* fprintf(ficparo," %lf",param[i][j][k]); */
10515: printf(" 0.");
10516: fprintf(ficparo," 0.");
10517: }
10518: printf("\n");
10519: fprintf(ficparo,"\n");
10520: }
10521: }
10522: printf("# Scales (for hessian or gradient estimation)\n");
10523: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10524: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10525: for(i=1; i <=nlstate; i++){
10526: jj=0;
10527: for(j=1; j <=nlstate+ndeath; j++){
10528: if(j==i) continue;
10529: jj++;
10530: fprintf(ficparo,"%1d%1d",i,j);
10531: printf("%1d%1d",i,j);
10532: fflush(stdout);
10533: for(k=1; k<=ncovmodel;k++){
10534: /* printf(" %le",delti3[i][j][k]); */
10535: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10536: printf(" 0.");
10537: fprintf(ficparo," 0.");
10538: }
10539: numlinepar++;
10540: printf("\n");
10541: fprintf(ficparo,"\n");
10542: }
10543: }
10544: printf("# Covariance matrix\n");
10545: /* # 121 Var(a12)\n\ */
10546: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10547: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10548: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10549: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10550: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10551: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10552: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10553: fflush(stdout);
10554: fprintf(ficparo,"# Covariance matrix\n");
10555: /* # 121 Var(a12)\n\ */
10556: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10557: /* # ...\n\ */
10558: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10559:
10560: for(itimes=1;itimes<=2;itimes++){
10561: jj=0;
10562: for(i=1; i <=nlstate; i++){
10563: for(j=1; j <=nlstate+ndeath; j++){
10564: if(j==i) continue;
10565: for(k=1; k<=ncovmodel;k++){
10566: jj++;
10567: ca[0]= k+'a'-1;ca[1]='\0';
10568: if(itimes==1){
10569: printf("#%1d%1d%d",i,j,k);
10570: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10571: }else{
10572: printf("%1d%1d%d",i,j,k);
10573: fprintf(ficparo,"%1d%1d%d",i,j,k);
10574: /* printf(" %.5le",matcov[i][j]); */
10575: }
10576: ll=0;
10577: for(li=1;li <=nlstate; li++){
10578: for(lj=1;lj <=nlstate+ndeath; lj++){
10579: if(lj==li) continue;
10580: for(lk=1;lk<=ncovmodel;lk++){
10581: ll++;
10582: if(ll<=jj){
10583: cb[0]= lk +'a'-1;cb[1]='\0';
10584: if(ll<jj){
10585: if(itimes==1){
10586: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10587: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10588: }else{
10589: printf(" 0.");
10590: fprintf(ficparo," 0.");
10591: }
10592: }else{
10593: if(itimes==1){
10594: printf(" Var(%s%1d%1d)",ca,i,j);
10595: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10596: }else{
10597: printf(" 0.");
10598: fprintf(ficparo," 0.");
10599: }
10600: }
10601: }
10602: } /* end lk */
10603: } /* end lj */
10604: } /* end li */
10605: printf("\n");
10606: fprintf(ficparo,"\n");
10607: numlinepar++;
10608: } /* end k*/
10609: } /*end j */
10610: } /* end i */
10611: } /* end itimes */
10612:
10613: } /* end of prwizard */
10614: /******************* Gompertz Likelihood ******************************/
10615: double gompertz(double x[])
10616: {
1.302 brouard 10617: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10618: int i,n=0; /* n is the size of the sample */
10619:
1.220 brouard 10620: for (i=1;i<=imx ; i++) {
1.126 brouard 10621: sump=sump+weight[i];
10622: /* sump=sump+1;*/
10623: num=num+1;
10624: }
1.302 brouard 10625: L=0.0;
10626: /* agegomp=AGEGOMP; */
1.126 brouard 10627: /* for (i=0; i<=imx; i++)
10628: 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]);*/
10629:
1.302 brouard 10630: for (i=1;i<=imx ; i++) {
10631: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10632: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10633: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10634: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10635: * +
10636: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10637: */
10638: if (wav[i] > 1 || agedc[i] < AGESUP) {
10639: if (cens[i] == 1){
10640: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10641: } else if (cens[i] == 0){
1.126 brouard 10642: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10643: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10644: } else
10645: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10646: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10647: L=L+A*weight[i];
1.126 brouard 10648: /* 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 10649: }
10650: }
1.126 brouard 10651:
1.302 brouard 10652: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10653:
10654: return -2*L*num/sump;
10655: }
10656:
1.136 brouard 10657: #ifdef GSL
10658: /******************* Gompertz_f Likelihood ******************************/
10659: double gompertz_f(const gsl_vector *v, void *params)
10660: {
1.302 brouard 10661: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10662: double *x= (double *) v->data;
10663: int i,n=0; /* n is the size of the sample */
10664:
10665: for (i=0;i<=imx-1 ; i++) {
10666: sump=sump+weight[i];
10667: /* sump=sump+1;*/
10668: num=num+1;
10669: }
10670:
10671:
10672: /* for (i=0; i<=imx; i++)
10673: 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]);*/
10674: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10675: for (i=1;i<=imx ; i++)
10676: {
10677: if (cens[i] == 1 && wav[i]>1)
10678: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10679:
10680: if (cens[i] == 0 && wav[i]>1)
10681: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10682: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10683:
10684: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10685: if (wav[i] > 1 ) { /* ??? */
10686: LL=LL+A*weight[i];
10687: /* 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]);*/
10688: }
10689: }
10690:
10691: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10692: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10693:
10694: return -2*LL*num/sump;
10695: }
10696: #endif
10697:
1.126 brouard 10698: /******************* Printing html file ***********/
1.201 brouard 10699: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10700: int lastpass, int stepm, int weightopt, char model[],\
10701: int imx, double p[],double **matcov,double agemortsup){
10702: int i,k;
10703:
10704: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10705: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10706: for (i=1;i<=2;i++)
10707: 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 10708: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10709: fprintf(fichtm,"</ul>");
10710:
10711: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10712:
10713: 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>");
10714:
10715: for (k=agegomp;k<(agemortsup-2);k++)
10716: 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]);
10717:
10718:
10719: fflush(fichtm);
10720: }
10721:
10722: /******************* Gnuplot file **************/
1.201 brouard 10723: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10724:
10725: char dirfileres[132],optfileres[132];
1.164 brouard 10726:
1.126 brouard 10727: int ng;
10728:
10729:
10730: /*#ifdef windows */
10731: fprintf(ficgp,"cd \"%s\" \n",pathc);
10732: /*#endif */
10733:
10734:
10735: strcpy(dirfileres,optionfilefiname);
10736: strcpy(optfileres,"vpl");
1.199 brouard 10737: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10738: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10739: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10740: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10741: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10742:
10743: }
10744:
1.136 brouard 10745: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10746: {
1.126 brouard 10747:
1.136 brouard 10748: /*-------- data file ----------*/
10749: FILE *fic;
10750: char dummy[]=" ";
1.240 brouard 10751: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10752: int lstra;
1.136 brouard 10753: int linei, month, year,iout;
1.302 brouard 10754: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10755: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10756: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10757: char *stratrunc;
1.223 brouard 10758:
1.349 brouard 10759: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
10760: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10761:
10762: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10763:
1.136 brouard 10764: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10765: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10766: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10767: }
1.126 brouard 10768:
1.302 brouard 10769: /* Is it a BOM UTF-8 Windows file? */
10770: /* First data line */
10771: linei=0;
10772: while(fgets(line, MAXLINE, fic)) {
10773: noffset=0;
10774: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10775: {
10776: noffset=noffset+3;
10777: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10778: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10779: fflush(ficlog); return 1;
10780: }
10781: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10782: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10783: {
10784: noffset=noffset+2;
1.304 brouard 10785: 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);
10786: 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 10787: fflush(ficlog); return 1;
10788: }
10789: else if( line[0] == 0 && line[1] == 0)
10790: {
10791: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10792: noffset=noffset+4;
1.304 brouard 10793: 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);
10794: 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 10795: fflush(ficlog); return 1;
10796: }
10797: } else{
10798: ;/*printf(" Not a BOM file\n");*/
10799: }
10800: /* If line starts with a # it is a comment */
10801: if (line[noffset] == '#') {
10802: linei=linei+1;
10803: break;
10804: }else{
10805: break;
10806: }
10807: }
10808: fclose(fic);
10809: if((fic=fopen(datafile,"r"))==NULL) {
10810: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10811: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10812: }
10813: /* Not a Bom file */
10814:
1.136 brouard 10815: i=1;
10816: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10817: linei=linei+1;
10818: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10819: if(line[j] == '\t')
10820: line[j] = ' ';
10821: }
10822: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10823: ;
10824: };
10825: line[j+1]=0; /* Trims blanks at end of line */
10826: if(line[0]=='#'){
10827: fprintf(ficlog,"Comment line\n%s\n",line);
10828: printf("Comment line\n%s\n",line);
10829: continue;
10830: }
10831: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10832: strcpy(line, linetmp);
1.223 brouard 10833:
10834: /* Loops on waves */
10835: for (j=maxwav;j>=1;j--){
10836: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10837: cutv(stra, strb, line, ' ');
10838: if(strb[0]=='.') { /* Missing value */
10839: lval=-1;
10840: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10841: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10842: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10843: 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);
10844: 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);
10845: return 1;
10846: }
10847: }else{
10848: errno=0;
10849: /* what_kind_of_number(strb); */
10850: dval=strtod(strb,&endptr);
10851: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10852: /* if(strb != endptr && *endptr == '\0') */
10853: /* dval=dlval; */
10854: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10855: if( strb[0]=='\0' || (*endptr != '\0')){
10856: 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);
10857: 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);
10858: return 1;
10859: }
10860: cotqvar[j][iv][i]=dval;
1.341 brouard 10861: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10862: }
10863: strcpy(line,stra);
1.223 brouard 10864: }/* end loop ntqv */
1.225 brouard 10865:
1.223 brouard 10866: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10867: cutv(stra, strb, line, ' ');
10868: if(strb[0]=='.') { /* Missing value */
10869: lval=-1;
10870: }else{
10871: errno=0;
10872: lval=strtol(strb,&endptr,10);
10873: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10874: if( strb[0]=='\0' || (*endptr != '\0')){
10875: 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);
10876: 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);
10877: return 1;
10878: }
10879: }
10880: if(lval <-1 || lval >1){
10881: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10882: 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 10883: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10884: For example, for multinomial values like 1, 2 and 3,\n \
10885: build V1=0 V2=0 for the reference value (1),\n \
10886: V1=1 V2=0 for (2) \n \
1.223 brouard 10887: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10888: output of IMaCh is often meaningless.\n \
1.319 brouard 10889: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10890: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10891: 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 10892: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10893: For example, for multinomial values like 1, 2 and 3,\n \
10894: build V1=0 V2=0 for the reference value (1),\n \
10895: V1=1 V2=0 for (2) \n \
1.223 brouard 10896: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10897: output of IMaCh is often meaningless.\n \
1.319 brouard 10898: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10899: return 1;
10900: }
1.341 brouard 10901: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10902: strcpy(line,stra);
1.223 brouard 10903: }/* end loop ntv */
1.225 brouard 10904:
1.223 brouard 10905: /* Statuses at wave */
1.137 brouard 10906: cutv(stra, strb, line, ' ');
1.223 brouard 10907: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10908: lval=-1;
1.136 brouard 10909: }else{
1.238 brouard 10910: errno=0;
10911: lval=strtol(strb,&endptr,10);
10912: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10913: if( strb[0]=='\0' || (*endptr != '\0' )){
10914: 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);
10915: 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);
10916: return 1;
10917: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10918: 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);
10919: 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 10920: return 1;
10921: }
1.136 brouard 10922: }
1.225 brouard 10923:
1.136 brouard 10924: s[j][i]=lval;
1.225 brouard 10925:
1.223 brouard 10926: /* Date of Interview */
1.136 brouard 10927: strcpy(line,stra);
10928: cutv(stra, strb,line,' ');
1.169 brouard 10929: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10930: }
1.169 brouard 10931: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10932: month=99;
10933: year=9999;
1.136 brouard 10934: }else{
1.225 brouard 10935: 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);
10936: 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);
10937: return 1;
1.136 brouard 10938: }
10939: anint[j][i]= (double) year;
1.302 brouard 10940: mint[j][i]= (double)month;
10941: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10942: /* 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]); */
10943: /* 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]); */
10944: /* } */
1.136 brouard 10945: strcpy(line,stra);
1.223 brouard 10946: } /* End loop on waves */
1.225 brouard 10947:
1.223 brouard 10948: /* Date of death */
1.136 brouard 10949: cutv(stra, strb,line,' ');
1.169 brouard 10950: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10951: }
1.169 brouard 10952: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10953: month=99;
10954: year=9999;
10955: }else{
1.141 brouard 10956: 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 10957: 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);
10958: return 1;
1.136 brouard 10959: }
10960: andc[i]=(double) year;
10961: moisdc[i]=(double) month;
10962: strcpy(line,stra);
10963:
1.223 brouard 10964: /* Date of birth */
1.136 brouard 10965: cutv(stra, strb,line,' ');
1.169 brouard 10966: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10967: }
1.169 brouard 10968: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10969: month=99;
10970: year=9999;
10971: }else{
1.141 brouard 10972: 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);
10973: 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 10974: return 1;
1.136 brouard 10975: }
10976: if (year==9999) {
1.141 brouard 10977: 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);
10978: 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 10979: return 1;
10980:
1.136 brouard 10981: }
10982: annais[i]=(double)(year);
1.302 brouard 10983: moisnais[i]=(double)(month);
10984: for (j=1;j<=maxwav;j++){
10985: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10986: 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]);
10987: 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]);
10988: }
10989: }
10990:
1.136 brouard 10991: strcpy(line,stra);
1.225 brouard 10992:
1.223 brouard 10993: /* Sample weight */
1.136 brouard 10994: cutv(stra, strb,line,' ');
10995: errno=0;
10996: dval=strtod(strb,&endptr);
10997: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10998: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10999: 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 11000: fflush(ficlog);
11001: return 1;
11002: }
11003: weight[i]=dval;
11004: strcpy(line,stra);
1.225 brouard 11005:
1.223 brouard 11006: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
11007: cutv(stra, strb, line, ' ');
11008: if(strb[0]=='.') { /* Missing value */
1.225 brouard 11009: lval=-1;
1.311 brouard 11010: coqvar[iv][i]=NAN;
11011: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 11012: }else{
1.225 brouard 11013: errno=0;
11014: /* what_kind_of_number(strb); */
11015: dval=strtod(strb,&endptr);
11016: /* if(strb != endptr && *endptr == '\0') */
11017: /* dval=dlval; */
11018: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
11019: if( strb[0]=='\0' || (*endptr != '\0')){
11020: 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);
11021: 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);
11022: return 1;
11023: }
11024: coqvar[iv][i]=dval;
1.226 brouard 11025: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 11026: }
11027: strcpy(line,stra);
11028: }/* end loop nqv */
1.136 brouard 11029:
1.223 brouard 11030: /* Covariate values */
1.136 brouard 11031: for (j=ncovcol;j>=1;j--){
11032: cutv(stra, strb,line,' ');
1.223 brouard 11033: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 11034: lval=-1;
1.136 brouard 11035: }else{
1.225 brouard 11036: errno=0;
11037: lval=strtol(strb,&endptr,10);
11038: if( strb[0]=='\0' || (*endptr != '\0')){
11039: 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);
11040: 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);
11041: return 1;
11042: }
1.136 brouard 11043: }
11044: if(lval <-1 || lval >1){
1.225 brouard 11045: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11046: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11047: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11048: For example, for multinomial values like 1, 2 and 3,\n \
11049: build V1=0 V2=0 for the reference value (1),\n \
11050: V1=1 V2=0 for (2) \n \
1.136 brouard 11051: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11052: output of IMaCh is often meaningless.\n \
1.136 brouard 11053: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11054: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11055: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11056: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11057: For example, for multinomial values like 1, 2 and 3,\n \
11058: build V1=0 V2=0 for the reference value (1),\n \
11059: V1=1 V2=0 for (2) \n \
1.136 brouard 11060: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11061: output of IMaCh is often meaningless.\n \
1.136 brouard 11062: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11063: return 1;
1.136 brouard 11064: }
11065: covar[j][i]=(double)(lval);
11066: strcpy(line,stra);
11067: }
11068: lstra=strlen(stra);
1.225 brouard 11069:
1.136 brouard 11070: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11071: stratrunc = &(stra[lstra-9]);
11072: num[i]=atol(stratrunc);
11073: }
11074: else
11075: num[i]=atol(stra);
11076: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11077: 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;}*/
11078:
11079: i=i+1;
11080: } /* End loop reading data */
1.225 brouard 11081:
1.136 brouard 11082: *imax=i-1; /* Number of individuals */
11083: fclose(fic);
1.225 brouard 11084:
1.136 brouard 11085: return (0);
1.164 brouard 11086: /* endread: */
1.225 brouard 11087: printf("Exiting readdata: ");
11088: fclose(fic);
11089: return (1);
1.223 brouard 11090: }
1.126 brouard 11091:
1.234 brouard 11092: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11093: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11094: while (*p2 == ' ')
1.234 brouard 11095: p2++;
11096: /* while ((*p1++ = *p2++) !=0) */
11097: /* ; */
11098: /* do */
11099: /* while (*p2 == ' ') */
11100: /* p2++; */
11101: /* while (*p1++ == *p2++); */
11102: *stri=p2;
1.145 brouard 11103: }
11104:
1.330 brouard 11105: int decoderesult( char resultline[], int nres)
1.230 brouard 11106: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11107: {
1.235 brouard 11108: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11109: char resultsav[MAXLINE];
1.330 brouard 11110: /* int resultmodel[MAXLINE]; */
1.334 brouard 11111: /* int modelresult[MAXLINE]; */
1.230 brouard 11112: char stra[80], strb[80], strc[80], strd[80],stre[80];
11113:
1.234 brouard 11114: removefirstspace(&resultline);
1.332 brouard 11115: printf("decoderesult:%s\n",resultline);
1.230 brouard 11116:
1.332 brouard 11117: strcpy(resultsav,resultline);
1.342 brouard 11118: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11119: if (strlen(resultsav) >1){
1.334 brouard 11120: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11121: }
1.253 brouard 11122: if(j == 0){ /* Resultline but no = */
11123: TKresult[nres]=0; /* Combination for the nresult and the model */
11124: return (0);
11125: }
1.234 brouard 11126: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 11127: 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, %s.\n",j, cptcovs, model);
11128: 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, %s.\n",j, cptcovs, model);
1.332 brouard 11129: /* return 1;*/
1.234 brouard 11130: }
1.334 brouard 11131: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11132: if(nbocc(resultsav,'=') >1){
1.318 brouard 11133: 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 11134: /* 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 11135: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11136: /* If a blank, then strc="V4=" and strd='\0' */
11137: if(strc[0]=='\0'){
11138: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11139: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11140: return 1;
11141: }
1.234 brouard 11142: }else
11143: cutl(strc,strd,resultsav,'=');
1.318 brouard 11144: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11145:
1.230 brouard 11146: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11147: 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 11148: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11149: /* cptcovsel++; */
11150: if (nbocc(stra,'=') >0)
11151: strcpy(resultsav,stra); /* and analyzes it */
11152: }
1.235 brouard 11153: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11154: /* 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 11155: 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 11156: if(Typevar[k1]==0){ /* Single covariate in model */
11157: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11158: match=0;
1.318 brouard 11159: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11160: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11161: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11162: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11163: break;
11164: }
11165: }
11166: if(match == 0){
1.338 brouard 11167: 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]);
11168: 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 11169: return 1;
1.234 brouard 11170: }
1.332 brouard 11171: }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*/
11172: /* We feed resultmodel[k1]=k2; */
11173: match=0;
11174: 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 */
11175: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11176: 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 11177: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11178: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11179: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11180: break;
11181: }
11182: }
11183: if(match == 0){
1.338 brouard 11184: 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]);
11185: 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 11186: return 1;
11187: }
1.349 brouard 11188: }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 11189: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11190: match=0;
1.342 brouard 11191: /* 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 11192: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11193: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11194: /* modelresult[k2]=k1; */
1.342 brouard 11195: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11196: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11197: }
11198: }
11199: if(match == 0){
1.349 brouard 11200: 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);
11201: 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 11202: return 1;
11203: }
11204: match=0;
11205: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11206: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11207: /* modelresult[k2]=k1;*/
1.342 brouard 11208: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11209: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11210: break;
11211: }
11212: }
11213: if(match == 0){
1.349 brouard 11214: 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);
11215: 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 11216: return 1;
11217: }
11218: }/* End of testing */
1.333 brouard 11219: }/* End loop cptcovt */
1.235 brouard 11220: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11221: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11222: 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)
11223: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11224: match=0;
1.318 brouard 11225: 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 11226: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 11227: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11228: 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 11229: 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 11230: ++match;
11231: }
11232: }
11233: }
11234: if(match == 0){
1.338 brouard 11235: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11236: 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 11237: return 1;
1.234 brouard 11238: }else if(match > 1){
1.338 brouard 11239: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11240: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11241: return 1;
1.234 brouard 11242: }
11243: }
1.334 brouard 11244: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11245: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11246: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11247: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11248: /* 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*/
11249: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11250: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11251: /* 1 0 0 0 */
11252: /* 2 1 0 0 */
11253: /* 3 0 1 0 */
1.330 brouard 11254: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11255: /* 5 0 0 1 */
1.330 brouard 11256: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11257: /* 7 0 1 1 */
11258: /* 8 1 1 1 */
1.237 brouard 11259: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11260: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11261: /* V5*age V5 known which value for nres? */
11262: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11263: 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.
11264: * loop on position k1 in the MODEL LINE */
1.331 brouard 11265: /* k counting number of combination of single dummies in the equation model */
11266: /* k4 counting single dummies in the equation model */
11267: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11268: 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 11269: /* 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 11270: /* 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 11271: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11272: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11273: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11274: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11275: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11276: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11277: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11278: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11279: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11280: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11281: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11282: 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 11283: 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 11284: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11285: /* Tinvresult[nres][4]=1 */
1.334 brouard 11286: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11287: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11288: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11289: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11290: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11291: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11292: /* 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 11293: k4++;;
1.331 brouard 11294: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11295: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11296: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11297: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11298: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11299: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11300: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11301: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11302: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11303: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11304: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11305: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11306: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11307: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11308: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11309: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11310: /* 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 11311: k4q++;;
1.350 brouard 11312: }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"*/
11313: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 11314: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 11315: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11316: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11317: /* 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]]); */
11318: }else{
11319: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11320: 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)*/
11321: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
11322: precov[nres][k1]=Tvalsel[k3];
11323: }
1.342 brouard 11324: /* 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 11325: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 11326: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11327: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11328: /* 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]]); */
11329: }else{
11330: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
11331: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
11332: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
11333: precov[nres][k1]=Tvalsel[k3q];
11334: }
1.342 brouard 11335: /* 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 11336: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11337: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11338: /* 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 11339: }else{
1.332 brouard 11340: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11341: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11342: }
11343: }
1.234 brouard 11344:
1.334 brouard 11345: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11346: return (0);
11347: }
1.235 brouard 11348:
1.230 brouard 11349: int decodemodel( char model[], int lastobs)
11350: /**< This routine decodes the model and returns:
1.224 brouard 11351: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11352: * - nagesqr = 1 if age*age in the model, otherwise 0.
11353: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11354: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11355: * - cptcovage number of covariates with age*products =2
11356: * - cptcovs number of simple covariates
1.339 brouard 11357: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11358: * - 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 11359: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11360: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11361: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11362: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11363: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11364: */
1.319 brouard 11365: /* 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 11366: {
1.238 brouard 11367: int i, j, k, ks, v;
1.349 brouard 11368: int n,m;
11369: int j1, k1, k11, k12, k2, k3, k4;
11370: char modelsav[300];
11371: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11372: char *strpt;
1.349 brouard 11373: int **existcomb;
11374:
11375: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
11376: for(i=1;i<=NCOVMAX;i++)
11377: for(j=1;j<=NCOVMAX;j++)
11378: existcomb[i][j]=0;
11379:
1.145 brouard 11380: /*removespace(model);*/
1.136 brouard 11381: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 11382: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11383: if (strstr(model,"AGE") !=0){
1.192 brouard 11384: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11385: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11386: return 1;
11387: }
1.141 brouard 11388: if (strstr(model,"v") !=0){
1.338 brouard 11389: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11390: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11391: return 1;
11392: }
1.187 brouard 11393: strcpy(modelsav,model);
11394: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11395: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11396: if(strpt != model){
1.338 brouard 11397: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11398: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11399: corresponding column of parameters.\n",model);
1.338 brouard 11400: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11401: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11402: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11403: return 1;
1.225 brouard 11404: }
1.187 brouard 11405: nagesqr=1;
11406: if (strstr(model,"+age*age") !=0)
1.234 brouard 11407: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11408: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11409: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11410: else
1.234 brouard 11411: substrchaine(modelsav, model, "age*age");
1.187 brouard 11412: }else
11413: nagesqr=0;
1.349 brouard 11414: 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 11415: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11416: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 11417: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 11418: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11419: * cst, age and age*age
11420: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11421: /* including age products which are counted in cptcovage.
11422: * but the covariates which are products must be treated
11423: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 11424: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
11425: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11426: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 11427: cptcovprodage=0;
11428: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11429:
1.187 brouard 11430: /* Design
11431: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11432: * < ncovcol=8 >
11433: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11434: * k= 1 2 3 4 5 6 7 8
11435: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11436: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11437: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11438: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11439: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11440: * Tage[++cptcovage]=k
1.345 brouard 11441: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11442: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11443: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11444: * 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
11445: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11446: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11447: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11448: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11449: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11450: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11451: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11452: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11453: * p Tprod[1]@2={ 6, 5}
11454: *p Tvard[1][1]@4= {7, 8, 5, 6}
11455: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11456: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11457: *How to reorganize? Tvars(orted)
1.187 brouard 11458: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11459: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11460: * {2, 1, 4, 8, 5, 6, 3, 7}
11461: * Struct []
11462: */
1.225 brouard 11463:
1.187 brouard 11464: /* This loop fills the array Tvar from the string 'model'.*/
11465: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11466: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11467: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11468: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11469: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11470: /* k=1 Tvar[1]=2 (from V2) */
11471: /* k=5 Tvar[5] */
11472: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11473: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11474: /* } */
1.198 brouard 11475: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11476: /*
11477: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11478: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11479: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11480: }
1.187 brouard 11481: cptcovage=0;
1.351 brouard 11482:
11483: /* First loop in order to calculate */
11484: /* for age*VN*Vm
11485: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
11486: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
11487: */
11488: /* Needs FixedV[Tvardk[k][1]] */
11489: /* For others:
11490: * Sets Typevar[k];
11491: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11492: * Tposprod[k]=k11;
11493: * Tprod[k11]=k;
11494: * Tvardk[k][1] =m;
11495: * Needs FixedV[Tvardk[k][1]] == 0
11496: */
11497:
1.319 brouard 11498: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11499: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11500: 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" */
11501: if (nbocc(modelsav,'+')==0)
11502: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11503: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11504: /*scanf("%d",i);*/
1.349 brouard 11505: 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 */
11506: 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 */
11507: 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 */
11508: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
11509: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
11510: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
11511: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
11512: /* We want strb=Vn*Vm */
11513: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
11514: strcpy(strb,strd);
11515: strcat(strb,"*");
11516: strcat(strb,stre);
11517: }else{ /* strf=Vm If strf=V6 then stre=V2 */
11518: strcpy(strb,strf);
11519: strcat(strb,"*");
11520: strcat(strb,stre);
11521: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
11522: }
1.351 brouard 11523: /* 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]]]); */
11524: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 11525: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
11526: strcpy(stre,strb); /* save full b in stre */
11527: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
11528: strcpy(strf,strc); /* save short c in new short f */
11529: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
11530: /* strcpy(strc,stre);*/ /* save full e in c for future */
11531: }
11532: cptcovdageprod++; /* double product with age Which product is it? */
11533: /* 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 *\/ */
11534: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11535: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 11536: n=atoi(stre);
1.234 brouard 11537: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 11538: m=atoi(strc);
11539: cptcovage++; /* Counts the number of covariates which include age as a product */
11540: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
11541: if(existcomb[n][m] == 0){
11542: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
11543: 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);
11544: 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);
11545: fflush(ficlog);
11546: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
11547: k12++;
11548: existcomb[n][m]=k1;
11549: existcomb[m][n]=k1;
11550: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
11551: 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*/
11552: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
11553: Tvard[k1][1] =m; /* m 1 for V1*/
11554: Tvardk[k][1] =m; /* m 1 for V1*/
11555: Tvard[k1][2] =n; /* n 4 for V4*/
11556: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 11557: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 11558: 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 */
11559: for (i=1; i<=lastobs;i++){/* For fixed product */
11560: /* Computes the new covariate which is a product of
11561: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11562: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11563: }
11564: cptcovprodage++; /* Counting the number of fixed covariate with age */
11565: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11566: k12++;
11567: FixedV[ncovcolt+k12]=0;
11568: }else{ /*End of FixedV */
11569: cptcovprodvage++; /* Counting the number of varying covariate with age */
11570: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11571: k12++;
11572: FixedV[ncovcolt+k12]=1;
11573: }
11574: }else{ /* k1 Vn*Vm already exists */
11575: k11=existcomb[n][m];
11576: Tposprod[k]=k11; /* OK */
11577: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
11578: Tvardk[k][1]=m;
11579: Tvardk[k][2]=n;
11580: 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 */
11581: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11582: cptcovprodage++; /* Counting the number of fixed covariate with age */
11583: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11584: Tvar[Tage[cptcovage]]=k1;
11585: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11586: k12++;
11587: FixedV[ncovcolt+k12]=0;
11588: }else{ /* Already exists but time varying (and age) */
11589: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11590: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11591: /* Tvar[Tage[cptcovage]]=k1; */
11592: cptcovprodvage++;
11593: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11594: k12++;
11595: FixedV[ncovcolt+k12]=1;
11596: }
11597: }
11598: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
11599: /* Tvar[k]=k11; /\* HERY *\/ */
11600: } 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 */
11601: cptcovprod++;
11602: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
11603: /* covar is not filled and then is empty */
11604: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
11605: 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 */
11606: Typevar[k]=1; /* 1 for age product */
11607: cptcovage++; /* Counts the number of covariates which include age as a product */
11608: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
11609: if( FixedV[Tvar[k]] == 0){
11610: cptcovprodage++; /* Counting the number of fixed covariate with age */
11611: }else{
11612: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
11613: }
11614: /*printf("stre=%s ", stre);*/
11615: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
11616: cutl(stre,strb,strc,'V');
11617: Tvar[k]=atoi(stre);
11618: Typevar[k]=1; /* 1 for age product */
11619: cptcovage++;
11620: Tage[cptcovage]=k;
11621: if( FixedV[Tvar[k]] == 0){
11622: cptcovprodage++; /* Counting the number of fixed covariate with age */
11623: }else{
11624: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11625: }
1.349 brouard 11626: }else{ /* for product Vn*Vm */
11627: Typevar[k]=2; /* 2 for product Vn*Vm */
11628: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
11629: n=atoi(stre);
11630: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11631: m=atoi(strc);
11632: k1++;
11633: cptcovprodnoage++;
11634: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
11635: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11636: 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]);
11637: fflush(ficlog);
11638: k11=existcomb[n][m];
11639: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11640: Tposprod[k]=k11;
11641: Tprod[k11]=k;
11642: Tvardk[k][1] =m; /* m 1 for V1*/
11643: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
11644: Tvardk[k][2] =n; /* n 4 for V4*/
11645: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
11646: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
11647: existcomb[n][m]=k1;
11648: existcomb[m][n]=k1;
11649: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
11650: because this model-covariate is a construction we invent a new column
11651: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
11652: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
11653: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
11654: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
11655: /* Please remark that the new variables are model dependent */
11656: /* If we have 4 variable but the model uses only 3, like in
11657: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11658: * k= 1 2 3 4 5 6 7 8
11659: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11660: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11661: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11662: */
11663: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
11664: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
11665: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
11666: Tvard[k1][1] =m; /* m 1 for V1*/
11667: Tvardk[k][1] =m; /* m 1 for V1*/
11668: Tvard[k1][2] =n; /* n 4 for V4*/
11669: Tvardk[k][2] =n; /* n 4 for V4*/
11670: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11671: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11672: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
11673: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
11674: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
11675: 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 */
11676: for (i=1; i<=lastobs;i++){/* For fixed product */
11677: /* Computes the new covariate which is a product of
11678: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11679: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11680: }
11681: /* TvarVV[k2]=n; */
11682: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11683: /* TvarVV[k2+1]=m; */
11684: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11685: }else{ /* not FixedV */
11686: /* TvarVV[k2]=n; */
11687: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11688: /* TvarVV[k2+1]=m; */
11689: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11690: }
11691: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
11692: } /* End of product Vn*Vm */
11693: } /* End of age*double product or simple product */
11694: }else { /* not a product */
1.234 brouard 11695: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11696: /* scanf("%d",i);*/
11697: cutl(strd,strc,strb,'V');
11698: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11699: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11700: Tvar[k]=atoi(strd);
11701: Typevar[k]=0; /* 0 for simple covariates */
11702: }
11703: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11704: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11705: scanf("%d",i);*/
1.187 brouard 11706: } /* end of loop + on total covariates */
1.351 brouard 11707:
11708:
1.187 brouard 11709: } /* end if strlen(modelsave == 0) age*age might exist */
11710: } /* end if strlen(model == 0) */
1.349 brouard 11711: 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 */
11712:
1.136 brouard 11713: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11714: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11715:
1.136 brouard 11716: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11717: printf("cptcovprod=%d ", cptcovprod);
11718: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11719: scanf("%d ",i);*/
11720:
11721:
1.230 brouard 11722: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11723: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11724: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11725: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11726: k = 1 2 3 4 5 6 7 8 9
11727: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11728: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11729: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11730: Dummy[k] 1 0 0 0 3 1 1 2 3
11731: Tmodelind[combination of covar]=k;
1.225 brouard 11732: */
11733: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11734: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11735: /* 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 11736: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11737: printf("Model=1+age+%s\n\
1.349 brouard 11738: 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 11739: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11740: 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 11741: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 11742: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 11743: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11744: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.342 brouard 11745: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11746: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 11747:
11748:
11749: /* Second loop for calculating Fixed[k], Dummy[k]*/
11750:
11751:
1.349 brouard 11752: 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 11753: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11754: Fixed[k]= 0;
11755: Dummy[k]= 0;
1.225 brouard 11756: ncoveff++;
1.232 brouard 11757: ncovf++;
1.234 brouard 11758: nsd++;
11759: modell[k].maintype= FTYPE;
11760: TvarsD[nsd]=Tvar[k];
11761: TvarsDind[nsd]=k;
1.330 brouard 11762: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11763: TvarF[ncovf]=Tvar[k];
11764: TvarFind[ncovf]=k;
11765: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11766: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11767: /* }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 11768: }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 11769: Fixed[k]= 0;
11770: Dummy[k]= 1;
1.230 brouard 11771: nqfveff++;
1.234 brouard 11772: modell[k].maintype= FTYPE;
11773: modell[k].subtype= FQ;
11774: nsq++;
1.334 brouard 11775: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11776: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11777: ncovf++;
1.234 brouard 11778: TvarF[ncovf]=Tvar[k];
11779: TvarFind[ncovf]=k;
1.231 brouard 11780: 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 11781: 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 11782: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11783: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11784: /* model V1+V3+age*V1+age*V3+V1*V3 */
11785: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11786: ncovvt++;
11787: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11788: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11789:
1.227 brouard 11790: Fixed[k]= 1;
11791: Dummy[k]= 0;
1.225 brouard 11792: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11793: modell[k].maintype= VTYPE;
11794: modell[k].subtype= VD;
11795: nsd++;
11796: TvarsD[nsd]=Tvar[k];
11797: TvarsDind[nsd]=k;
1.330 brouard 11798: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11799: ncovv++; /* Only simple time varying variables */
11800: TvarV[ncovv]=Tvar[k];
1.242 brouard 11801: 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 11802: 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 */
11803: 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 11804: 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);
11805: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11806: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11807: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11808: /* model V1+V3+age*V1+age*V3+V1*V3 */
11809: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11810: ncovvt++;
11811: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11812: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11813:
1.234 brouard 11814: Fixed[k]= 1;
11815: Dummy[k]= 1;
11816: nqtveff++;
11817: modell[k].maintype= VTYPE;
11818: modell[k].subtype= VQ;
11819: ncovv++; /* Only simple time varying variables */
11820: nsq++;
1.334 brouard 11821: 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) */
11822: 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 11823: TvarV[ncovv]=Tvar[k];
1.242 brouard 11824: 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 11825: 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 */
11826: 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 11827: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11828: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 11829: /* 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 11830: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11831: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11832: ncova++;
11833: TvarA[ncova]=Tvar[k];
11834: TvarAind[ncova]=k;
1.349 brouard 11835: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11836: /** 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 11837: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11838: Fixed[k]= 2;
11839: Dummy[k]= 2;
11840: modell[k].maintype= ATYPE;
11841: modell[k].subtype= APFD;
1.349 brouard 11842: ncovta++;
11843: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
11844: TvarAVVAind[ncovta]=k;
1.240 brouard 11845: /* ncoveff++; */
1.227 brouard 11846: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11847: Fixed[k]= 2;
11848: Dummy[k]= 3;
11849: modell[k].maintype= ATYPE;
11850: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 11851: ncovta++;
11852: TvarAVVA[ncovta]=Tvar[k]; /* */
11853: TvarAVVAind[ncovta]=k;
1.240 brouard 11854: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11855: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11856: Fixed[k]= 3;
11857: Dummy[k]= 2;
11858: modell[k].maintype= ATYPE;
11859: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 11860: ncovva++;
11861: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11862: TvarVVAind[ncovva]=k;
11863: ncovta++;
11864: TvarAVVA[ncovta]=Tvar[k]; /* */
11865: TvarAVVAind[ncovta]=k;
1.240 brouard 11866: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11867: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11868: Fixed[k]= 3;
11869: Dummy[k]= 3;
11870: modell[k].maintype= ATYPE;
11871: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 11872: ncovva++;
11873: TvarVVA[ncovva]=Tvar[k]; /* */
11874: TvarVVAind[ncovva]=k;
11875: ncovta++;
11876: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11877: TvarAVVAind[ncovta]=k;
1.240 brouard 11878: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11879: }
1.349 brouard 11880: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
11881: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
11882: 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 */
11883: 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]]);
11884: Fixed[k]= 0;
11885: Dummy[k]= 0;
11886: ncoveff++;
11887: ncovf++;
11888: /* ncovv++; */
11889: /* TvarVV[ncovv]=Tvardk[k][1]; */
11890: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11891: /* ncovv++; */
11892: /* TvarVV[ncovv]=Tvardk[k][2]; */
11893: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11894: modell[k].maintype= FTYPE;
11895: TvarF[ncovf]=Tvar[k];
11896: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
11897: TvarFind[ncovf]=k;
11898: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11899: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11900: }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 */
11901: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11902: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11903: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11904: 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 */
11905: ncovvt++;
11906: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11907: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11908: ncovvt++;
11909: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11910: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11911:
11912: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11913: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
11914:
11915: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11916: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
11917: Fixed[k]= 1;
11918: Dummy[k]= 0;
11919: modell[k].maintype= FTYPE;
11920: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11921: ncovf++; /* Fixed variables without age */
11922: TvarF[ncovf]=Tvar[k];
11923: TvarFind[ncovf]=k;
11924: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11925: Fixed[k]= 0; /* Fixed product */
11926: Dummy[k]= 1;
11927: modell[k].maintype= FTYPE;
11928: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11929: ncovf++; /* Varying variables without age */
11930: TvarF[ncovf]=Tvar[k];
11931: TvarFind[ncovf]=k;
11932: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
11933: Fixed[k]= 1;
11934: Dummy[k]= 0;
11935: modell[k].maintype= VTYPE;
11936: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11937: ncovv++; /* Varying variables without age */
11938: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11939: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11940: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
11941: Fixed[k]= 1;
11942: Dummy[k]= 1;
11943: modell[k].maintype= VTYPE;
11944: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11945: ncovv++; /* Varying variables without age */
11946: TvarV[ncovv]=Tvar[k];
11947: TvarVind[ncovv]=k;
11948: }
11949: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11950: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11951: Fixed[k]= 0; /* Fixed product */
11952: Dummy[k]= 1;
11953: modell[k].maintype= FTYPE;
11954: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11955: ncovf++; /* Fixed variables without age */
11956: TvarF[ncovf]=Tvar[k];
11957: TvarFind[ncovf]=k;
11958: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
11959: Fixed[k]= 1;
11960: Dummy[k]= 1;
11961: modell[k].maintype= VTYPE;
11962: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11963: ncovv++; /* Varying variables without age */
11964: TvarV[ncovv]=Tvar[k];
11965: TvarVind[ncovv]=k;
11966: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
11967: Fixed[k]= 1;
11968: Dummy[k]= 1;
11969: modell[k].maintype= VTYPE;
11970: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11971: ncovv++; /* Varying variables without age */
11972: TvarV[ncovv]=Tvar[k];
11973: TvarVind[ncovv]=k;
11974: ncovv++; /* Varying variables without age */
11975: TvarV[ncovv]=Tvar[k];
11976: TvarVind[ncovv]=k;
11977: }
11978: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
11979: if(Tvard[k1][2] <=ncovcol){
11980: Fixed[k]= 1;
11981: Dummy[k]= 1;
11982: modell[k].maintype= VTYPE;
11983: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11984: ncovv++; /* Varying variables without age */
11985: TvarV[ncovv]=Tvar[k];
11986: TvarVind[ncovv]=k;
11987: }else if(Tvard[k1][2] <=ncovcol+nqv){
11988: Fixed[k]= 1;
11989: Dummy[k]= 1;
11990: modell[k].maintype= VTYPE;
11991: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11992: ncovv++; /* Varying variables without age */
11993: TvarV[ncovv]=Tvar[k];
11994: TvarVind[ncovv]=k;
11995: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11996: Fixed[k]= 1;
11997: Dummy[k]= 0;
11998: modell[k].maintype= VTYPE;
11999: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
12000: ncovv++; /* Varying variables without age */
12001: TvarV[ncovv]=Tvar[k];
12002: TvarVind[ncovv]=k;
12003: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12004: Fixed[k]= 1;
12005: Dummy[k]= 1;
12006: modell[k].maintype= VTYPE;
12007: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
12008: ncovv++; /* Varying variables without age */
12009: TvarV[ncovv]=Tvar[k];
12010: TvarVind[ncovv]=k;
12011: }
12012: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
12013: if(Tvard[k1][2] <=ncovcol){
12014: Fixed[k]= 1;
12015: Dummy[k]= 1;
12016: modell[k].maintype= VTYPE;
12017: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
12018: ncovv++; /* Varying variables without age */
12019: TvarV[ncovv]=Tvar[k];
12020: TvarVind[ncovv]=k;
12021: }else if(Tvard[k1][2] <=ncovcol+nqv){
12022: Fixed[k]= 1;
12023: Dummy[k]= 1;
12024: modell[k].maintype= VTYPE;
12025: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
12026: ncovv++; /* Varying variables without age */
12027: TvarV[ncovv]=Tvar[k];
12028: TvarVind[ncovv]=k;
12029: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12030: Fixed[k]= 1;
12031: Dummy[k]= 1;
12032: modell[k].maintype= VTYPE;
12033: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
12034: ncovv++; /* Varying variables without age */
12035: TvarV[ncovv]=Tvar[k];
12036: TvarVind[ncovv]=k;
12037: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12038: Fixed[k]= 1;
12039: Dummy[k]= 1;
12040: modell[k].maintype= VTYPE;
12041: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
12042: ncovv++; /* Varying variables without age */
12043: TvarV[ncovv]=Tvar[k];
12044: TvarVind[ncovv]=k;
12045: }
12046: }else{
12047: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12048: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12049: } /*end k1*/
12050: }
12051: }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 12052: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 12053: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
12054: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
12055: 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 */
12056: ncova++;
12057: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
12058: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
12059: ncova++;
12060: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
12061: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 12062:
1.349 brouard 12063: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
12064: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
12065: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
12066: ncovta++;
12067: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12068: TvarAVVAind[ncovta]=k;
12069: ncovta++;
12070: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12071: TvarAVVAind[ncovta]=k;
12072: }else{
12073: ncovva++; /* HERY reached */
12074: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12075: TvarVVAind[ncovva]=k;
12076: ncovva++;
12077: TvarVVA[ncovva]=Tvard[k1][2]; /* */
12078: TvarVVAind[ncovva]=k;
12079: ncovta++;
12080: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12081: TvarAVVAind[ncovta]=k;
12082: ncovta++;
12083: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12084: TvarAVVAind[ncovta]=k;
12085: }
1.339 brouard 12086: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12087: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 12088: Fixed[k]= 2;
12089: Dummy[k]= 2;
1.240 brouard 12090: modell[k].maintype= FTYPE;
12091: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 12092: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
12093: /* TvarFind[ncova]=k; */
1.339 brouard 12094: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 12095: Fixed[k]= 2; /* Fixed product */
12096: Dummy[k]= 3;
1.240 brouard 12097: modell[k].maintype= FTYPE;
12098: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 12099: /* TvarF[ncova]=Tvar[k]; */
12100: /* TvarFind[ncova]=k; */
1.339 brouard 12101: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 12102: Fixed[k]= 3;
12103: Dummy[k]= 2;
1.240 brouard 12104: modell[k].maintype= VTYPE;
12105: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 12106: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
12107: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12108: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 12109: Fixed[k]= 3;
12110: Dummy[k]= 3;
1.240 brouard 12111: modell[k].maintype= VTYPE;
12112: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 12113: /* ncovv++; /\* Varying variables without age *\/ */
12114: /* TvarV[ncovv]=Tvar[k]; */
12115: /* TvarVind[ncovv]=k; */
1.240 brouard 12116: }
1.339 brouard 12117: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12118: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 12119: Fixed[k]= 2; /* Fixed product */
12120: Dummy[k]= 2;
1.240 brouard 12121: modell[k].maintype= FTYPE;
12122: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 12123: /* ncova++; /\* Fixed variables with age *\/ */
12124: /* TvarF[ncovf]=Tvar[k]; */
12125: /* TvarFind[ncovf]=k; */
1.339 brouard 12126: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 12127: Fixed[k]= 2;
12128: Dummy[k]= 3;
1.240 brouard 12129: modell[k].maintype= VTYPE;
12130: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 12131: /* ncova++; /\* Varying variables with age *\/ */
12132: /* TvarV[ncova]=Tvar[k]; */
12133: /* TvarVind[ncova]=k; */
1.339 brouard 12134: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 12135: Fixed[k]= 3;
12136: Dummy[k]= 2;
1.240 brouard 12137: modell[k].maintype= VTYPE;
12138: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 12139: ncova++; /* Varying variables without age */
12140: TvarV[ncova]=Tvar[k];
12141: TvarVind[ncova]=k;
12142: /* ncova++; /\* Varying variables without age *\/ */
12143: /* TvarV[ncova]=Tvar[k]; */
12144: /* TvarVind[ncova]=k; */
1.240 brouard 12145: }
1.339 brouard 12146: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12147: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12148: Fixed[k]= 2;
12149: Dummy[k]= 2;
1.240 brouard 12150: modell[k].maintype= VTYPE;
12151: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 12152: /* ncova++; /\* Varying variables with age *\/ */
12153: /* TvarV[ncova]=Tvar[k]; */
12154: /* TvarVind[ncova]=k; */
1.240 brouard 12155: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12156: Fixed[k]= 2;
12157: Dummy[k]= 3;
1.240 brouard 12158: modell[k].maintype= VTYPE;
12159: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 12160: /* ncova++; /\* Varying variables with age *\/ */
12161: /* TvarV[ncova]=Tvar[k]; */
12162: /* TvarVind[ncova]=k; */
1.240 brouard 12163: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12164: Fixed[k]= 3;
12165: Dummy[k]= 2;
1.240 brouard 12166: modell[k].maintype= VTYPE;
12167: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 12168: /* ncova++; /\* Varying variables with age *\/ */
12169: /* TvarV[ncova]=Tvar[k]; */
12170: /* TvarVind[ncova]=k; */
1.240 brouard 12171: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12172: Fixed[k]= 3;
12173: Dummy[k]= 3;
1.240 brouard 12174: modell[k].maintype= VTYPE;
12175: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 12176: /* ncova++; /\* Varying variables with age *\/ */
12177: /* TvarV[ncova]=Tvar[k]; */
12178: /* TvarVind[ncova]=k; */
1.240 brouard 12179: }
1.339 brouard 12180: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12181: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12182: Fixed[k]= 2;
12183: Dummy[k]= 2;
1.240 brouard 12184: modell[k].maintype= VTYPE;
12185: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 12186: /* ncova++; /\* Varying variables with age *\/ */
12187: /* TvarV[ncova]=Tvar[k]; */
12188: /* TvarVind[ncova]=k; */
1.240 brouard 12189: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12190: Fixed[k]= 2;
12191: Dummy[k]= 3;
1.240 brouard 12192: modell[k].maintype= VTYPE;
12193: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 12194: /* ncova++; /\* Varying variables with age *\/ */
12195: /* TvarV[ncova]=Tvar[k]; */
12196: /* TvarVind[ncova]=k; */
1.240 brouard 12197: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12198: Fixed[k]= 3;
12199: Dummy[k]= 2;
1.240 brouard 12200: modell[k].maintype= VTYPE;
12201: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 12202: /* ncova++; /\* Varying variables with age *\/ */
12203: /* TvarV[ncova]=Tvar[k]; */
12204: /* TvarVind[ncova]=k; */
1.240 brouard 12205: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12206: Fixed[k]= 3;
12207: Dummy[k]= 3;
1.240 brouard 12208: modell[k].maintype= VTYPE;
12209: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 12210: /* ncova++; /\* Varying variables with age *\/ */
12211: /* TvarV[ncova]=Tvar[k]; */
12212: /* TvarVind[ncova]=k; */
1.240 brouard 12213: }
1.227 brouard 12214: }else{
1.240 brouard 12215: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12216: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12217: } /*end k1*/
1.349 brouard 12218: } else{
1.226 brouard 12219: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12220: 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 12221: }
1.342 brouard 12222: /* 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]); */
12223: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12224: 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]);
12225: }
1.349 brouard 12226: ncovvta=ncovva;
1.227 brouard 12227: /* Searching for doublons in the model */
12228: for(k1=1; k1<= cptcovt;k1++){
12229: for(k2=1; k2 <k1;k2++){
1.285 brouard 12230: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12231: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12232: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12233: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12234: 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]);
12235: 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 12236: return(1);
12237: }
12238: }else if (Typevar[k1] ==2){
12239: k3=Tposprod[k1];
12240: k4=Tposprod[k2];
12241: 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 12242: 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]]);
12243: 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 12244: return(1);
12245: }
12246: }
1.227 brouard 12247: }
12248: }
1.225 brouard 12249: }
12250: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12251: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12252: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12253: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 12254:
12255: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12256: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12257: /*endread:*/
1.225 brouard 12258: printf("Exiting decodemodel: ");
12259: return (1);
1.136 brouard 12260: }
12261:
1.169 brouard 12262: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12263: {/* Check ages at death */
1.136 brouard 12264: int i, m;
1.218 brouard 12265: int firstone=0;
12266:
1.136 brouard 12267: for (i=1; i<=imx; i++) {
12268: for(m=2; (m<= maxwav); m++) {
12269: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12270: anint[m][i]=9999;
1.216 brouard 12271: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12272: s[m][i]=-1;
1.136 brouard 12273: }
12274: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12275: *nberr = *nberr + 1;
1.218 brouard 12276: if(firstone == 0){
12277: firstone=1;
1.260 brouard 12278: 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 12279: }
1.262 brouard 12280: 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 12281: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12282: }
12283: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12284: (*nberr)++;
1.259 brouard 12285: 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 12286: 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 12287: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12288: }
12289: }
12290: }
12291:
12292: for (i=1; i<=imx; i++) {
12293: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12294: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12295: 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 12296: if (s[m][i] >= nlstate+1) {
1.169 brouard 12297: if(agedc[i]>0){
12298: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12299: agev[m][i]=agedc[i];
1.214 brouard 12300: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12301: }else {
1.136 brouard 12302: if ((int)andc[i]!=9999){
12303: nbwarn++;
12304: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12305: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12306: agev[m][i]=-1;
12307: }
12308: }
1.169 brouard 12309: } /* agedc > 0 */
1.214 brouard 12310: } /* end if */
1.136 brouard 12311: else if(s[m][i] !=9){ /* Standard case, age in fractional
12312: years but with the precision of a month */
12313: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12314: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12315: agev[m][i]=1;
12316: else if(agev[m][i] < *agemin){
12317: *agemin=agev[m][i];
12318: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12319: }
12320: else if(agev[m][i] >*agemax){
12321: *agemax=agev[m][i];
1.156 brouard 12322: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12323: }
12324: /*agev[m][i]=anint[m][i]-annais[i];*/
12325: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12326: } /* en if 9*/
1.136 brouard 12327: else { /* =9 */
1.214 brouard 12328: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12329: agev[m][i]=1;
12330: s[m][i]=-1;
12331: }
12332: }
1.214 brouard 12333: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12334: agev[m][i]=1;
1.214 brouard 12335: else{
12336: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12337: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12338: agev[m][i]=0;
12339: }
12340: } /* End for lastpass */
12341: }
1.136 brouard 12342:
12343: for (i=1; i<=imx; i++) {
12344: for(m=firstpass; (m<=lastpass); m++){
12345: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12346: (*nberr)++;
1.136 brouard 12347: 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);
12348: 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);
12349: return 1;
12350: }
12351: }
12352: }
12353:
12354: /*for (i=1; i<=imx; i++){
12355: for (m=firstpass; (m<lastpass); m++){
12356: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12357: }
12358:
12359: }*/
12360:
12361:
1.139 brouard 12362: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12363: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12364:
12365: return (0);
1.164 brouard 12366: /* endread:*/
1.136 brouard 12367: printf("Exiting calandcheckages: ");
12368: return (1);
12369: }
12370:
1.172 brouard 12371: #if defined(_MSC_VER)
12372: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12373: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12374: //#include "stdafx.h"
12375: //#include <stdio.h>
12376: //#include <tchar.h>
12377: //#include <windows.h>
12378: //#include <iostream>
12379: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12380:
12381: LPFN_ISWOW64PROCESS fnIsWow64Process;
12382:
12383: BOOL IsWow64()
12384: {
12385: BOOL bIsWow64 = FALSE;
12386:
12387: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12388: // (HANDLE, PBOOL);
12389:
12390: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12391:
12392: HMODULE module = GetModuleHandle(_T("kernel32"));
12393: const char funcName[] = "IsWow64Process";
12394: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12395: GetProcAddress(module, funcName);
12396:
12397: if (NULL != fnIsWow64Process)
12398: {
12399: if (!fnIsWow64Process(GetCurrentProcess(),
12400: &bIsWow64))
12401: //throw std::exception("Unknown error");
12402: printf("Unknown error\n");
12403: }
12404: return bIsWow64 != FALSE;
12405: }
12406: #endif
1.177 brouard 12407:
1.191 brouard 12408: void syscompilerinfo(int logged)
1.292 brouard 12409: {
12410: #include <stdint.h>
12411:
12412: /* #include "syscompilerinfo.h"*/
1.185 brouard 12413: /* command line Intel compiler 32bit windows, XP compatible:*/
12414: /* /GS /W3 /Gy
12415: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12416: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12417: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12418: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12419: */
12420: /* 64 bits */
1.185 brouard 12421: /*
12422: /GS /W3 /Gy
12423: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12424: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12425: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12426: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12427: /* Optimization are useless and O3 is slower than O2 */
12428: /*
12429: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12430: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12431: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12432: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12433: */
1.186 brouard 12434: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12435: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12436: /PDB:"visual studio
12437: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12438: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12439: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12440: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12441: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12442: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12443: uiAccess='false'"
12444: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12445: /NOLOGO /TLBID:1
12446: */
1.292 brouard 12447:
12448:
1.177 brouard 12449: #if defined __INTEL_COMPILER
1.178 brouard 12450: #if defined(__GNUC__)
12451: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12452: #endif
1.177 brouard 12453: #elif defined(__GNUC__)
1.179 brouard 12454: #ifndef __APPLE__
1.174 brouard 12455: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12456: #endif
1.177 brouard 12457: struct utsname sysInfo;
1.178 brouard 12458: int cross = CROSS;
12459: if (cross){
12460: printf("Cross-");
1.191 brouard 12461: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12462: }
1.174 brouard 12463: #endif
12464:
1.191 brouard 12465: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12466: #if defined(__clang__)
1.191 brouard 12467: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12468: #endif
12469: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12470: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12471: #endif
12472: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12473: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12474: #endif
12475: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12476: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12477: #endif
12478: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12479: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12480: #endif
12481: #if defined(_MSC_VER)
1.191 brouard 12482: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12483: #endif
12484: #if defined(__PGI)
1.191 brouard 12485: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12486: #endif
12487: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12488: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12489: #endif
1.191 brouard 12490: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12491:
1.167 brouard 12492: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12493: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12494: // Windows (x64 and x86)
1.191 brouard 12495: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12496: #elif __unix__ // all unices, not all compilers
12497: // Unix
1.191 brouard 12498: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12499: #elif __linux__
12500: // linux
1.191 brouard 12501: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12502: #elif __APPLE__
1.174 brouard 12503: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12504: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12505: #endif
12506:
12507: /* __MINGW32__ */
12508: /* __CYGWIN__ */
12509: /* __MINGW64__ */
12510: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12511: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12512: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12513: /* _WIN64 // Defined for applications for Win64. */
12514: /* _M_X64 // Defined for compilations that target x64 processors. */
12515: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12516:
1.167 brouard 12517: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12518: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12519: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12520: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12521: #else
1.191 brouard 12522: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12523: #endif
12524:
1.169 brouard 12525: #if defined(__GNUC__)
12526: # if defined(__GNUC_PATCHLEVEL__)
12527: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12528: + __GNUC_MINOR__ * 100 \
12529: + __GNUC_PATCHLEVEL__)
12530: # else
12531: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12532: + __GNUC_MINOR__ * 100)
12533: # endif
1.174 brouard 12534: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12535: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12536:
12537: if (uname(&sysInfo) != -1) {
12538: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12539: 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 12540: }
12541: else
12542: perror("uname() error");
1.179 brouard 12543: //#ifndef __INTEL_COMPILER
12544: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12545: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12546: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12547: #endif
1.169 brouard 12548: #endif
1.172 brouard 12549:
1.286 brouard 12550: // void main ()
1.172 brouard 12551: // {
1.169 brouard 12552: #if defined(_MSC_VER)
1.174 brouard 12553: if (IsWow64()){
1.191 brouard 12554: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12555: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12556: }
12557: else{
1.191 brouard 12558: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12559: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12560: }
1.172 brouard 12561: // printf("\nPress Enter to continue...");
12562: // getchar();
12563: // }
12564:
1.169 brouard 12565: #endif
12566:
1.167 brouard 12567:
1.219 brouard 12568: }
1.136 brouard 12569:
1.219 brouard 12570: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12571: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12572: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12573: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12574: /* double ftolpl = 1.e-10; */
1.180 brouard 12575: double age, agebase, agelim;
1.203 brouard 12576: double tot;
1.180 brouard 12577:
1.202 brouard 12578: strcpy(filerespl,"PL_");
12579: strcat(filerespl,fileresu);
12580: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12581: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12582: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12583: }
1.288 brouard 12584: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12585: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12586: pstamp(ficrespl);
1.288 brouard 12587: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12588: fprintf(ficrespl,"#Age ");
12589: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12590: fprintf(ficrespl,"\n");
1.180 brouard 12591:
1.219 brouard 12592: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12593:
1.219 brouard 12594: agebase=ageminpar;
12595: agelim=agemaxpar;
1.180 brouard 12596:
1.227 brouard 12597: /* i1=pow(2,ncoveff); */
1.234 brouard 12598: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12599: if (cptcovn < 1){i1=1;}
1.180 brouard 12600:
1.337 brouard 12601: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12602: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12603: k=TKresult[nres];
1.338 brouard 12604: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12605: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12606: /* continue; */
1.235 brouard 12607:
1.238 brouard 12608: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12609: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12610: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12611: /* k=k+1; */
12612: /* to clean */
1.332 brouard 12613: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12614: fprintf(ficrespl,"#******");
12615: printf("#******");
12616: fprintf(ficlog,"#******");
1.337 brouard 12617: 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 12618: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12619: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12620: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12621: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12622: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12623: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12624: }
12625: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12626: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12627: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12628: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12629: /* } */
1.238 brouard 12630: fprintf(ficrespl,"******\n");
12631: printf("******\n");
12632: fprintf(ficlog,"******\n");
12633: if(invalidvarcomb[k]){
12634: printf("\nCombination (%d) ignored because no case \n",k);
12635: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12636: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12637: continue;
12638: }
1.219 brouard 12639:
1.238 brouard 12640: fprintf(ficrespl,"#Age ");
1.337 brouard 12641: /* for(j=1;j<=cptcoveff;j++) { */
12642: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12643: /* } */
12644: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12645: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12646: }
12647: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12648: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12649:
1.238 brouard 12650: for (age=agebase; age<=agelim; age++){
12651: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12652: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12653: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12654: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12655: /* for(j=1;j<=cptcoveff;j++) */
12656: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12657: for(j=1;j<=cptcovs;j++)
12658: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12659: tot=0.;
12660: for(i=1; i<=nlstate;i++){
12661: tot += prlim[i][i];
12662: fprintf(ficrespl," %.5f", prlim[i][i]);
12663: }
12664: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12665: } /* Age */
12666: /* was end of cptcod */
1.337 brouard 12667: } /* nres */
12668: /* } /\* for each combination *\/ */
1.219 brouard 12669: return 0;
1.180 brouard 12670: }
12671:
1.218 brouard 12672: 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 12673: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12674:
12675: /* Computes the back prevalence limit for any combination of covariate values
12676: * at any age between ageminpar and agemaxpar
12677: */
1.235 brouard 12678: int i, j, k, i1, nres=0 ;
1.217 brouard 12679: /* double ftolpl = 1.e-10; */
12680: double age, agebase, agelim;
12681: double tot;
1.218 brouard 12682: /* double ***mobaverage; */
12683: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12684:
12685: strcpy(fileresplb,"PLB_");
12686: strcat(fileresplb,fileresu);
12687: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12688: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12689: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12690: }
1.288 brouard 12691: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12692: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12693: pstamp(ficresplb);
1.288 brouard 12694: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12695: fprintf(ficresplb,"#Age ");
12696: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12697: fprintf(ficresplb,"\n");
12698:
1.218 brouard 12699:
12700: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12701:
12702: agebase=ageminpar;
12703: agelim=agemaxpar;
12704:
12705:
1.227 brouard 12706: i1=pow(2,cptcoveff);
1.218 brouard 12707: if (cptcovn < 1){i1=1;}
1.227 brouard 12708:
1.238 brouard 12709: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12710: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12711: k=TKresult[nres];
12712: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12713: /* if(i1 != 1 && TKresult[nres]!= k) */
12714: /* continue; */
12715: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12716: fprintf(ficresplb,"#******");
12717: printf("#******");
12718: fprintf(ficlog,"#******");
1.338 brouard 12719: 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) */
12720: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12721: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12722: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12723: }
1.338 brouard 12724: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12725: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12726: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12727: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12728: /* } */
12729: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12730: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12731: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12732: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12733: /* } */
1.238 brouard 12734: fprintf(ficresplb,"******\n");
12735: printf("******\n");
12736: fprintf(ficlog,"******\n");
12737: if(invalidvarcomb[k]){
12738: printf("\nCombination (%d) ignored because no cases \n",k);
12739: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12740: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12741: continue;
12742: }
1.218 brouard 12743:
1.238 brouard 12744: fprintf(ficresplb,"#Age ");
1.338 brouard 12745: for(j=1;j<=cptcovs;j++) {
12746: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12747: }
12748: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12749: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12750:
12751:
1.238 brouard 12752: for (age=agebase; age<=agelim; age++){
12753: /* for (age=agebase; age<=agebase; age++){ */
12754: if(mobilavproj > 0){
12755: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12756: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12757: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12758: }else if (mobilavproj == 0){
12759: 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);
12760: 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);
12761: exit(1);
12762: }else{
12763: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12764: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12765: /* printf("TOTOT\n"); */
12766: /* exit(1); */
1.238 brouard 12767: }
12768: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12769: for(j=1;j<=cptcovs;j++)
12770: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12771: tot=0.;
12772: for(i=1; i<=nlstate;i++){
12773: tot += bprlim[i][i];
12774: fprintf(ficresplb," %.5f", bprlim[i][i]);
12775: }
12776: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12777: } /* Age */
12778: /* was end of cptcod */
1.255 brouard 12779: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12780: /* } /\* end of any combination *\/ */
1.238 brouard 12781: } /* end of nres */
1.218 brouard 12782: /* hBijx(p, bage, fage); */
12783: /* fclose(ficrespijb); */
12784:
12785: return 0;
1.217 brouard 12786: }
1.218 brouard 12787:
1.180 brouard 12788: int hPijx(double *p, int bage, int fage){
12789: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12790: /* to be optimized with precov */
1.180 brouard 12791: int stepsize;
12792: int agelim;
12793: int hstepm;
12794: int nhstepm;
1.235 brouard 12795: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12796:
12797: double agedeb;
12798: double ***p3mat;
12799:
1.337 brouard 12800: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12801: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12802: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12803: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12804: }
12805: printf("Computing pij: result on file '%s' \n", filerespij);
12806: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12807:
12808: stepsize=(int) (stepm+YEARM-1)/YEARM;
12809: /*if (stepm<=24) stepsize=2;*/
12810:
12811: agelim=AGESUP;
12812: hstepm=stepsize*YEARM; /* Every year of age */
12813: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12814:
12815: /* hstepm=1; aff par mois*/
12816: pstamp(ficrespij);
12817: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12818: i1= pow(2,cptcoveff);
12819: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12820: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12821: /* k=k+1; */
12822: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12823: k=TKresult[nres];
1.338 brouard 12824: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12825: /* for(k=1; k<=i1;k++){ */
12826: /* if(i1 != 1 && TKresult[nres]!= k) */
12827: /* continue; */
12828: fprintf(ficrespij,"\n#****** ");
12829: for(j=1;j<=cptcovs;j++){
12830: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12831: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12832: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12833: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12834: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12835: }
12836: fprintf(ficrespij,"******\n");
12837:
12838: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12839: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12840: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12841:
12842: /* nhstepm=nhstepm*YEARM; aff par mois*/
12843:
12844: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12845: oldm=oldms;savm=savms;
12846: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12847: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12848: for(i=1; i<=nlstate;i++)
12849: for(j=1; j<=nlstate+ndeath;j++)
12850: fprintf(ficrespij," %1d-%1d",i,j);
12851: fprintf(ficrespij,"\n");
12852: for (h=0; h<=nhstepm; h++){
12853: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12854: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12855: for(i=1; i<=nlstate;i++)
12856: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12857: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12858: fprintf(ficrespij,"\n");
12859: }
1.337 brouard 12860: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12861: fprintf(ficrespij,"\n");
1.180 brouard 12862: }
1.337 brouard 12863: }
12864: /*}*/
12865: return 0;
1.180 brouard 12866: }
1.218 brouard 12867:
12868: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12869: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12870: /* To be optimized with precov */
1.217 brouard 12871: int stepsize;
1.218 brouard 12872: /* int agelim; */
12873: int ageminl;
1.217 brouard 12874: int hstepm;
12875: int nhstepm;
1.238 brouard 12876: int h, i, i1, j, k, nres;
1.218 brouard 12877:
1.217 brouard 12878: double agedeb;
12879: double ***p3mat;
1.218 brouard 12880:
12881: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12882: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12883: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12884: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12885: }
12886: printf("Computing pij back: result on file '%s' \n", filerespijb);
12887: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12888:
12889: stepsize=(int) (stepm+YEARM-1)/YEARM;
12890: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12891:
1.218 brouard 12892: /* agelim=AGESUP; */
1.289 brouard 12893: ageminl=AGEINF; /* was 30 */
1.218 brouard 12894: hstepm=stepsize*YEARM; /* Every year of age */
12895: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12896:
12897: /* hstepm=1; aff par mois*/
12898: pstamp(ficrespijb);
1.255 brouard 12899: 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 12900: i1= pow(2,cptcoveff);
1.218 brouard 12901: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12902: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12903: /* k=k+1; */
1.238 brouard 12904: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12905: k=TKresult[nres];
1.338 brouard 12906: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12907: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12908: /* if(i1 != 1 && TKresult[nres]!= k) */
12909: /* continue; */
12910: fprintf(ficrespijb,"\n#****** ");
12911: for(j=1;j<=cptcovs;j++){
1.338 brouard 12912: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12913: /* for(j=1;j<=cptcoveff;j++) */
12914: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12915: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12916: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12917: }
12918: fprintf(ficrespijb,"******\n");
12919: if(invalidvarcomb[k]){ /* Is it necessary here? */
12920: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12921: continue;
12922: }
12923:
12924: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12925: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12926: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12927: 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 */
12928: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12929:
12930: /* nhstepm=nhstepm*YEARM; aff par mois*/
12931:
12932: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12933: /* and memory limitations if stepm is small */
12934:
12935: /* oldm=oldms;savm=savms; */
12936: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12937: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12938: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12939: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12940: for(i=1; i<=nlstate;i++)
12941: for(j=1; j<=nlstate+ndeath;j++)
12942: fprintf(ficrespijb," %1d-%1d",i,j);
12943: fprintf(ficrespijb,"\n");
12944: for (h=0; h<=nhstepm; h++){
12945: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12946: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12947: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12948: for(i=1; i<=nlstate;i++)
12949: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12950: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12951: fprintf(ficrespijb,"\n");
1.337 brouard 12952: }
12953: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12954: fprintf(ficrespijb,"\n");
12955: } /* end age deb */
12956: /* } /\* end combination *\/ */
1.238 brouard 12957: } /* end nres */
1.218 brouard 12958: return 0;
12959: } /* hBijx */
1.217 brouard 12960:
1.180 brouard 12961:
1.136 brouard 12962: /***********************************************/
12963: /**************** Main Program *****************/
12964: /***********************************************/
12965:
12966: int main(int argc, char *argv[])
12967: {
12968: #ifdef GSL
12969: const gsl_multimin_fminimizer_type *T;
12970: size_t iteri = 0, it;
12971: int rval = GSL_CONTINUE;
12972: int status = GSL_SUCCESS;
12973: double ssval;
12974: #endif
12975: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12976: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12977: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12978: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12979: int jj, ll, li, lj, lk;
1.136 brouard 12980: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12981: int num_filled;
1.136 brouard 12982: int itimes;
12983: int NDIM=2;
12984: int vpopbased=0;
1.235 brouard 12985: int nres=0;
1.258 brouard 12986: int endishere=0;
1.277 brouard 12987: int noffset=0;
1.274 brouard 12988: int ncurrv=0; /* Temporary variable */
12989:
1.164 brouard 12990: char ca[32], cb[32];
1.136 brouard 12991: /* FILE *fichtm; *//* Html File */
12992: /* FILE *ficgp;*/ /*Gnuplot File */
12993: struct stat info;
1.191 brouard 12994: double agedeb=0.;
1.194 brouard 12995:
12996: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 12997: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 12998:
1.165 brouard 12999: double fret;
1.191 brouard 13000: double dum=0.; /* Dummy variable */
1.136 brouard 13001: double ***p3mat;
1.218 brouard 13002: /* double ***mobaverage; */
1.319 brouard 13003: double wald;
1.164 brouard 13004:
1.351 brouard 13005: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 13006: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
13007:
1.234 brouard 13008: char modeltemp[MAXLINE];
1.332 brouard 13009: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 13010:
1.136 brouard 13011: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 13012: char *tok, *val; /* pathtot */
1.334 brouard 13013: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 13014: int c, h , cpt, c2;
1.191 brouard 13015: int jl=0;
13016: int i1, j1, jk, stepsize=0;
1.194 brouard 13017: int count=0;
13018:
1.164 brouard 13019: int *tab;
1.136 brouard 13020: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 13021: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
13022: /* double anprojf, mprojf, jprojf; */
13023: /* double jintmean,mintmean,aintmean; */
13024: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13025: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13026: double yrfproj= 10.0; /* Number of years of forward projections */
13027: double yrbproj= 10.0; /* Number of years of backward projections */
13028: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 13029: int mobilav=0,popforecast=0;
1.191 brouard 13030: int hstepm=0, nhstepm=0;
1.136 brouard 13031: int agemortsup;
13032: float sumlpop=0.;
13033: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
13034: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
13035:
1.191 brouard 13036: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 13037: double ftolpl=FTOL;
13038: double **prlim;
1.217 brouard 13039: double **bprlim;
1.317 brouard 13040: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
13041: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 13042: double ***paramstart; /* Matrix of starting parameter values */
13043: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 13044: double **matcov; /* Matrix of covariance */
1.203 brouard 13045: double **hess; /* Hessian matrix */
1.136 brouard 13046: double ***delti3; /* Scale */
13047: double *delti; /* Scale */
13048: double ***eij, ***vareij;
13049: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 13050:
1.136 brouard 13051: double *epj, vepp;
1.164 brouard 13052:
1.273 brouard 13053: double dateprev1, dateprev2;
1.296 brouard 13054: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
13055: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
13056:
1.217 brouard 13057:
1.136 brouard 13058: double **ximort;
1.145 brouard 13059: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 13060: int *dcwave;
13061:
1.164 brouard 13062: char z[1]="c";
1.136 brouard 13063:
13064: /*char *strt;*/
13065: char strtend[80];
1.126 brouard 13066:
1.164 brouard 13067:
1.126 brouard 13068: /* setlocale (LC_ALL, ""); */
13069: /* bindtextdomain (PACKAGE, LOCALEDIR); */
13070: /* textdomain (PACKAGE); */
13071: /* setlocale (LC_CTYPE, ""); */
13072: /* setlocale (LC_MESSAGES, ""); */
13073:
13074: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 13075: rstart_time = time(NULL);
13076: /* (void) gettimeofday(&start_time,&tzp);*/
13077: start_time = *localtime(&rstart_time);
1.126 brouard 13078: curr_time=start_time;
1.157 brouard 13079: /*tml = *localtime(&start_time.tm_sec);*/
13080: /* strcpy(strstart,asctime(&tml)); */
13081: strcpy(strstart,asctime(&start_time));
1.126 brouard 13082:
13083: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13084: /* tp.tm_sec = tp.tm_sec +86400; */
13085: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13086: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13087: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13088: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13089: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13090: /* strt=asctime(&tmg); */
13091: /* printf("Time(after) =%s",strstart); */
13092: /* (void) time (&time_value);
13093: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13094: * tm = *localtime(&time_value);
13095: * strstart=asctime(&tm);
13096: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13097: */
13098:
13099: nberr=0; /* Number of errors and warnings */
13100: nbwarn=0;
1.184 brouard 13101: #ifdef WIN32
13102: _getcwd(pathcd, size);
13103: #else
1.126 brouard 13104: getcwd(pathcd, size);
1.184 brouard 13105: #endif
1.191 brouard 13106: syscompilerinfo(0);
1.196 brouard 13107: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13108: if(argc <=1){
13109: printf("\nEnter the parameter file name: ");
1.205 brouard 13110: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13111: printf("ERROR Empty parameter file name\n");
13112: goto end;
13113: }
1.126 brouard 13114: i=strlen(pathr);
13115: if(pathr[i-1]=='\n')
13116: pathr[i-1]='\0';
1.156 brouard 13117: i=strlen(pathr);
1.205 brouard 13118: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13119: pathr[i-1]='\0';
1.205 brouard 13120: }
13121: i=strlen(pathr);
13122: if( i==0 ){
13123: printf("ERROR Empty parameter file name\n");
13124: goto end;
13125: }
13126: for (tok = pathr; tok != NULL; ){
1.126 brouard 13127: printf("Pathr |%s|\n",pathr);
13128: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13129: printf("val= |%s| pathr=%s\n",val,pathr);
13130: strcpy (pathtot, val);
13131: if(pathr[0] == '\0') break; /* Dirty */
13132: }
13133: }
1.281 brouard 13134: else if (argc<=2){
13135: strcpy(pathtot,argv[1]);
13136: }
1.126 brouard 13137: else{
13138: strcpy(pathtot,argv[1]);
1.281 brouard 13139: strcpy(z,argv[2]);
13140: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13141: }
13142: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13143: /*cygwin_split_path(pathtot,path,optionfile);
13144: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13145: /* cutv(path,optionfile,pathtot,'\\');*/
13146:
13147: /* Split argv[0], imach program to get pathimach */
13148: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13149: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13150: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13151: /* strcpy(pathimach,argv[0]); */
13152: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13153: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13154: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13155: #ifdef WIN32
13156: _chdir(path); /* Can be a relative path */
13157: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13158: #else
1.126 brouard 13159: chdir(path); /* Can be a relative path */
1.184 brouard 13160: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13161: #endif
13162: printf("Current directory %s!\n",pathcd);
1.126 brouard 13163: strcpy(command,"mkdir ");
13164: strcat(command,optionfilefiname);
13165: if((outcmd=system(command)) != 0){
1.169 brouard 13166: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13167: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13168: /* fclose(ficlog); */
13169: /* exit(1); */
13170: }
13171: /* if((imk=mkdir(optionfilefiname))<0){ */
13172: /* perror("mkdir"); */
13173: /* } */
13174:
13175: /*-------- arguments in the command line --------*/
13176:
1.186 brouard 13177: /* Main Log file */
1.126 brouard 13178: strcat(filelog, optionfilefiname);
13179: strcat(filelog,".log"); /* */
13180: if((ficlog=fopen(filelog,"w"))==NULL) {
13181: printf("Problem with logfile %s\n",filelog);
13182: goto end;
13183: }
13184: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13185: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13186: fprintf(ficlog,"\nEnter the parameter file name: \n");
13187: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13188: path=%s \n\
13189: optionfile=%s\n\
13190: optionfilext=%s\n\
1.156 brouard 13191: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13192:
1.197 brouard 13193: syscompilerinfo(1);
1.167 brouard 13194:
1.126 brouard 13195: printf("Local time (at start):%s",strstart);
13196: fprintf(ficlog,"Local time (at start): %s",strstart);
13197: fflush(ficlog);
13198: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13199: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13200:
13201: /* */
13202: strcpy(fileres,"r");
13203: strcat(fileres, optionfilefiname);
1.201 brouard 13204: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13205: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13206: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13207:
1.186 brouard 13208: /* Main ---------arguments file --------*/
1.126 brouard 13209:
13210: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13211: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13212: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13213: fflush(ficlog);
1.149 brouard 13214: /* goto end; */
13215: exit(70);
1.126 brouard 13216: }
13217:
13218: strcpy(filereso,"o");
1.201 brouard 13219: strcat(filereso,fileresu);
1.126 brouard 13220: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13221: printf("Problem with Output resultfile: %s\n", filereso);
13222: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13223: fflush(ficlog);
13224: goto end;
13225: }
1.278 brouard 13226: /*-------- Rewriting parameter file ----------*/
13227: strcpy(rfileres,"r"); /* "Rparameterfile */
13228: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13229: strcat(rfileres,"."); /* */
13230: strcat(rfileres,optionfilext); /* Other files have txt extension */
13231: if((ficres =fopen(rfileres,"w"))==NULL) {
13232: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13233: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13234: fflush(ficlog);
13235: goto end;
13236: }
13237: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13238:
1.278 brouard 13239:
1.126 brouard 13240: /* Reads comments: lines beginning with '#' */
13241: numlinepar=0;
1.277 brouard 13242: /* Is it a BOM UTF-8 Windows file? */
13243: /* First parameter line */
1.197 brouard 13244: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13245: noffset=0;
13246: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13247: {
13248: noffset=noffset+3;
13249: printf("# File is an UTF8 Bom.\n"); // 0xBF
13250: }
1.302 brouard 13251: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13252: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13253: {
13254: noffset=noffset+2;
13255: printf("# File is an UTF16BE BOM file\n");
13256: }
13257: else if( line[0] == 0 && line[1] == 0)
13258: {
13259: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13260: noffset=noffset+4;
13261: printf("# File is an UTF16BE BOM file\n");
13262: }
13263: } else{
13264: ;/*printf(" Not a BOM file\n");*/
13265: }
13266:
1.197 brouard 13267: /* If line starts with a # it is a comment */
1.277 brouard 13268: if (line[noffset] == '#') {
1.197 brouard 13269: numlinepar++;
13270: fputs(line,stdout);
13271: fputs(line,ficparo);
1.278 brouard 13272: fputs(line,ficres);
1.197 brouard 13273: fputs(line,ficlog);
13274: continue;
13275: }else
13276: break;
13277: }
13278: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13279: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13280: if (num_filled != 5) {
13281: printf("Should be 5 parameters\n");
1.283 brouard 13282: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13283: }
1.126 brouard 13284: numlinepar++;
1.197 brouard 13285: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13286: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13287: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13288: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13289: }
13290: /* Second parameter line */
13291: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13292: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13293: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13294: if (line[0] == '#') {
13295: numlinepar++;
1.283 brouard 13296: printf("%s",line);
13297: fprintf(ficres,"%s",line);
13298: fprintf(ficparo,"%s",line);
13299: fprintf(ficlog,"%s",line);
1.197 brouard 13300: continue;
13301: }else
13302: break;
13303: }
1.223 brouard 13304: 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", \
13305: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13306: if (num_filled != 11) {
13307: 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 13308: printf("but line=%s\n",line);
1.283 brouard 13309: 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");
13310: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13311: }
1.286 brouard 13312: if( lastpass > maxwav){
13313: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13314: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13315: fflush(ficlog);
13316: goto end;
13317: }
13318: 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 13319: 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 13320: 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 13321: 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 13322: }
1.203 brouard 13323: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13324: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13325: /* Third parameter line */
13326: while(fgets(line, MAXLINE, ficpar)) {
13327: /* If line starts with a # it is a comment */
13328: if (line[0] == '#') {
13329: numlinepar++;
1.283 brouard 13330: printf("%s",line);
13331: fprintf(ficres,"%s",line);
13332: fprintf(ficparo,"%s",line);
13333: fprintf(ficlog,"%s",line);
1.197 brouard 13334: continue;
13335: }else
13336: break;
13337: }
1.351 brouard 13338: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
13339: if (num_filled != 1){
13340: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13341: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13342: model[0]='\0';
13343: goto end;
13344: }else{
13345: trimbtab(linetmp,line); /* Trims multiple blanks in line */
13346: strcpy(line, linetmp);
13347: }
13348: }
13349: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 13350: if (num_filled != 1){
1.302 brouard 13351: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13352: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13353: model[0]='\0';
13354: goto end;
13355: }
13356: else{
13357: if (model[0]=='+'){
13358: for(i=1; i<=strlen(model);i++)
13359: modeltemp[i-1]=model[i];
1.201 brouard 13360: strcpy(model,modeltemp);
1.197 brouard 13361: }
13362: }
1.338 brouard 13363: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13364: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13365: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13366: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13367: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13368: }
13369: /* 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); */
13370: /* numlinepar=numlinepar+3; /\* In general *\/ */
13371: /* 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 13372: /* 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); */
13373: /* 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 13374: fflush(ficlog);
1.190 brouard 13375: /* if(model[0]=='#'|| model[0]== '\0'){ */
13376: if(model[0]=='#'){
1.279 brouard 13377: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13378: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13379: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13380: if(mle != -1){
1.279 brouard 13381: 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 13382: exit(1);
13383: }
13384: }
1.126 brouard 13385: while((c=getc(ficpar))=='#' && c!= EOF){
13386: ungetc(c,ficpar);
13387: fgets(line, MAXLINE, ficpar);
13388: numlinepar++;
1.195 brouard 13389: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13390: z[0]=line[1];
1.342 brouard 13391: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13392: debugILK=1;printf("DebugILK\n");
1.195 brouard 13393: }
13394: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13395: fputs(line, stdout);
13396: //puts(line);
1.126 brouard 13397: fputs(line,ficparo);
13398: fputs(line,ficlog);
13399: }
13400: ungetc(c,ficpar);
13401:
13402:
1.290 brouard 13403: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13404: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13405: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13406: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13407: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13408: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13409: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13410: v1+v2*age+v2*v3 makes cptcovn = 3
13411: */
13412: if (strlen(model)>1)
1.187 brouard 13413: 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 13414: else
1.187 brouard 13415: ncovmodel=2; /* Constant and age */
1.133 brouard 13416: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13417: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13418: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13419: 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);
13420: 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);
13421: fflush(stdout);
13422: fclose (ficlog);
13423: goto end;
13424: }
1.126 brouard 13425: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13426: delti=delti3[1][1];
13427: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13428: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13429: /* We could also provide initial parameters values giving by simple logistic regression
13430: * only one way, that is without matrix product. We will have nlstate maximizations */
13431: /* for(i=1;i<nlstate;i++){ */
13432: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13433: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13434: /* } */
1.126 brouard 13435: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13436: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13437: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13438: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13439: fclose (ficparo);
13440: fclose (ficlog);
13441: goto end;
13442: exit(0);
1.220 brouard 13443: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13444: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13445: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13446: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13447: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13448: matcov=matrix(1,npar,1,npar);
1.203 brouard 13449: hess=matrix(1,npar,1,npar);
1.220 brouard 13450: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13451: /* Read guessed parameters */
1.126 brouard 13452: /* Reads comments: lines beginning with '#' */
13453: while((c=getc(ficpar))=='#' && c!= EOF){
13454: ungetc(c,ficpar);
13455: fgets(line, MAXLINE, ficpar);
13456: numlinepar++;
1.141 brouard 13457: fputs(line,stdout);
1.126 brouard 13458: fputs(line,ficparo);
13459: fputs(line,ficlog);
13460: }
13461: ungetc(c,ficpar);
13462:
13463: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13464: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13465: for(i=1; i <=nlstate; i++){
1.234 brouard 13466: j=0;
1.126 brouard 13467: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13468: if(jj==i) continue;
13469: j++;
1.292 brouard 13470: while((c=getc(ficpar))=='#' && c!= EOF){
13471: ungetc(c,ficpar);
13472: fgets(line, MAXLINE, ficpar);
13473: numlinepar++;
13474: fputs(line,stdout);
13475: fputs(line,ficparo);
13476: fputs(line,ficlog);
13477: }
13478: ungetc(c,ficpar);
1.234 brouard 13479: fscanf(ficpar,"%1d%1d",&i1,&j1);
13480: if ((i1 != i) || (j1 != jj)){
13481: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13482: It might be a problem of design; if ncovcol and the model are correct\n \
13483: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13484: exit(1);
13485: }
13486: fprintf(ficparo,"%1d%1d",i1,j1);
13487: if(mle==1)
13488: printf("%1d%1d",i,jj);
13489: fprintf(ficlog,"%1d%1d",i,jj);
13490: for(k=1; k<=ncovmodel;k++){
13491: fscanf(ficpar," %lf",¶m[i][j][k]);
13492: if(mle==1){
13493: printf(" %lf",param[i][j][k]);
13494: fprintf(ficlog," %lf",param[i][j][k]);
13495: }
13496: else
13497: fprintf(ficlog," %lf",param[i][j][k]);
13498: fprintf(ficparo," %lf",param[i][j][k]);
13499: }
13500: fscanf(ficpar,"\n");
13501: numlinepar++;
13502: if(mle==1)
13503: printf("\n");
13504: fprintf(ficlog,"\n");
13505: fprintf(ficparo,"\n");
1.126 brouard 13506: }
13507: }
13508: fflush(ficlog);
1.234 brouard 13509:
1.251 brouard 13510: /* Reads parameters values */
1.126 brouard 13511: p=param[1][1];
1.251 brouard 13512: pstart=paramstart[1][1];
1.126 brouard 13513:
13514: /* Reads comments: lines beginning with '#' */
13515: while((c=getc(ficpar))=='#' && c!= EOF){
13516: ungetc(c,ficpar);
13517: fgets(line, MAXLINE, ficpar);
13518: numlinepar++;
1.141 brouard 13519: fputs(line,stdout);
1.126 brouard 13520: fputs(line,ficparo);
13521: fputs(line,ficlog);
13522: }
13523: ungetc(c,ficpar);
13524:
13525: for(i=1; i <=nlstate; i++){
13526: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13527: fscanf(ficpar,"%1d%1d",&i1,&j1);
13528: if ( (i1-i) * (j1-j) != 0){
13529: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13530: exit(1);
13531: }
13532: printf("%1d%1d",i,j);
13533: fprintf(ficparo,"%1d%1d",i1,j1);
13534: fprintf(ficlog,"%1d%1d",i1,j1);
13535: for(k=1; k<=ncovmodel;k++){
13536: fscanf(ficpar,"%le",&delti3[i][j][k]);
13537: printf(" %le",delti3[i][j][k]);
13538: fprintf(ficparo," %le",delti3[i][j][k]);
13539: fprintf(ficlog," %le",delti3[i][j][k]);
13540: }
13541: fscanf(ficpar,"\n");
13542: numlinepar++;
13543: printf("\n");
13544: fprintf(ficparo,"\n");
13545: fprintf(ficlog,"\n");
1.126 brouard 13546: }
13547: }
13548: fflush(ficlog);
1.234 brouard 13549:
1.145 brouard 13550: /* Reads covariance matrix */
1.126 brouard 13551: delti=delti3[1][1];
1.220 brouard 13552:
13553:
1.126 brouard 13554: /* 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 13555:
1.126 brouard 13556: /* Reads comments: lines beginning with '#' */
13557: while((c=getc(ficpar))=='#' && c!= EOF){
13558: ungetc(c,ficpar);
13559: fgets(line, MAXLINE, ficpar);
13560: numlinepar++;
1.141 brouard 13561: fputs(line,stdout);
1.126 brouard 13562: fputs(line,ficparo);
13563: fputs(line,ficlog);
13564: }
13565: ungetc(c,ficpar);
1.220 brouard 13566:
1.126 brouard 13567: matcov=matrix(1,npar,1,npar);
1.203 brouard 13568: hess=matrix(1,npar,1,npar);
1.131 brouard 13569: for(i=1; i <=npar; i++)
13570: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13571:
1.194 brouard 13572: /* Scans npar lines */
1.126 brouard 13573: for(i=1; i <=npar; i++){
1.226 brouard 13574: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13575: if(count != 3){
1.226 brouard 13576: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13577: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13578: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13579: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13580: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13581: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13582: exit(1);
1.220 brouard 13583: }else{
1.226 brouard 13584: if(mle==1)
13585: printf("%1d%1d%d",i1,j1,jk);
13586: }
13587: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13588: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13589: for(j=1; j <=i; j++){
1.226 brouard 13590: fscanf(ficpar," %le",&matcov[i][j]);
13591: if(mle==1){
13592: printf(" %.5le",matcov[i][j]);
13593: }
13594: fprintf(ficlog," %.5le",matcov[i][j]);
13595: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13596: }
13597: fscanf(ficpar,"\n");
13598: numlinepar++;
13599: if(mle==1)
1.220 brouard 13600: printf("\n");
1.126 brouard 13601: fprintf(ficlog,"\n");
13602: fprintf(ficparo,"\n");
13603: }
1.194 brouard 13604: /* End of read covariance matrix npar lines */
1.126 brouard 13605: for(i=1; i <=npar; i++)
13606: for(j=i+1;j<=npar;j++)
1.226 brouard 13607: matcov[i][j]=matcov[j][i];
1.126 brouard 13608:
13609: if(mle==1)
13610: printf("\n");
13611: fprintf(ficlog,"\n");
13612:
13613: fflush(ficlog);
13614:
13615: } /* End of mle != -3 */
1.218 brouard 13616:
1.186 brouard 13617: /* Main data
13618: */
1.290 brouard 13619: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13620: /* num=lvector(1,n); */
13621: /* moisnais=vector(1,n); */
13622: /* annais=vector(1,n); */
13623: /* moisdc=vector(1,n); */
13624: /* andc=vector(1,n); */
13625: /* weight=vector(1,n); */
13626: /* agedc=vector(1,n); */
13627: /* cod=ivector(1,n); */
13628: /* for(i=1;i<=n;i++){ */
13629: num=lvector(firstobs,lastobs);
13630: moisnais=vector(firstobs,lastobs);
13631: annais=vector(firstobs,lastobs);
13632: moisdc=vector(firstobs,lastobs);
13633: andc=vector(firstobs,lastobs);
13634: weight=vector(firstobs,lastobs);
13635: agedc=vector(firstobs,lastobs);
13636: cod=ivector(firstobs,lastobs);
13637: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13638: num[i]=0;
13639: moisnais[i]=0;
13640: annais[i]=0;
13641: moisdc[i]=0;
13642: andc[i]=0;
13643: agedc[i]=0;
13644: cod[i]=0;
13645: weight[i]=1.0; /* Equal weights, 1 by default */
13646: }
1.290 brouard 13647: mint=matrix(1,maxwav,firstobs,lastobs);
13648: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13649: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13650: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13651: tab=ivector(1,NCOVMAX);
1.144 brouard 13652: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13653: 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 13654:
1.136 brouard 13655: /* Reads data from file datafile */
13656: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13657: goto end;
13658:
13659: /* Calculation of the number of parameters from char model */
1.234 brouard 13660: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13661: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13662: k=3 V4 Tvar[k=3]= 4 (from V4)
13663: k=2 V1 Tvar[k=2]= 1 (from V1)
13664: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13665: */
13666:
13667: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13668: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13669: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13670: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13671: TvarsD=ivector(1,NCOVMAX); /* */
13672: TvarsQind=ivector(1,NCOVMAX); /* */
13673: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13674: TvarF=ivector(1,NCOVMAX); /* */
13675: TvarFind=ivector(1,NCOVMAX); /* */
13676: TvarV=ivector(1,NCOVMAX); /* */
13677: TvarVind=ivector(1,NCOVMAX); /* */
13678: TvarA=ivector(1,NCOVMAX); /* */
13679: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13680: TvarFD=ivector(1,NCOVMAX); /* */
13681: TvarFDind=ivector(1,NCOVMAX); /* */
13682: TvarFQ=ivector(1,NCOVMAX); /* */
13683: TvarFQind=ivector(1,NCOVMAX); /* */
13684: TvarVD=ivector(1,NCOVMAX); /* */
13685: TvarVDind=ivector(1,NCOVMAX); /* */
13686: TvarVQ=ivector(1,NCOVMAX); /* */
13687: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13688: TvarVV=ivector(1,NCOVMAX); /* */
13689: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 13690: TvarVVA=ivector(1,NCOVMAX); /* */
13691: TvarVVAind=ivector(1,NCOVMAX); /* */
13692: TvarAVVA=ivector(1,NCOVMAX); /* */
13693: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13694:
1.230 brouard 13695: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13696: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13697: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13698: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13699: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 13700: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
13701: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
13702:
1.137 brouard 13703: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13704: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13705: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13706: */
13707: /* For model-covariate k tells which data-covariate to use but
13708: because this model-covariate is a construction we invent a new column
13709: ncovcol + k1
13710: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13711: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13712: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13713: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13714: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13715: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13716: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13717: */
1.145 brouard 13718: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13719: 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 13720: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13721: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 13722: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 13723: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13724: 4 covariates (3 plus signs)
13725: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13726: */
13727: for(i=1;i<NCOVMAX;i++)
13728: Tage[i]=0;
1.230 brouard 13729: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13730: * individual dummy, fixed or varying:
13731: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13732: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13733: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13734: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13735: * Tmodelind[1]@9={9,0,3,2,}*/
13736: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13737: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13738: * individual quantitative, fixed or varying:
13739: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13740: * 3, 1, 0, 0, 0, 0, 0, 0},
13741: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 13742:
13743: /* Probably useless zeroes */
13744: for(i=1;i<NCOVMAX;i++){
13745: DummyV[i]=0;
13746: FixedV[i]=0;
13747: }
13748:
13749: for(i=1; i <=ncovcol;i++){
13750: DummyV[i]=0;
13751: FixedV[i]=0;
13752: }
13753: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
13754: DummyV[i]=1;
13755: FixedV[i]=0;
13756: }
13757: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
13758: DummyV[i]=0;
13759: FixedV[i]=1;
13760: }
13761: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
13762: DummyV[i]=1;
13763: FixedV[i]=1;
13764: }
13765: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
13766: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13767: 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]);
13768: }
13769:
13770:
13771:
1.186 brouard 13772: /* Main decodemodel */
13773:
1.187 brouard 13774:
1.223 brouard 13775: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13776: goto end;
13777:
1.137 brouard 13778: if((double)(lastobs-imx)/(double)imx > 1.10){
13779: nbwarn++;
13780: 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);
13781: 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);
13782: }
1.136 brouard 13783: /* if(mle==1){*/
1.137 brouard 13784: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13785: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13786: }
13787:
13788: /*-calculation of age at interview from date of interview and age at death -*/
13789: agev=matrix(1,maxwav,1,imx);
13790:
13791: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13792: goto end;
13793:
1.126 brouard 13794:
1.136 brouard 13795: agegomp=(int)agemin;
1.290 brouard 13796: free_vector(moisnais,firstobs,lastobs);
13797: free_vector(annais,firstobs,lastobs);
1.126 brouard 13798: /* free_matrix(mint,1,maxwav,1,n);
13799: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13800: /* free_vector(moisdc,1,n); */
13801: /* free_vector(andc,1,n); */
1.145 brouard 13802: /* */
13803:
1.126 brouard 13804: wav=ivector(1,imx);
1.214 brouard 13805: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13806: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13807: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13808: 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.*/
13809: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13810: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13811:
13812: /* Concatenates waves */
1.214 brouard 13813: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13814: Death is a valid wave (if date is known).
13815: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13816: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13817: and mw[mi+1][i]. dh depends on stepm.
13818: */
13819:
1.126 brouard 13820: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13821: /* Concatenates waves */
1.145 brouard 13822:
1.290 brouard 13823: free_vector(moisdc,firstobs,lastobs);
13824: free_vector(andc,firstobs,lastobs);
1.215 brouard 13825:
1.126 brouard 13826: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13827: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13828: ncodemax[1]=1;
1.145 brouard 13829: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13830: cptcoveff=0;
1.220 brouard 13831: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13832: 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 13833: }
13834:
13835: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13836: invalidvarcomb=ivector(0, ncovcombmax);
13837: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13838: invalidvarcomb[i]=0;
13839:
1.211 brouard 13840: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13841: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13842: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13843:
1.200 brouard 13844: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13845: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13846: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13847: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13848: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13849: * (currently 0 or 1) in the data.
13850: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13851: * corresponding modality (h,j).
13852: */
13853:
1.145 brouard 13854: h=0;
13855: /*if (cptcovn > 0) */
1.126 brouard 13856: m=pow(2,cptcoveff);
13857:
1.144 brouard 13858: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13859: * For k=4 covariates, h goes from 1 to m=2**k
13860: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13861: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13862: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13863: *______________________________ *______________________
13864: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13865: * 2 2 1 1 1 * 1 0 0 0 1
13866: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13867: * 4 2 2 1 1 * 3 0 0 1 1
13868: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13869: * 6 2 1 2 1 * 5 0 1 0 1
13870: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13871: * 8 2 2 2 1 * 7 0 1 1 1
13872: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13873: * 10 2 1 1 2 * 9 1 0 0 1
13874: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13875: * 12 2 2 1 2 * 11 1 0 1 1
13876: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13877: * 14 2 1 2 2 * 13 1 1 0 1
13878: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13879: * 16 2 2 2 2 * 15 1 1 1 1
13880: */
1.212 brouard 13881: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13882: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13883: * and the value of each covariate?
13884: * V1=1, V2=1, V3=2, V4=1 ?
13885: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13886: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13887: * In order to get the real value in the data, we use nbcode
13888: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13889: * We are keeping this crazy system in order to be able (in the future?)
13890: * to have more than 2 values (0 or 1) for a covariate.
13891: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13892: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13893: * bbbbbbbb
13894: * 76543210
13895: * h-1 00000101 (6-1=5)
1.219 brouard 13896: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13897: * &
13898: * 1 00000001 (1)
1.219 brouard 13899: * 00000000 = 1 & ((h-1) >> (k-1))
13900: * +1= 00000001 =1
1.211 brouard 13901: *
13902: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13903: * h' 1101 =2^3+2^2+0x2^1+2^0
13904: * >>k' 11
13905: * & 00000001
13906: * = 00000001
13907: * +1 = 00000010=2 = codtabm(14,3)
13908: * Reverse h=6 and m=16?
13909: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13910: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13911: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13912: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13913: * V3=decodtabm(14,3,2**4)=2
13914: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13915: *(h-1) >> (j-1) 0011 =13 >> 2
13916: * &1 000000001
13917: * = 000000001
13918: * +1= 000000010 =2
13919: * 2211
13920: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13921: * V3=2
1.220 brouard 13922: * codtabm and decodtabm are identical
1.211 brouard 13923: */
13924:
1.145 brouard 13925:
13926: free_ivector(Ndum,-1,NCOVMAX);
13927:
13928:
1.126 brouard 13929:
1.186 brouard 13930: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13931: strcpy(optionfilegnuplot,optionfilefiname);
13932: if(mle==-3)
1.201 brouard 13933: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13934: strcat(optionfilegnuplot,".gp");
13935:
13936: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13937: printf("Problem with file %s",optionfilegnuplot);
13938: }
13939: else{
1.204 brouard 13940: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13941: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13942: //fprintf(ficgp,"set missing 'NaNq'\n");
13943: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13944: }
13945: /* fclose(ficgp);*/
1.186 brouard 13946:
13947:
13948: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13949:
13950: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13951: if(mle==-3)
1.201 brouard 13952: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13953: strcat(optionfilehtm,".htm");
13954: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13955: printf("Problem with %s \n",optionfilehtm);
13956: exit(0);
1.126 brouard 13957: }
13958:
13959: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13960: strcat(optionfilehtmcov,"-cov.htm");
13961: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13962: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13963: }
13964: else{
13965: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13966: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13967: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13968: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13969: }
13970:
1.335 brouard 13971: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13972: <title>IMaCh %s</title></head>\n\
13973: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13974: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13975: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13976: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13977: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13978:
13979: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13980: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13981: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13982: 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 13983: \n\
13984: <hr size=\"2\" color=\"#EC5E5E\">\
13985: <ul><li><h4>Parameter files</h4>\n\
13986: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13987: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13988: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13989: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13990: - Date and time at start: %s</ul>\n",\
1.335 brouard 13991: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13992: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13993: fileres,fileres,\
13994: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13995: fflush(fichtm);
13996:
13997: strcpy(pathr,path);
13998: strcat(pathr,optionfilefiname);
1.184 brouard 13999: #ifdef WIN32
14000: _chdir(optionfilefiname); /* Move to directory named optionfile */
14001: #else
1.126 brouard 14002: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 14003: #endif
14004:
1.126 brouard 14005:
1.220 brouard 14006: /* Calculates basic frequencies. Computes observed prevalence at single age
14007: and for any valid combination of covariates
1.126 brouard 14008: and prints on file fileres'p'. */
1.251 brouard 14009: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 14010: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 14011:
14012: fprintf(fichtm,"\n");
1.286 brouard 14013: 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 14014: ftol, stepm);
14015: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
14016: ncurrv=1;
14017: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
14018: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
14019: ncurrv=i;
14020: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14021: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 14022: ncurrv=i;
14023: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14024: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 14025: ncurrv=i;
14026: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
14027: 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", \
14028: nlstate, ndeath, maxwav, mle, weightopt);
14029:
14030: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
14031: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
14032:
14033:
1.317 brouard 14034: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 14035: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
14036: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 14037: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 14038: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 14039: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14040: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14041: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14042: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 14043:
1.126 brouard 14044: /* For Powell, parameters are in a vector p[] starting at p[1]
14045: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
14046: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
14047:
14048: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 14049: /* For mortality only */
1.126 brouard 14050: if (mle==-3){
1.136 brouard 14051: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 14052: for(i=1;i<=NDIM;i++)
14053: for(j=1;j<=NDIM;j++)
14054: ximort[i][j]=0.;
1.186 brouard 14055: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 14056: cens=ivector(firstobs,lastobs);
14057: ageexmed=vector(firstobs,lastobs);
14058: agecens=vector(firstobs,lastobs);
14059: dcwave=ivector(firstobs,lastobs);
1.223 brouard 14060:
1.126 brouard 14061: for (i=1; i<=imx; i++){
14062: dcwave[i]=-1;
14063: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 14064: if (s[m][i]>nlstate) {
14065: dcwave[i]=m;
14066: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
14067: break;
14068: }
1.126 brouard 14069: }
1.226 brouard 14070:
1.126 brouard 14071: for (i=1; i<=imx; i++) {
14072: if (wav[i]>0){
1.226 brouard 14073: ageexmed[i]=agev[mw[1][i]][i];
14074: j=wav[i];
14075: agecens[i]=1.;
14076:
14077: if (ageexmed[i]> 1 && wav[i] > 0){
14078: agecens[i]=agev[mw[j][i]][i];
14079: cens[i]= 1;
14080: }else if (ageexmed[i]< 1)
14081: cens[i]= -1;
14082: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
14083: cens[i]=0 ;
1.126 brouard 14084: }
14085: else cens[i]=-1;
14086: }
14087:
14088: for (i=1;i<=NDIM;i++) {
14089: for (j=1;j<=NDIM;j++)
1.226 brouard 14090: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 14091: }
14092:
1.302 brouard 14093: p[1]=0.0268; p[NDIM]=0.083;
14094: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14095:
14096:
1.136 brouard 14097: #ifdef GSL
14098: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14099: #else
1.126 brouard 14100: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14101: #endif
1.201 brouard 14102: strcpy(filerespow,"POW-MORT_");
14103: strcat(filerespow,fileresu);
1.126 brouard 14104: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14105: printf("Problem with resultfile: %s\n", filerespow);
14106: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14107: }
1.136 brouard 14108: #ifdef GSL
14109: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14110: #else
1.126 brouard 14111: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14112: #endif
1.126 brouard 14113: /* for (i=1;i<=nlstate;i++)
14114: for(j=1;j<=nlstate+ndeath;j++)
14115: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14116: */
14117: fprintf(ficrespow,"\n");
1.136 brouard 14118: #ifdef GSL
14119: /* gsl starts here */
14120: T = gsl_multimin_fminimizer_nmsimplex;
14121: gsl_multimin_fminimizer *sfm = NULL;
14122: gsl_vector *ss, *x;
14123: gsl_multimin_function minex_func;
14124:
14125: /* Initial vertex size vector */
14126: ss = gsl_vector_alloc (NDIM);
14127:
14128: if (ss == NULL){
14129: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14130: }
14131: /* Set all step sizes to 1 */
14132: gsl_vector_set_all (ss, 0.001);
14133:
14134: /* Starting point */
1.126 brouard 14135:
1.136 brouard 14136: x = gsl_vector_alloc (NDIM);
14137:
14138: if (x == NULL){
14139: gsl_vector_free(ss);
14140: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14141: }
14142:
14143: /* Initialize method and iterate */
14144: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14145: /* gsl_vector_set(x, 0, 0.0268); */
14146: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14147: gsl_vector_set(x, 0, p[1]);
14148: gsl_vector_set(x, 1, p[2]);
14149:
14150: minex_func.f = &gompertz_f;
14151: minex_func.n = NDIM;
14152: minex_func.params = (void *)&p; /* ??? */
14153:
14154: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14155: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14156:
14157: printf("Iterations beginning .....\n\n");
14158: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14159:
14160: iteri=0;
14161: while (rval == GSL_CONTINUE){
14162: iteri++;
14163: status = gsl_multimin_fminimizer_iterate(sfm);
14164:
14165: if (status) printf("error: %s\n", gsl_strerror (status));
14166: fflush(0);
14167:
14168: if (status)
14169: break;
14170:
14171: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14172: ssval = gsl_multimin_fminimizer_size (sfm);
14173:
14174: if (rval == GSL_SUCCESS)
14175: printf ("converged to a local maximum at\n");
14176:
14177: printf("%5d ", iteri);
14178: for (it = 0; it < NDIM; it++){
14179: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14180: }
14181: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14182: }
14183:
14184: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14185:
14186: gsl_vector_free(x); /* initial values */
14187: gsl_vector_free(ss); /* inital step size */
14188: for (it=0; it<NDIM; it++){
14189: p[it+1]=gsl_vector_get(sfm->x,it);
14190: fprintf(ficrespow," %.12lf", p[it]);
14191: }
14192: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14193: #endif
14194: #ifdef POWELL
14195: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14196: #endif
1.126 brouard 14197: fclose(ficrespow);
14198:
1.203 brouard 14199: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14200:
14201: for(i=1; i <=NDIM; i++)
14202: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14203: matcov[i][j]=matcov[j][i];
1.126 brouard 14204:
14205: printf("\nCovariance matrix\n ");
1.203 brouard 14206: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14207: for(i=1; i <=NDIM; i++) {
14208: for(j=1;j<=NDIM;j++){
1.220 brouard 14209: printf("%f ",matcov[i][j]);
14210: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14211: }
1.203 brouard 14212: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14213: }
14214:
14215: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14216: for (i=1;i<=NDIM;i++) {
1.126 brouard 14217: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14218: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14219: }
1.302 brouard 14220: lsurv=vector(agegomp,AGESUP);
14221: lpop=vector(agegomp,AGESUP);
14222: tpop=vector(agegomp,AGESUP);
1.126 brouard 14223: lsurv[agegomp]=100000;
14224:
14225: for (k=agegomp;k<=AGESUP;k++) {
14226: agemortsup=k;
14227: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14228: }
14229:
14230: for (k=agegomp;k<agemortsup;k++)
14231: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14232:
14233: for (k=agegomp;k<agemortsup;k++){
14234: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14235: sumlpop=sumlpop+lpop[k];
14236: }
14237:
14238: tpop[agegomp]=sumlpop;
14239: for (k=agegomp;k<(agemortsup-3);k++){
14240: /* tpop[k+1]=2;*/
14241: tpop[k+1]=tpop[k]-lpop[k];
14242: }
14243:
14244:
14245: printf("\nAge lx qx dx Lx Tx e(x)\n");
14246: for (k=agegomp;k<(agemortsup-2);k++)
14247: 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]);
14248:
14249:
14250: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14251: ageminpar=50;
14252: agemaxpar=100;
1.194 brouard 14253: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14254: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14255: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14256: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
14257: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14258: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14259: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14260: }else{
14261: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14262: 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 14263: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14264: }
1.201 brouard 14265: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14266: stepm, weightopt,\
14267: model,imx,p,matcov,agemortsup);
14268:
1.302 brouard 14269: free_vector(lsurv,agegomp,AGESUP);
14270: free_vector(lpop,agegomp,AGESUP);
14271: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14272: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14273: free_ivector(dcwave,firstobs,lastobs);
14274: free_vector(agecens,firstobs,lastobs);
14275: free_vector(ageexmed,firstobs,lastobs);
14276: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14277: #ifdef GSL
1.136 brouard 14278: #endif
1.186 brouard 14279: } /* Endof if mle==-3 mortality only */
1.205 brouard 14280: /* Standard */
14281: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14282: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14283: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14284: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14285: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14286: for (k=1; k<=npar;k++)
14287: printf(" %d %8.5f",k,p[k]);
14288: printf("\n");
1.205 brouard 14289: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14290: /* mlikeli uses func not funcone */
1.247 brouard 14291: /* for(i=1;i<nlstate;i++){ */
14292: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14293: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14294: /* } */
1.205 brouard 14295: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14296: }
14297: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14298: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14299: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14300: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14301: }
14302: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14303: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14304: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14305: /* exit(0); */
1.126 brouard 14306: for (k=1; k<=npar;k++)
14307: printf(" %d %8.5f",k,p[k]);
14308: printf("\n");
14309:
14310: /*--------- results files --------------*/
1.283 brouard 14311: /* 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 14312:
14313:
14314: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14315: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14316: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14317:
14318: printf("#model= 1 + age ");
14319: fprintf(ficres,"#model= 1 + age ");
14320: fprintf(ficlog,"#model= 1 + age ");
14321: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14322: </ul>", model);
14323:
14324: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14325: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14326: if(nagesqr==1){
14327: printf(" + age*age ");
14328: fprintf(ficres," + age*age ");
14329: fprintf(ficlog," + age*age ");
14330: fprintf(fichtm, "<th>+ age*age</th>");
14331: }
14332: for(j=1;j <=ncovmodel-2;j++){
14333: if(Typevar[j]==0) {
14334: printf(" + V%d ",Tvar[j]);
14335: fprintf(ficres," + V%d ",Tvar[j]);
14336: fprintf(ficlog," + V%d ",Tvar[j]);
14337: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14338: }else if(Typevar[j]==1) {
14339: printf(" + V%d*age ",Tvar[j]);
14340: fprintf(ficres," + V%d*age ",Tvar[j]);
14341: fprintf(ficlog," + V%d*age ",Tvar[j]);
14342: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14343: }else if(Typevar[j]==2) {
14344: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14345: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14346: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14347: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14348: }else if(Typevar[j]==3) { /* TO VERIFY */
14349: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14350: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14351: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14352: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14353: }
14354: }
14355: printf("\n");
14356: fprintf(ficres,"\n");
14357: fprintf(ficlog,"\n");
14358: fprintf(fichtm, "</tr>");
14359: fprintf(fichtm, "\n");
14360:
14361:
1.126 brouard 14362: for(i=1,jk=1; i <=nlstate; i++){
14363: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14364: if (k != i) {
1.319 brouard 14365: fprintf(fichtm, "<tr>");
1.225 brouard 14366: printf("%d%d ",i,k);
14367: fprintf(ficlog,"%d%d ",i,k);
14368: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14369: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14370: for(j=1; j <=ncovmodel; j++){
14371: printf("%12.7f ",p[jk]);
14372: fprintf(ficlog,"%12.7f ",p[jk]);
14373: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14374: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14375: jk++;
14376: }
14377: printf("\n");
14378: fprintf(ficlog,"\n");
14379: fprintf(ficres,"\n");
1.319 brouard 14380: fprintf(fichtm, "</tr>\n");
1.225 brouard 14381: }
1.126 brouard 14382: }
14383: }
1.319 brouard 14384: /* fprintf(fichtm,"</tr>\n"); */
14385: fprintf(fichtm,"</table>\n");
14386: fprintf(fichtm, "\n");
14387:
1.203 brouard 14388: if(mle != 0){
14389: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14390: ftolhess=ftol; /* Usually correct */
1.203 brouard 14391: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14392: 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");
14393: 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 14394: 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 14395: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14396: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14397: if(nagesqr==1){
14398: printf(" + age*age ");
14399: fprintf(ficres," + age*age ");
14400: fprintf(ficlog," + age*age ");
14401: fprintf(fichtm, "<th>+ age*age</th>");
14402: }
14403: for(j=1;j <=ncovmodel-2;j++){
14404: if(Typevar[j]==0) {
14405: printf(" + V%d ",Tvar[j]);
14406: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14407: }else if(Typevar[j]==1) {
14408: printf(" + V%d*age ",Tvar[j]);
14409: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14410: }else if(Typevar[j]==2) {
14411: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14412: }else if(Typevar[j]==3) { /* TO VERIFY */
14413: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14414: }
14415: }
14416: fprintf(fichtm, "</tr>\n");
14417:
1.203 brouard 14418: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14419: for(k=1; k <=(nlstate+ndeath); k++){
14420: if (k != i) {
1.319 brouard 14421: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14422: printf("%d%d ",i,k);
14423: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14424: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14425: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14426: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14427: 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]));
14428: 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 14429: if(fabs(wald) > 1.96){
1.321 brouard 14430: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14431: }else{
14432: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14433: }
1.324 brouard 14434: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14435: 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 14436: jk++;
14437: }
14438: printf("\n");
14439: fprintf(ficlog,"\n");
1.319 brouard 14440: fprintf(fichtm, "</tr>\n");
1.225 brouard 14441: }
14442: }
1.193 brouard 14443: }
1.203 brouard 14444: } /* end of hesscov and Wald tests */
1.319 brouard 14445: fprintf(fichtm,"</table>\n");
1.225 brouard 14446:
1.203 brouard 14447: /* */
1.126 brouard 14448: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14449: printf("# Scales (for hessian or gradient estimation)\n");
14450: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14451: for(i=1,jk=1; i <=nlstate; i++){
14452: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14453: if (j!=i) {
14454: fprintf(ficres,"%1d%1d",i,j);
14455: printf("%1d%1d",i,j);
14456: fprintf(ficlog,"%1d%1d",i,j);
14457: for(k=1; k<=ncovmodel;k++){
14458: printf(" %.5e",delti[jk]);
14459: fprintf(ficlog," %.5e",delti[jk]);
14460: fprintf(ficres," %.5e",delti[jk]);
14461: jk++;
14462: }
14463: printf("\n");
14464: fprintf(ficlog,"\n");
14465: fprintf(ficres,"\n");
14466: }
1.126 brouard 14467: }
14468: }
14469:
14470: 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 14471: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14472: 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");
14473: 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");
14474: /* # 121 Var(a12)\n\ */
14475: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14476: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14477: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14478: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14479: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14480: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14481: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14482:
14483:
14484: /* Just to have a covariance matrix which will be more understandable
14485: even is we still don't want to manage dictionary of variables
14486: */
14487: for(itimes=1;itimes<=2;itimes++){
14488: jj=0;
14489: for(i=1; i <=nlstate; i++){
1.225 brouard 14490: for(j=1; j <=nlstate+ndeath; j++){
14491: if(j==i) continue;
14492: for(k=1; k<=ncovmodel;k++){
14493: jj++;
14494: ca[0]= k+'a'-1;ca[1]='\0';
14495: if(itimes==1){
14496: if(mle>=1)
14497: printf("#%1d%1d%d",i,j,k);
14498: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14499: fprintf(ficres,"#%1d%1d%d",i,j,k);
14500: }else{
14501: if(mle>=1)
14502: printf("%1d%1d%d",i,j,k);
14503: fprintf(ficlog,"%1d%1d%d",i,j,k);
14504: fprintf(ficres,"%1d%1d%d",i,j,k);
14505: }
14506: ll=0;
14507: for(li=1;li <=nlstate; li++){
14508: for(lj=1;lj <=nlstate+ndeath; lj++){
14509: if(lj==li) continue;
14510: for(lk=1;lk<=ncovmodel;lk++){
14511: ll++;
14512: if(ll<=jj){
14513: cb[0]= lk +'a'-1;cb[1]='\0';
14514: if(ll<jj){
14515: if(itimes==1){
14516: if(mle>=1)
14517: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14518: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14519: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14520: }else{
14521: if(mle>=1)
14522: printf(" %.5e",matcov[jj][ll]);
14523: fprintf(ficlog," %.5e",matcov[jj][ll]);
14524: fprintf(ficres," %.5e",matcov[jj][ll]);
14525: }
14526: }else{
14527: if(itimes==1){
14528: if(mle>=1)
14529: printf(" Var(%s%1d%1d)",ca,i,j);
14530: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14531: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14532: }else{
14533: if(mle>=1)
14534: printf(" %.7e",matcov[jj][ll]);
14535: fprintf(ficlog," %.7e",matcov[jj][ll]);
14536: fprintf(ficres," %.7e",matcov[jj][ll]);
14537: }
14538: }
14539: }
14540: } /* end lk */
14541: } /* end lj */
14542: } /* end li */
14543: if(mle>=1)
14544: printf("\n");
14545: fprintf(ficlog,"\n");
14546: fprintf(ficres,"\n");
14547: numlinepar++;
14548: } /* end k*/
14549: } /*end j */
1.126 brouard 14550: } /* end i */
14551: } /* end itimes */
14552:
14553: fflush(ficlog);
14554: fflush(ficres);
1.225 brouard 14555: while(fgets(line, MAXLINE, ficpar)) {
14556: /* If line starts with a # it is a comment */
14557: if (line[0] == '#') {
14558: numlinepar++;
14559: fputs(line,stdout);
14560: fputs(line,ficparo);
14561: fputs(line,ficlog);
1.299 brouard 14562: fputs(line,ficres);
1.225 brouard 14563: continue;
14564: }else
14565: break;
14566: }
14567:
1.209 brouard 14568: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14569: /* ungetc(c,ficpar); */
14570: /* fgets(line, MAXLINE, ficpar); */
14571: /* fputs(line,stdout); */
14572: /* fputs(line,ficparo); */
14573: /* } */
14574: /* ungetc(c,ficpar); */
1.126 brouard 14575:
14576: estepm=0;
1.209 brouard 14577: 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 14578:
14579: if (num_filled != 6) {
14580: 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);
14581: 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);
14582: goto end;
14583: }
14584: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14585: }
14586: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14587: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14588:
1.209 brouard 14589: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14590: if (estepm==0 || estepm < stepm) estepm=stepm;
14591: if (fage <= 2) {
14592: bage = ageminpar;
14593: fage = agemaxpar;
14594: }
14595:
14596: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14597: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14598: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14599:
1.186 brouard 14600: /* Other stuffs, more or less useful */
1.254 brouard 14601: while(fgets(line, MAXLINE, ficpar)) {
14602: /* If line starts with a # it is a comment */
14603: if (line[0] == '#') {
14604: numlinepar++;
14605: fputs(line,stdout);
14606: fputs(line,ficparo);
14607: fputs(line,ficlog);
1.299 brouard 14608: fputs(line,ficres);
1.254 brouard 14609: continue;
14610: }else
14611: break;
14612: }
14613:
14614: 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){
14615:
14616: if (num_filled != 7) {
14617: 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);
14618: 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);
14619: goto end;
14620: }
14621: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14622: 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);
14623: 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);
14624: 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 14625: }
1.254 brouard 14626:
14627: while(fgets(line, MAXLINE, ficpar)) {
14628: /* If line starts with a # it is a comment */
14629: if (line[0] == '#') {
14630: numlinepar++;
14631: fputs(line,stdout);
14632: fputs(line,ficparo);
14633: fputs(line,ficlog);
1.299 brouard 14634: fputs(line,ficres);
1.254 brouard 14635: continue;
14636: }else
14637: break;
1.126 brouard 14638: }
14639:
14640:
14641: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14642: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14643:
1.254 brouard 14644: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14645: if (num_filled != 1) {
14646: 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);
14647: 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);
14648: goto end;
14649: }
14650: printf("pop_based=%d\n",popbased);
14651: fprintf(ficlog,"pop_based=%d\n",popbased);
14652: fprintf(ficparo,"pop_based=%d\n",popbased);
14653: fprintf(ficres,"pop_based=%d\n",popbased);
14654: }
14655:
1.258 brouard 14656: /* Results */
1.332 brouard 14657: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14658: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14659: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14660: endishere=0;
1.258 brouard 14661: nresult=0;
1.308 brouard 14662: parameterline=0;
1.258 brouard 14663: do{
14664: if(!fgets(line, MAXLINE, ficpar)){
14665: endishere=1;
1.308 brouard 14666: parameterline=15;
1.258 brouard 14667: }else if (line[0] == '#') {
14668: /* If line starts with a # it is a comment */
1.254 brouard 14669: numlinepar++;
14670: fputs(line,stdout);
14671: fputs(line,ficparo);
14672: fputs(line,ficlog);
1.299 brouard 14673: fputs(line,ficres);
1.254 brouard 14674: continue;
1.258 brouard 14675: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14676: parameterline=11;
1.296 brouard 14677: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14678: parameterline=12;
1.307 brouard 14679: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14680: parameterline=13;
1.307 brouard 14681: }
1.258 brouard 14682: else{
14683: parameterline=14;
1.254 brouard 14684: }
1.308 brouard 14685: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14686: case 11:
1.296 brouard 14687: 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)){
14688: 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 14689: 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);
14690: 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);
14691: 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);
14692: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14693: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14694: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14695: prvforecast = 1;
14696: }
14697: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14698: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14699: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14700: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14701: prvforecast = 2;
14702: }
14703: else {
14704: 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);
14705: 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);
14706: goto end;
1.258 brouard 14707: }
1.254 brouard 14708: break;
1.258 brouard 14709: case 12:
1.296 brouard 14710: 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)){
14711: 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);
14712: 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);
14713: 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);
14714: 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);
14715: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14716: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14717: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14718: prvbackcast = 1;
14719: }
14720: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14721: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14722: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14723: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14724: prvbackcast = 2;
14725: }
14726: else {
14727: 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);
14728: 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);
14729: goto end;
1.258 brouard 14730: }
1.230 brouard 14731: break;
1.258 brouard 14732: case 13:
1.332 brouard 14733: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14734: nresult++; /* Sum of resultlines */
1.342 brouard 14735: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14736: /* removefirstspace(&resultlineori); */
14737:
14738: if(strstr(resultlineori,"v") !=0){
14739: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14740: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14741: return 1;
14742: }
14743: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14744: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14745: if(nresult > MAXRESULTLINESPONE-1){
14746: 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);
14747: 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 14748: goto end;
14749: }
1.332 brouard 14750:
1.310 brouard 14751: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14752: fprintf(ficparo,"result: %s\n",resultline);
14753: fprintf(ficres,"result: %s\n",resultline);
14754: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14755: } else
14756: goto end;
1.307 brouard 14757: break;
14758: case 14:
14759: printf("Error: Unknown command '%s'\n",line);
14760: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14761: if(line[0] == ' ' || line[0] == '\n'){
14762: printf("It should not be an empty line '%s'\n",line);
14763: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14764: }
1.307 brouard 14765: if(ncovmodel >=2 && nresult==0 ){
14766: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14767: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14768: }
1.307 brouard 14769: /* goto end; */
14770: break;
1.308 brouard 14771: case 15:
14772: printf("End of resultlines.\n");
14773: fprintf(ficlog,"End of resultlines.\n");
14774: break;
14775: default: /* parameterline =0 */
1.307 brouard 14776: nresult=1;
14777: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14778: } /* End switch parameterline */
14779: }while(endishere==0); /* End do */
1.126 brouard 14780:
1.230 brouard 14781: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14782: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14783:
14784: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14785: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14786: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14787: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14788: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14789: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14790: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14791: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14792: }else{
1.270 brouard 14793: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14794: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14795: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14796: if(prvforecast==1){
14797: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14798: jprojd=jproj1;
14799: mprojd=mproj1;
14800: anprojd=anproj1;
14801: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14802: jprojf=jproj2;
14803: mprojf=mproj2;
14804: anprojf=anproj2;
14805: } else if(prvforecast == 2){
14806: dateprojd=dateintmean;
14807: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14808: dateprojf=dateintmean+yrfproj;
14809: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14810: }
14811: if(prvbackcast==1){
14812: datebackd=(jback1+12*mback1+365*anback1)/365;
14813: jbackd=jback1;
14814: mbackd=mback1;
14815: anbackd=anback1;
14816: datebackf=(jback2+12*mback2+365*anback2)/365;
14817: jbackf=jback2;
14818: mbackf=mback2;
14819: anbackf=anback2;
14820: } else if(prvbackcast == 2){
14821: datebackd=dateintmean;
14822: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14823: datebackf=dateintmean-yrbproj;
14824: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14825: }
14826:
1.350 brouard 14827: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 14828: }
14829: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14830: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14831: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14832:
1.225 brouard 14833: /*------------ free_vector -------------*/
14834: /* chdir(path); */
1.220 brouard 14835:
1.215 brouard 14836: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14837: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14838: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14839: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14840: free_lvector(num,firstobs,lastobs);
14841: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14842: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14843: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14844: fclose(ficparo);
14845: fclose(ficres);
1.220 brouard 14846:
14847:
1.186 brouard 14848: /* Other results (useful)*/
1.220 brouard 14849:
14850:
1.126 brouard 14851: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14852: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14853: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14854: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14855: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14856: fclose(ficrespl);
14857:
14858: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14859: /*#include "hpijx.h"*/
1.332 brouard 14860: /** 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?*/
14861: /* calls hpxij with combination k */
1.180 brouard 14862: hPijx(p, bage, fage);
1.145 brouard 14863: fclose(ficrespij);
1.227 brouard 14864:
1.220 brouard 14865: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14866: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14867: k=1;
1.126 brouard 14868: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14869:
1.269 brouard 14870: /* Prevalence for each covariate combination in probs[age][status][cov] */
14871: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14872: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14873: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14874: for(k=1;k<=ncovcombmax;k++)
14875: probs[i][j][k]=0.;
1.269 brouard 14876: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14877: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14878: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14879: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14880: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14881: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14882: for(k=1;k<=ncovcombmax;k++)
14883: mobaverages[i][j][k]=0.;
1.219 brouard 14884: mobaverage=mobaverages;
14885: if (mobilav!=0) {
1.235 brouard 14886: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14887: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14888: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14889: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14890: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14891: }
1.269 brouard 14892: } else if (mobilavproj !=0) {
1.235 brouard 14893: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14894: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14895: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14896: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14897: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14898: }
1.269 brouard 14899: }else{
14900: printf("Internal error moving average\n");
14901: fflush(stdout);
14902: exit(1);
1.219 brouard 14903: }
14904: }/* end if moving average */
1.227 brouard 14905:
1.126 brouard 14906: /*---------- Forecasting ------------------*/
1.296 brouard 14907: if(prevfcast==1){
14908: /* /\* if(stepm ==1){*\/ */
14909: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14910: /*This done previously after freqsummary.*/
14911: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14912: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14913:
14914: /* } else if (prvforecast==2){ */
14915: /* /\* if(stepm ==1){*\/ */
14916: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14917: /* } */
14918: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14919: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14920: }
1.269 brouard 14921:
1.296 brouard 14922: /* Prevbcasting */
14923: if(prevbcast==1){
1.219 brouard 14924: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14925: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14926: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14927:
14928: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14929:
14930: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14931:
1.219 brouard 14932: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14933: fclose(ficresplb);
14934:
1.222 brouard 14935: hBijx(p, bage, fage, mobaverage);
14936: fclose(ficrespijb);
1.219 brouard 14937:
1.296 brouard 14938: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14939: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14940: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14941: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14942: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14943: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14944:
14945:
1.269 brouard 14946: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14947:
14948:
1.269 brouard 14949: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14950: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14951: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14952: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14953: } /* end Prevbcasting */
1.268 brouard 14954:
1.186 brouard 14955:
14956: /* ------ Other prevalence ratios------------ */
1.126 brouard 14957:
1.215 brouard 14958: free_ivector(wav,1,imx);
14959: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14960: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14961: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14962:
14963:
1.127 brouard 14964: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14965:
1.201 brouard 14966: strcpy(filerese,"E_");
14967: strcat(filerese,fileresu);
1.126 brouard 14968: if((ficreseij=fopen(filerese,"w"))==NULL) {
14969: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14970: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14971: }
1.208 brouard 14972: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14973: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14974:
14975: pstamp(ficreseij);
1.219 brouard 14976:
1.351 brouard 14977: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
14978: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 14979:
1.351 brouard 14980: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
14981: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14982: /* if(i1 != 1 && TKresult[nres]!= k) */
14983: /* continue; */
1.219 brouard 14984: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14985: printf("\n#****** ");
1.351 brouard 14986: for(j=1;j<=cptcovs;j++){
14987: /* for(j=1;j<=cptcoveff;j++) { */
14988: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14989: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14990: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14991: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 14992: }
14993: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14994: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14995: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 14996: }
14997: fprintf(ficreseij,"******\n");
1.235 brouard 14998: printf("******\n");
1.219 brouard 14999:
15000: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15001: oldm=oldms;savm=savms;
1.330 brouard 15002: /* 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 15003: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 15004:
1.219 brouard 15005: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 15006: }
15007: fclose(ficreseij);
1.208 brouard 15008: printf("done evsij\n");fflush(stdout);
15009: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 15010:
1.218 brouard 15011:
1.227 brouard 15012: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 15013: /* Should be moved in a function */
1.201 brouard 15014: strcpy(filerest,"T_");
15015: strcat(filerest,fileresu);
1.127 brouard 15016: if((ficrest=fopen(filerest,"w"))==NULL) {
15017: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
15018: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
15019: }
1.208 brouard 15020: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
15021: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 15022: strcpy(fileresstde,"STDE_");
15023: strcat(fileresstde,fileresu);
1.126 brouard 15024: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 15025: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
15026: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 15027: }
1.227 brouard 15028: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
15029: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 15030:
1.201 brouard 15031: strcpy(filerescve,"CVE_");
15032: strcat(filerescve,fileresu);
1.126 brouard 15033: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 15034: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
15035: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 15036: }
1.227 brouard 15037: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
15038: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 15039:
1.201 brouard 15040: strcpy(fileresv,"V_");
15041: strcat(fileresv,fileresu);
1.126 brouard 15042: if((ficresvij=fopen(fileresv,"w"))==NULL) {
15043: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
15044: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
15045: }
1.227 brouard 15046: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
15047: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 15048:
1.235 brouard 15049: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
15050: if (cptcovn < 1){i1=1;}
15051:
1.334 brouard 15052: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
15053: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
15054: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
15055: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
15056: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
15057: /* */
15058: 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 15059: continue;
1.350 brouard 15060: printf("\n# model %s \n#****** Result for:", model); /* HERE model is empty */
1.321 brouard 15061: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
15062: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 15063: /* It might not be a good idea to mix dummies and quantitative */
15064: /* 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 *\/ */
15065: 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 */
15066: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
15067: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
15068: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
15069: * (V5 is quanti) V4 and V3 are dummies
15070: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
15071: * l=1 l=2
15072: * k=1 1 1 0 0
15073: * k=2 2 1 1 0
15074: * k=3 [1] [2] 0 1
15075: * k=4 2 2 1 1
15076: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
15077: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
15078: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
15079: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
15080: */
15081: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
15082: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
15083: /* We give up with the combinations!! */
1.342 brouard 15084: /* if(debugILK) */
15085: /* 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 15086:
15087: 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 15088: /* 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] */
15089: 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 */
15090: 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 */
15091: 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 15092: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15093: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15094: }else{
15095: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15096: }
15097: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15098: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15099: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15100: /* For each selected (single) quantitative value */
1.337 brouard 15101: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15102: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15103: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15104: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15105: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15106: }else{
15107: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15108: }
15109: }else{
15110: 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 */
15111: 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 */
15112: exit(1);
15113: }
1.335 brouard 15114: } /* End loop for each variable in the resultline */
1.334 brouard 15115: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15116: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15117: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15118: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15119: /* } */
1.208 brouard 15120: fprintf(ficrest,"******\n");
1.227 brouard 15121: fprintf(ficlog,"******\n");
15122: printf("******\n");
1.208 brouard 15123:
15124: fprintf(ficresstdeij,"\n#****** ");
15125: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15126: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15127: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15128: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15129: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15130: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15131: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15132: }
15133: 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 15134: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15135: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15136: }
1.208 brouard 15137: fprintf(ficresstdeij,"******\n");
15138: fprintf(ficrescveij,"******\n");
15139:
15140: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15141: /* pstamp(ficresvij); */
1.225 brouard 15142: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15143: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15144: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15145: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15146: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15147: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15148: }
1.208 brouard 15149: fprintf(ficresvij,"******\n");
15150:
15151: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15152: oldm=oldms;savm=savms;
1.235 brouard 15153: printf(" cvevsij ");
15154: fprintf(ficlog, " cvevsij ");
15155: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15156: printf(" end cvevsij \n ");
15157: fprintf(ficlog, " end cvevsij \n ");
15158:
15159: /*
15160: */
15161: /* goto endfree; */
15162:
15163: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15164: pstamp(ficrest);
15165:
1.269 brouard 15166: epj=vector(1,nlstate+1);
1.208 brouard 15167: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15168: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15169: cptcod= 0; /* To be deleted */
15170: printf("varevsij vpopbased=%d \n",vpopbased);
15171: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15172: 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 15173: 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 ");
15174: if(vpopbased==1)
15175: 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);
15176: else
1.288 brouard 15177: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15178: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15179: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15180: fprintf(ficrest,"\n");
15181: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15182: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15183: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15184: for(age=bage; age <=fage ;age++){
1.235 brouard 15185: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15186: if (vpopbased==1) {
15187: if(mobilav ==0){
15188: for(i=1; i<=nlstate;i++)
15189: prlim[i][i]=probs[(int)age][i][k];
15190: }else{ /* mobilav */
15191: for(i=1; i<=nlstate;i++)
15192: prlim[i][i]=mobaverage[(int)age][i][k];
15193: }
15194: }
1.219 brouard 15195:
1.227 brouard 15196: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15197: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15198: /* printf(" age %4.0f ",age); */
15199: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15200: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15201: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15202: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15203: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15204: }
15205: epj[nlstate+1] +=epj[j];
15206: }
15207: /* printf(" age %4.0f \n",age); */
1.219 brouard 15208:
1.227 brouard 15209: for(i=1, vepp=0.;i <=nlstate;i++)
15210: for(j=1;j <=nlstate;j++)
15211: vepp += vareij[i][j][(int)age];
15212: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15213: for(j=1;j <=nlstate;j++){
15214: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15215: }
15216: fprintf(ficrest,"\n");
15217: }
1.208 brouard 15218: } /* End vpopbased */
1.269 brouard 15219: free_vector(epj,1,nlstate+1);
1.208 brouard 15220: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15221: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15222: printf("done selection\n");fflush(stdout);
15223: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15224:
1.335 brouard 15225: } /* End k selection or end covariate selection for nres */
1.227 brouard 15226:
15227: printf("done State-specific expectancies\n");fflush(stdout);
15228: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15229:
1.335 brouard 15230: /* variance-covariance of forward period prevalence */
1.269 brouard 15231: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15232:
1.227 brouard 15233:
1.290 brouard 15234: free_vector(weight,firstobs,lastobs);
1.351 brouard 15235: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 15236: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15237: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15238: free_matrix(anint,1,maxwav,firstobs,lastobs);
15239: free_matrix(mint,1,maxwav,firstobs,lastobs);
15240: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15241: free_ivector(tab,1,NCOVMAX);
15242: fclose(ficresstdeij);
15243: fclose(ficrescveij);
15244: fclose(ficresvij);
15245: fclose(ficrest);
15246: fclose(ficpar);
15247:
15248:
1.126 brouard 15249: /*---------- End : free ----------------*/
1.219 brouard 15250: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15251: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15252: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15253: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15254: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15255: } /* mle==-3 arrives here for freeing */
1.227 brouard 15256: /* endfree:*/
15257: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15258: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15259: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15260: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15261: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15262: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15263: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15264: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15265: free_matrix(matcov,1,npar,1,npar);
15266: free_matrix(hess,1,npar,1,npar);
15267: /*free_vector(delti,1,npar);*/
15268: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15269: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15270: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15271: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15272:
15273: free_ivector(ncodemax,1,NCOVMAX);
15274: free_ivector(ncodemaxwundef,1,NCOVMAX);
15275: free_ivector(Dummy,-1,NCOVMAX);
15276: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 15277: free_ivector(DummyV,-1,NCOVMAX);
15278: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15279: free_ivector(Typevar,-1,NCOVMAX);
15280: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15281: free_ivector(TvarsQ,1,NCOVMAX);
15282: free_ivector(TvarsQind,1,NCOVMAX);
15283: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15284: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15285: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15286: free_ivector(TvarFD,1,NCOVMAX);
15287: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15288: free_ivector(TvarF,1,NCOVMAX);
15289: free_ivector(TvarFind,1,NCOVMAX);
15290: free_ivector(TvarV,1,NCOVMAX);
15291: free_ivector(TvarVind,1,NCOVMAX);
15292: free_ivector(TvarA,1,NCOVMAX);
15293: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15294: free_ivector(TvarFQ,1,NCOVMAX);
15295: free_ivector(TvarFQind,1,NCOVMAX);
15296: free_ivector(TvarVD,1,NCOVMAX);
15297: free_ivector(TvarVDind,1,NCOVMAX);
15298: free_ivector(TvarVQ,1,NCOVMAX);
15299: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 15300: free_ivector(TvarAVVA,1,NCOVMAX);
15301: free_ivector(TvarAVVAind,1,NCOVMAX);
15302: free_ivector(TvarVVA,1,NCOVMAX);
15303: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15304: free_ivector(TvarVV,1,NCOVMAX);
15305: free_ivector(TvarVVind,1,NCOVMAX);
15306:
1.230 brouard 15307: free_ivector(Tvarsel,1,NCOVMAX);
15308: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15309: free_ivector(Tposprod,1,NCOVMAX);
15310: free_ivector(Tprod,1,NCOVMAX);
15311: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15312: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15313: free_ivector(Tage,1,NCOVMAX);
15314: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15315: free_ivector(TmodelInvind,1,NCOVMAX);
15316: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15317:
15318: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15319:
1.227 brouard 15320: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15321: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15322: fflush(fichtm);
15323: fflush(ficgp);
15324:
1.227 brouard 15325:
1.126 brouard 15326: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15327: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15328: 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 15329: }else{
15330: printf("End of Imach\n");
15331: fprintf(ficlog,"End of Imach\n");
15332: }
15333: printf("See log file on %s\n",filelog);
15334: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15335: /*(void) gettimeofday(&end_time,&tzp);*/
15336: rend_time = time(NULL);
15337: end_time = *localtime(&rend_time);
15338: /* tml = *localtime(&end_time.tm_sec); */
15339: strcpy(strtend,asctime(&end_time));
1.126 brouard 15340: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15341: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15342: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15343:
1.157 brouard 15344: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15345: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15346: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15347: /* printf("Total time was %d uSec.\n", total_usecs);*/
15348: /* if(fileappend(fichtm,optionfilehtm)){ */
15349: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15350: fclose(fichtm);
15351: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15352: fclose(fichtmcov);
15353: fclose(ficgp);
15354: fclose(ficlog);
15355: /*------ End -----------*/
1.227 brouard 15356:
1.281 brouard 15357:
15358: /* Executes gnuplot */
1.227 brouard 15359:
15360: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15361: #ifdef WIN32
1.227 brouard 15362: if (_chdir(pathcd) != 0)
15363: printf("Can't move to directory %s!\n",path);
15364: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15365: #else
1.227 brouard 15366: if(chdir(pathcd) != 0)
15367: printf("Can't move to directory %s!\n", path);
15368: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15369: #endif
1.126 brouard 15370: printf("Current directory %s!\n",pathcd);
15371: /*strcat(plotcmd,CHARSEPARATOR);*/
15372: sprintf(plotcmd,"gnuplot");
1.157 brouard 15373: #ifdef _WIN32
1.126 brouard 15374: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15375: #endif
15376: if(!stat(plotcmd,&info)){
1.158 brouard 15377: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15378: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15379: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15380: }else
15381: strcpy(pplotcmd,plotcmd);
1.157 brouard 15382: #ifdef __unix
1.126 brouard 15383: strcpy(plotcmd,GNUPLOTPROGRAM);
15384: if(!stat(plotcmd,&info)){
1.158 brouard 15385: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15386: }else
15387: strcpy(pplotcmd,plotcmd);
15388: #endif
15389: }else
15390: strcpy(pplotcmd,plotcmd);
15391:
15392: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15393: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15394: strcpy(pplotcmd,plotcmd);
1.227 brouard 15395:
1.126 brouard 15396: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15397: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15398: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15399: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15400: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15401: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15402: strcpy(plotcmd,pplotcmd);
15403: }
1.126 brouard 15404: }
1.158 brouard 15405: printf(" Successful, please wait...");
1.126 brouard 15406: while (z[0] != 'q') {
15407: /* chdir(path); */
1.154 brouard 15408: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15409: scanf("%s",z);
15410: /* if (z[0] == 'c') system("./imach"); */
15411: if (z[0] == 'e') {
1.158 brouard 15412: #ifdef __APPLE__
1.152 brouard 15413: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15414: #elif __linux
15415: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15416: #else
1.152 brouard 15417: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15418: #endif
15419: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15420: system(pplotcmd);
1.126 brouard 15421: }
15422: else if (z[0] == 'g') system(plotcmd);
15423: else if (z[0] == 'q') exit(0);
15424: }
1.227 brouard 15425: end:
1.126 brouard 15426: while (z[0] != 'q') {
1.195 brouard 15427: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15428: scanf("%s",z);
15429: }
1.283 brouard 15430: printf("End\n");
1.282 brouard 15431: exit(0);
1.126 brouard 15432: }
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