Annotation of imach/src/imach.c, revision 1.341
1.341 ! brouard 1: /* $Id: imach.c,v 1.340 2022/09/11 07:53:11 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.341 ! brouard 4: Revision 1.340 2022/09/11 07:53:11 brouard
! 5: Summary: Version imach 0.99r37
! 6:
! 7: * imach.c (Module): Adding timevarying products of any kinds,
! 8: should work before shifting cotvar from ncovcol+nqv columns in
! 9: order to have a correspondance between the column of cotvar and
! 10: the id of column.
! 11:
1.340 brouard 12: Revision 1.339 2022/09/09 17:55:22 brouard
13: Summary: version 0.99r37
14:
15: * imach.c (Module): Many improvements for fixing products of fixed
16: timevarying as well as fixed * fixed, and test with quantitative
17: covariate.
18:
1.339 brouard 19: Revision 1.338 2022/09/04 17:40:33 brouard
20: Summary: 0.99r36
21:
22: * imach.c (Module): Now the easy runs i.e. without result or
23: model=1+age only did not work. The defautl combination should be 1
24: and not 0 because everything hasn't been tranformed yet.
25:
1.338 brouard 26: Revision 1.337 2022/09/02 14:26:02 brouard
27: Summary: version 0.99r35
28:
29: * src/imach.c: Version 0.99r35 because it outputs same results with
30: 1+age+V1+V1*age for females and 1+age for females only
31: (education=1 noweight)
32:
1.337 brouard 33: Revision 1.336 2022/08/31 09:52:36 brouard
34: *** empty log message ***
35:
1.336 brouard 36: Revision 1.335 2022/08/31 08:23:16 brouard
37: Summary: improvements...
38:
1.335 brouard 39: Revision 1.334 2022/08/25 09:08:41 brouard
40: Summary: In progress for quantitative
41:
1.334 brouard 42: Revision 1.333 2022/08/21 09:10:30 brouard
43: * src/imach.c (Module): Version 0.99r33 A lot of changes in
44: reassigning covariates: my first idea was that people will always
45: use the first covariate V1 into the model but in fact they are
46: producing data with many covariates and can use an equation model
47: with some of the covariate; it means that in a model V2+V3 instead
48: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
49: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
50: the equation model is restricted to two variables only (V2, V3)
51: and the combination for V2 should be codtabm(k,1) instead of
52: (codtabm(k,2), and the code should be
53: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
54: made. All of these should be simplified once a day like we did in
55: hpxij() for example by using precov[nres] which is computed in
56: decoderesult for each nres of each resultline. Loop should be done
57: on the equation model globally by distinguishing only product with
58: age (which are changing with age) and no more on type of
59: covariates, single dummies, single covariates.
60:
1.333 brouard 61: Revision 1.332 2022/08/21 09:06:25 brouard
62: Summary: Version 0.99r33
63:
64: * src/imach.c (Module): Version 0.99r33 A lot of changes in
65: reassigning covariates: my first idea was that people will always
66: use the first covariate V1 into the model but in fact they are
67: producing data with many covariates and can use an equation model
68: with some of the covariate; it means that in a model V2+V3 instead
69: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
70: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
71: the equation model is restricted to two variables only (V2, V3)
72: and the combination for V2 should be codtabm(k,1) instead of
73: (codtabm(k,2), and the code should be
74: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
75: made. All of these should be simplified once a day like we did in
76: hpxij() for example by using precov[nres] which is computed in
77: decoderesult for each nres of each resultline. Loop should be done
78: on the equation model globally by distinguishing only product with
79: age (which are changing with age) and no more on type of
80: covariates, single dummies, single covariates.
81:
1.332 brouard 82: Revision 1.331 2022/08/07 05:40:09 brouard
83: *** empty log message ***
84:
1.331 brouard 85: Revision 1.330 2022/08/06 07:18:25 brouard
86: Summary: last 0.99r31
87:
88: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
89:
1.330 brouard 90: Revision 1.329 2022/08/03 17:29:54 brouard
91: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
92:
1.329 brouard 93: Revision 1.328 2022/07/27 17:40:48 brouard
94: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
95:
1.328 brouard 96: Revision 1.327 2022/07/27 14:47:35 brouard
97: Summary: Still a problem for one-step probabilities in case of quantitative variables
98:
1.327 brouard 99: Revision 1.326 2022/07/26 17:33:55 brouard
100: Summary: some test with nres=1
101:
1.326 brouard 102: Revision 1.325 2022/07/25 14:27:23 brouard
103: Summary: r30
104:
105: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
106: coredumped, revealed by Feiuno, thank you.
107:
1.325 brouard 108: Revision 1.324 2022/07/23 17:44:26 brouard
109: *** empty log message ***
110:
1.324 brouard 111: Revision 1.323 2022/07/22 12:30:08 brouard
112: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
113:
1.323 brouard 114: Revision 1.322 2022/07/22 12:27:48 brouard
115: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
116:
1.322 brouard 117: Revision 1.321 2022/07/22 12:04:24 brouard
118: Summary: r28
119:
120: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
121:
1.321 brouard 122: Revision 1.320 2022/06/02 05:10:11 brouard
123: *** empty log message ***
124:
1.320 brouard 125: Revision 1.319 2022/06/02 04:45:11 brouard
126: * imach.c (Module): Adding the Wald tests from the log to the main
127: htm for better display of the maximum likelihood estimators.
128:
1.319 brouard 129: Revision 1.318 2022/05/24 08:10:59 brouard
130: * imach.c (Module): Some attempts to find a bug of wrong estimates
131: of confidencce intervals with product in the equation modelC
132:
1.318 brouard 133: Revision 1.317 2022/05/15 15:06:23 brouard
134: * imach.c (Module): Some minor improvements
135:
1.317 brouard 136: Revision 1.316 2022/05/11 15:11:31 brouard
137: Summary: r27
138:
1.316 brouard 139: Revision 1.315 2022/05/11 15:06:32 brouard
140: *** empty log message ***
141:
1.315 brouard 142: Revision 1.314 2022/04/13 17:43:09 brouard
143: * imach.c (Module): Adding link to text data files
144:
1.314 brouard 145: Revision 1.313 2022/04/11 15:57:42 brouard
146: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
147:
1.313 brouard 148: Revision 1.312 2022/04/05 21:24:39 brouard
149: *** empty log message ***
150:
1.312 brouard 151: Revision 1.311 2022/04/05 21:03:51 brouard
152: Summary: Fixed quantitative covariates
153:
154: Fixed covariates (dummy or quantitative)
155: with missing values have never been allowed but are ERRORS and
156: program quits. Standard deviations of fixed covariates were
157: wrongly computed. Mean and standard deviations of time varying
158: covariates are still not computed.
159:
1.311 brouard 160: Revision 1.310 2022/03/17 08:45:53 brouard
161: Summary: 99r25
162:
163: Improving detection of errors: result lines should be compatible with
164: the model.
165:
1.310 brouard 166: Revision 1.309 2021/05/20 12:39:14 brouard
167: Summary: Version 0.99r24
168:
1.309 brouard 169: Revision 1.308 2021/03/31 13:11:57 brouard
170: Summary: Version 0.99r23
171:
172:
173: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
174:
1.308 brouard 175: Revision 1.307 2021/03/08 18:11:32 brouard
176: Summary: 0.99r22 fixed bug on result:
177:
1.307 brouard 178: Revision 1.306 2021/02/20 15:44:02 brouard
179: Summary: Version 0.99r21
180:
181: * imach.c (Module): Fix bug on quitting after result lines!
182: (Module): Version 0.99r21
183:
1.306 brouard 184: Revision 1.305 2021/02/20 15:28:30 brouard
185: * imach.c (Module): Fix bug on quitting after result lines!
186:
1.305 brouard 187: Revision 1.304 2021/02/12 11:34:20 brouard
188: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
189:
1.304 brouard 190: Revision 1.303 2021/02/11 19:50:15 brouard
191: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
192:
1.303 brouard 193: Revision 1.302 2020/02/22 21:00:05 brouard
194: * (Module): imach.c Update mle=-3 (for computing Life expectancy
195: and life table from the data without any state)
196:
1.302 brouard 197: Revision 1.301 2019/06/04 13:51:20 brouard
198: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
199:
1.301 brouard 200: Revision 1.300 2019/05/22 19:09:45 brouard
201: Summary: version 0.99r19 of May 2019
202:
1.300 brouard 203: Revision 1.299 2019/05/22 18:37:08 brouard
204: Summary: Cleaned 0.99r19
205:
1.299 brouard 206: Revision 1.298 2019/05/22 18:19:56 brouard
207: *** empty log message ***
208:
1.298 brouard 209: Revision 1.297 2019/05/22 17:56:10 brouard
210: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
211:
1.297 brouard 212: Revision 1.296 2019/05/20 13:03:18 brouard
213: Summary: Projection syntax simplified
214:
215:
216: We can now start projections, forward or backward, from the mean date
217: of inteviews up to or down to a number of years of projection:
218: prevforecast=1 yearsfproj=15.3 mobil_average=0
219: or
220: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
221: or
222: prevbackcast=1 yearsbproj=12.3 mobil_average=1
223: or
224: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
225:
1.296 brouard 226: Revision 1.295 2019/05/18 09:52:50 brouard
227: Summary: doxygen tex bug
228:
1.295 brouard 229: Revision 1.294 2019/05/16 14:54:33 brouard
230: Summary: There was some wrong lines added
231:
1.294 brouard 232: Revision 1.293 2019/05/09 15:17:34 brouard
233: *** empty log message ***
234:
1.293 brouard 235: Revision 1.292 2019/05/09 14:17:20 brouard
236: Summary: Some updates
237:
1.292 brouard 238: Revision 1.291 2019/05/09 13:44:18 brouard
239: Summary: Before ncovmax
240:
1.291 brouard 241: Revision 1.290 2019/05/09 13:39:37 brouard
242: Summary: 0.99r18 unlimited number of individuals
243:
244: 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.
245:
1.290 brouard 246: Revision 1.289 2018/12/13 09:16:26 brouard
247: Summary: Bug for young ages (<-30) will be in r17
248:
1.289 brouard 249: Revision 1.288 2018/05/02 20:58:27 brouard
250: Summary: Some bugs fixed
251:
1.288 brouard 252: Revision 1.287 2018/05/01 17:57:25 brouard
253: Summary: Bug fixed by providing frequencies only for non missing covariates
254:
1.287 brouard 255: Revision 1.286 2018/04/27 14:27:04 brouard
256: Summary: some minor bugs
257:
1.286 brouard 258: Revision 1.285 2018/04/21 21:02:16 brouard
259: Summary: Some bugs fixed, valgrind tested
260:
1.285 brouard 261: Revision 1.284 2018/04/20 05:22:13 brouard
262: Summary: Computing mean and stdeviation of fixed quantitative variables
263:
1.284 brouard 264: Revision 1.283 2018/04/19 14:49:16 brouard
265: Summary: Some minor bugs fixed
266:
1.283 brouard 267: Revision 1.282 2018/02/27 22:50:02 brouard
268: *** empty log message ***
269:
1.282 brouard 270: Revision 1.281 2018/02/27 19:25:23 brouard
271: Summary: Adding second argument for quitting
272:
1.281 brouard 273: Revision 1.280 2018/02/21 07:58:13 brouard
274: Summary: 0.99r15
275:
276: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
277:
1.280 brouard 278: Revision 1.279 2017/07/20 13:35:01 brouard
279: Summary: temporary working
280:
1.279 brouard 281: Revision 1.278 2017/07/19 14:09:02 brouard
282: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
283:
1.278 brouard 284: Revision 1.277 2017/07/17 08:53:49 brouard
285: Summary: BOM files can be read now
286:
1.277 brouard 287: Revision 1.276 2017/06/30 15:48:31 brouard
288: Summary: Graphs improvements
289:
1.276 brouard 290: Revision 1.275 2017/06/30 13:39:33 brouard
291: Summary: Saito's color
292:
1.275 brouard 293: Revision 1.274 2017/06/29 09:47:08 brouard
294: Summary: Version 0.99r14
295:
1.274 brouard 296: Revision 1.273 2017/06/27 11:06:02 brouard
297: Summary: More documentation on projections
298:
1.273 brouard 299: Revision 1.272 2017/06/27 10:22:40 brouard
300: Summary: Color of backprojection changed from 6 to 5(yellow)
301:
1.272 brouard 302: Revision 1.271 2017/06/27 10:17:50 brouard
303: Summary: Some bug with rint
304:
1.271 brouard 305: Revision 1.270 2017/05/24 05:45:29 brouard
306: *** empty log message ***
307:
1.270 brouard 308: Revision 1.269 2017/05/23 08:39:25 brouard
309: Summary: Code into subroutine, cleanings
310:
1.269 brouard 311: Revision 1.268 2017/05/18 20:09:32 brouard
312: Summary: backprojection and confidence intervals of backprevalence
313:
1.268 brouard 314: Revision 1.267 2017/05/13 10:25:05 brouard
315: Summary: temporary save for backprojection
316:
1.267 brouard 317: Revision 1.266 2017/05/13 07:26:12 brouard
318: Summary: Version 0.99r13 (improvements and bugs fixed)
319:
1.266 brouard 320: Revision 1.265 2017/04/26 16:22:11 brouard
321: Summary: imach 0.99r13 Some bugs fixed
322:
1.265 brouard 323: Revision 1.264 2017/04/26 06:01:29 brouard
324: Summary: Labels in graphs
325:
1.264 brouard 326: Revision 1.263 2017/04/24 15:23:15 brouard
327: Summary: to save
328:
1.263 brouard 329: Revision 1.262 2017/04/18 16:48:12 brouard
330: *** empty log message ***
331:
1.262 brouard 332: Revision 1.261 2017/04/05 10:14:09 brouard
333: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
334:
1.261 brouard 335: Revision 1.260 2017/04/04 17:46:59 brouard
336: Summary: Gnuplot indexations fixed (humm)
337:
1.260 brouard 338: Revision 1.259 2017/04/04 13:01:16 brouard
339: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
340:
1.259 brouard 341: Revision 1.258 2017/04/03 10:17:47 brouard
342: Summary: Version 0.99r12
343:
344: Some cleanings, conformed with updated documentation.
345:
1.258 brouard 346: Revision 1.257 2017/03/29 16:53:30 brouard
347: Summary: Temp
348:
1.257 brouard 349: Revision 1.256 2017/03/27 05:50:23 brouard
350: Summary: Temporary
351:
1.256 brouard 352: Revision 1.255 2017/03/08 16:02:28 brouard
353: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
354:
1.255 brouard 355: Revision 1.254 2017/03/08 07:13:00 brouard
356: Summary: Fixing data parameter line
357:
1.254 brouard 358: Revision 1.253 2016/12/15 11:59:41 brouard
359: Summary: 0.99 in progress
360:
1.253 brouard 361: Revision 1.252 2016/09/15 21:15:37 brouard
362: *** empty log message ***
363:
1.252 brouard 364: Revision 1.251 2016/09/15 15:01:13 brouard
365: Summary: not working
366:
1.251 brouard 367: Revision 1.250 2016/09/08 16:07:27 brouard
368: Summary: continue
369:
1.250 brouard 370: Revision 1.249 2016/09/07 17:14:18 brouard
371: Summary: Starting values from frequencies
372:
1.249 brouard 373: Revision 1.248 2016/09/07 14:10:18 brouard
374: *** empty log message ***
375:
1.248 brouard 376: Revision 1.247 2016/09/02 11:11:21 brouard
377: *** empty log message ***
378:
1.247 brouard 379: Revision 1.246 2016/09/02 08:49:22 brouard
380: *** empty log message ***
381:
1.246 brouard 382: Revision 1.245 2016/09/02 07:25:01 brouard
383: *** empty log message ***
384:
1.245 brouard 385: Revision 1.244 2016/09/02 07:17:34 brouard
386: *** empty log message ***
387:
1.244 brouard 388: Revision 1.243 2016/09/02 06:45:35 brouard
389: *** empty log message ***
390:
1.243 brouard 391: Revision 1.242 2016/08/30 15:01:20 brouard
392: Summary: Fixing a lots
393:
1.242 brouard 394: Revision 1.241 2016/08/29 17:17:25 brouard
395: Summary: gnuplot problem in Back projection to fix
396:
1.241 brouard 397: Revision 1.240 2016/08/29 07:53:18 brouard
398: Summary: Better
399:
1.240 brouard 400: Revision 1.239 2016/08/26 15:51:03 brouard
401: Summary: Improvement in Powell output in order to copy and paste
402:
403: Author:
404:
1.239 brouard 405: Revision 1.238 2016/08/26 14:23:35 brouard
406: Summary: Starting tests of 0.99
407:
1.238 brouard 408: Revision 1.237 2016/08/26 09:20:19 brouard
409: Summary: to valgrind
410:
1.237 brouard 411: Revision 1.236 2016/08/25 10:50:18 brouard
412: *** empty log message ***
413:
1.236 brouard 414: Revision 1.235 2016/08/25 06:59:23 brouard
415: *** empty log message ***
416:
1.235 brouard 417: Revision 1.234 2016/08/23 16:51:20 brouard
418: *** empty log message ***
419:
1.234 brouard 420: Revision 1.233 2016/08/23 07:40:50 brouard
421: Summary: not working
422:
1.233 brouard 423: Revision 1.232 2016/08/22 14:20:21 brouard
424: Summary: not working
425:
1.232 brouard 426: Revision 1.231 2016/08/22 07:17:15 brouard
427: Summary: not working
428:
1.231 brouard 429: Revision 1.230 2016/08/22 06:55:53 brouard
430: Summary: Not working
431:
1.230 brouard 432: Revision 1.229 2016/07/23 09:45:53 brouard
433: Summary: Completing for func too
434:
1.229 brouard 435: Revision 1.228 2016/07/22 17:45:30 brouard
436: Summary: Fixing some arrays, still debugging
437:
1.227 brouard 438: Revision 1.226 2016/07/12 18:42:34 brouard
439: Summary: temp
440:
1.226 brouard 441: Revision 1.225 2016/07/12 08:40:03 brouard
442: Summary: saving but not running
443:
1.225 brouard 444: Revision 1.224 2016/07/01 13:16:01 brouard
445: Summary: Fixes
446:
1.224 brouard 447: Revision 1.223 2016/02/19 09:23:35 brouard
448: Summary: temporary
449:
1.223 brouard 450: Revision 1.222 2016/02/17 08:14:50 brouard
451: Summary: Probably last 0.98 stable version 0.98r6
452:
1.222 brouard 453: Revision 1.221 2016/02/15 23:35:36 brouard
454: Summary: minor bug
455:
1.220 brouard 456: Revision 1.219 2016/02/15 00:48:12 brouard
457: *** empty log message ***
458:
1.219 brouard 459: Revision 1.218 2016/02/12 11:29:23 brouard
460: Summary: 0.99 Back projections
461:
1.218 brouard 462: Revision 1.217 2015/12/23 17:18:31 brouard
463: Summary: Experimental backcast
464:
1.217 brouard 465: Revision 1.216 2015/12/18 17:32:11 brouard
466: Summary: 0.98r4 Warning and status=-2
467:
468: Version 0.98r4 is now:
469: - displaying an error when status is -1, date of interview unknown and date of death known;
470: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
471: Older changes concerning s=-2, dating from 2005 have been supersed.
472:
1.216 brouard 473: Revision 1.215 2015/12/16 08:52:24 brouard
474: Summary: 0.98r4 working
475:
1.215 brouard 476: Revision 1.214 2015/12/16 06:57:54 brouard
477: Summary: temporary not working
478:
1.214 brouard 479: Revision 1.213 2015/12/11 18:22:17 brouard
480: Summary: 0.98r4
481:
1.213 brouard 482: Revision 1.212 2015/11/21 12:47:24 brouard
483: Summary: minor typo
484:
1.212 brouard 485: Revision 1.211 2015/11/21 12:41:11 brouard
486: Summary: 0.98r3 with some graph of projected cross-sectional
487:
488: Author: Nicolas Brouard
489:
1.211 brouard 490: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 491: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 492: Summary: Adding ftolpl parameter
493: Author: N Brouard
494:
495: We had difficulties to get smoothed confidence intervals. It was due
496: to the period prevalence which wasn't computed accurately. The inner
497: parameter ftolpl is now an outer parameter of the .imach parameter
498: file after estepm. If ftolpl is small 1.e-4 and estepm too,
499: computation are long.
500:
1.209 brouard 501: Revision 1.208 2015/11/17 14:31:57 brouard
502: Summary: temporary
503:
1.208 brouard 504: Revision 1.207 2015/10/27 17:36:57 brouard
505: *** empty log message ***
506:
1.207 brouard 507: Revision 1.206 2015/10/24 07:14:11 brouard
508: *** empty log message ***
509:
1.206 brouard 510: Revision 1.205 2015/10/23 15:50:53 brouard
511: Summary: 0.98r3 some clarification for graphs on likelihood contributions
512:
1.205 brouard 513: Revision 1.204 2015/10/01 16:20:26 brouard
514: Summary: Some new graphs of contribution to likelihood
515:
1.204 brouard 516: Revision 1.203 2015/09/30 17:45:14 brouard
517: Summary: looking at better estimation of the hessian
518:
519: Also a better criteria for convergence to the period prevalence And
520: therefore adding the number of years needed to converge. (The
521: prevalence in any alive state shold sum to one
522:
1.203 brouard 523: Revision 1.202 2015/09/22 19:45:16 brouard
524: Summary: Adding some overall graph on contribution to likelihood. Might change
525:
1.202 brouard 526: Revision 1.201 2015/09/15 17:34:58 brouard
527: Summary: 0.98r0
528:
529: - Some new graphs like suvival functions
530: - Some bugs fixed like model=1+age+V2.
531:
1.201 brouard 532: Revision 1.200 2015/09/09 16:53:55 brouard
533: Summary: Big bug thanks to Flavia
534:
535: Even model=1+age+V2. did not work anymore
536:
1.200 brouard 537: Revision 1.199 2015/09/07 14:09:23 brouard
538: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
539:
1.199 brouard 540: Revision 1.198 2015/09/03 07:14:39 brouard
541: Summary: 0.98q5 Flavia
542:
1.198 brouard 543: Revision 1.197 2015/09/01 18:24:39 brouard
544: *** empty log message ***
545:
1.197 brouard 546: Revision 1.196 2015/08/18 23:17:52 brouard
547: Summary: 0.98q5
548:
1.196 brouard 549: Revision 1.195 2015/08/18 16:28:39 brouard
550: Summary: Adding a hack for testing purpose
551:
552: After reading the title, ftol and model lines, if the comment line has
553: a q, starting with #q, the answer at the end of the run is quit. It
554: permits to run test files in batch with ctest. The former workaround was
555: $ echo q | imach foo.imach
556:
1.195 brouard 557: Revision 1.194 2015/08/18 13:32:00 brouard
558: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
559:
1.194 brouard 560: Revision 1.193 2015/08/04 07:17:42 brouard
561: Summary: 0.98q4
562:
1.193 brouard 563: Revision 1.192 2015/07/16 16:49:02 brouard
564: Summary: Fixing some outputs
565:
1.192 brouard 566: Revision 1.191 2015/07/14 10:00:33 brouard
567: Summary: Some fixes
568:
1.191 brouard 569: Revision 1.190 2015/05/05 08:51:13 brouard
570: Summary: Adding digits in output parameters (7 digits instead of 6)
571:
572: Fix 1+age+.
573:
1.190 brouard 574: Revision 1.189 2015/04/30 14:45:16 brouard
575: Summary: 0.98q2
576:
1.189 brouard 577: Revision 1.188 2015/04/30 08:27:53 brouard
578: *** empty log message ***
579:
1.188 brouard 580: Revision 1.187 2015/04/29 09:11:15 brouard
581: *** empty log message ***
582:
1.187 brouard 583: Revision 1.186 2015/04/23 12:01:52 brouard
584: Summary: V1*age is working now, version 0.98q1
585:
586: Some codes had been disabled in order to simplify and Vn*age was
587: working in the optimization phase, ie, giving correct MLE parameters,
588: but, as usual, outputs were not correct and program core dumped.
589:
1.186 brouard 590: Revision 1.185 2015/03/11 13:26:42 brouard
591: Summary: Inclusion of compile and links command line for Intel Compiler
592:
1.185 brouard 593: Revision 1.184 2015/03/11 11:52:39 brouard
594: Summary: Back from Windows 8. Intel Compiler
595:
1.184 brouard 596: Revision 1.183 2015/03/10 20:34:32 brouard
597: Summary: 0.98q0, trying with directest, mnbrak fixed
598:
599: We use directest instead of original Powell test; probably no
600: incidence on the results, but better justifications;
601: We fixed Numerical Recipes mnbrak routine which was wrong and gave
602: wrong results.
603:
1.183 brouard 604: Revision 1.182 2015/02/12 08:19:57 brouard
605: Summary: Trying to keep directest which seems simpler and more general
606: Author: Nicolas Brouard
607:
1.182 brouard 608: Revision 1.181 2015/02/11 23:22:24 brouard
609: Summary: Comments on Powell added
610:
611: Author:
612:
1.181 brouard 613: Revision 1.180 2015/02/11 17:33:45 brouard
614: Summary: Finishing move from main to function (hpijx and prevalence_limit)
615:
1.180 brouard 616: Revision 1.179 2015/01/04 09:57:06 brouard
617: Summary: back to OS/X
618:
1.179 brouard 619: Revision 1.178 2015/01/04 09:35:48 brouard
620: *** empty log message ***
621:
1.178 brouard 622: Revision 1.177 2015/01/03 18:40:56 brouard
623: Summary: Still testing ilc32 on OSX
624:
1.177 brouard 625: Revision 1.176 2015/01/03 16:45:04 brouard
626: *** empty log message ***
627:
1.176 brouard 628: Revision 1.175 2015/01/03 16:33:42 brouard
629: *** empty log message ***
630:
1.175 brouard 631: Revision 1.174 2015/01/03 16:15:49 brouard
632: Summary: Still in cross-compilation
633:
1.174 brouard 634: Revision 1.173 2015/01/03 12:06:26 brouard
635: Summary: trying to detect cross-compilation
636:
1.173 brouard 637: Revision 1.172 2014/12/27 12:07:47 brouard
638: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
639:
1.172 brouard 640: Revision 1.171 2014/12/23 13:26:59 brouard
641: Summary: Back from Visual C
642:
643: Still problem with utsname.h on Windows
644:
1.171 brouard 645: Revision 1.170 2014/12/23 11:17:12 brouard
646: Summary: Cleaning some \%% back to %%
647:
648: The escape was mandatory for a specific compiler (which one?), but too many warnings.
649:
1.170 brouard 650: Revision 1.169 2014/12/22 23:08:31 brouard
651: Summary: 0.98p
652:
653: Outputs some informations on compiler used, OS etc. Testing on different platforms.
654:
1.169 brouard 655: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 656: Summary: update
1.169 brouard 657:
1.168 brouard 658: Revision 1.167 2014/12/22 13:50:56 brouard
659: Summary: Testing uname and compiler version and if compiled 32 or 64
660:
661: Testing on Linux 64
662:
1.167 brouard 663: Revision 1.166 2014/12/22 11:40:47 brouard
664: *** empty log message ***
665:
1.166 brouard 666: Revision 1.165 2014/12/16 11:20:36 brouard
667: Summary: After compiling on Visual C
668:
669: * imach.c (Module): Merging 1.61 to 1.162
670:
1.165 brouard 671: Revision 1.164 2014/12/16 10:52:11 brouard
672: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
673:
674: * imach.c (Module): Merging 1.61 to 1.162
675:
1.164 brouard 676: Revision 1.163 2014/12/16 10:30:11 brouard
677: * imach.c (Module): Merging 1.61 to 1.162
678:
1.163 brouard 679: Revision 1.162 2014/09/25 11:43:39 brouard
680: Summary: temporary backup 0.99!
681:
1.162 brouard 682: Revision 1.1 2014/09/16 11:06:58 brouard
683: Summary: With some code (wrong) for nlopt
684:
685: Author:
686:
687: Revision 1.161 2014/09/15 20:41:41 brouard
688: Summary: Problem with macro SQR on Intel compiler
689:
1.161 brouard 690: Revision 1.160 2014/09/02 09:24:05 brouard
691: *** empty log message ***
692:
1.160 brouard 693: Revision 1.159 2014/09/01 10:34:10 brouard
694: Summary: WIN32
695: Author: Brouard
696:
1.159 brouard 697: Revision 1.158 2014/08/27 17:11:51 brouard
698: *** empty log message ***
699:
1.158 brouard 700: Revision 1.157 2014/08/27 16:26:55 brouard
701: Summary: Preparing windows Visual studio version
702: Author: Brouard
703:
704: In order to compile on Visual studio, time.h is now correct and time_t
705: and tm struct should be used. difftime should be used but sometimes I
706: just make the differences in raw time format (time(&now).
707: Trying to suppress #ifdef LINUX
708: Add xdg-open for __linux in order to open default browser.
709:
1.157 brouard 710: Revision 1.156 2014/08/25 20:10:10 brouard
711: *** empty log message ***
712:
1.156 brouard 713: Revision 1.155 2014/08/25 18:32:34 brouard
714: Summary: New compile, minor changes
715: Author: Brouard
716:
1.155 brouard 717: Revision 1.154 2014/06/20 17:32:08 brouard
718: Summary: Outputs now all graphs of convergence to period prevalence
719:
1.154 brouard 720: Revision 1.153 2014/06/20 16:45:46 brouard
721: Summary: If 3 live state, convergence to period prevalence on same graph
722: Author: Brouard
723:
1.153 brouard 724: Revision 1.152 2014/06/18 17:54:09 brouard
725: Summary: open browser, use gnuplot on same dir than imach if not found in the path
726:
1.152 brouard 727: Revision 1.151 2014/06/18 16:43:30 brouard
728: *** empty log message ***
729:
1.151 brouard 730: Revision 1.150 2014/06/18 16:42:35 brouard
731: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
732: Author: brouard
733:
1.150 brouard 734: Revision 1.149 2014/06/18 15:51:14 brouard
735: Summary: Some fixes in parameter files errors
736: Author: Nicolas Brouard
737:
1.149 brouard 738: Revision 1.148 2014/06/17 17:38:48 brouard
739: Summary: Nothing new
740: Author: Brouard
741:
742: Just a new packaging for OS/X version 0.98nS
743:
1.148 brouard 744: Revision 1.147 2014/06/16 10:33:11 brouard
745: *** empty log message ***
746:
1.147 brouard 747: Revision 1.146 2014/06/16 10:20:28 brouard
748: Summary: Merge
749: Author: Brouard
750:
751: Merge, before building revised version.
752:
1.146 brouard 753: Revision 1.145 2014/06/10 21:23:15 brouard
754: Summary: Debugging with valgrind
755: Author: Nicolas Brouard
756:
757: Lot of changes in order to output the results with some covariates
758: After the Edimburgh REVES conference 2014, it seems mandatory to
759: improve the code.
760: No more memory valgrind error but a lot has to be done in order to
761: continue the work of splitting the code into subroutines.
762: Also, decodemodel has been improved. Tricode is still not
763: optimal. nbcode should be improved. Documentation has been added in
764: the source code.
765:
1.144 brouard 766: Revision 1.143 2014/01/26 09:45:38 brouard
767: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
768:
769: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
770: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
771:
1.143 brouard 772: Revision 1.142 2014/01/26 03:57:36 brouard
773: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
774:
775: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
776:
1.142 brouard 777: Revision 1.141 2014/01/26 02:42:01 brouard
778: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
779:
1.141 brouard 780: Revision 1.140 2011/09/02 10:37:54 brouard
781: Summary: times.h is ok with mingw32 now.
782:
1.140 brouard 783: Revision 1.139 2010/06/14 07:50:17 brouard
784: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
785: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
786:
1.139 brouard 787: Revision 1.138 2010/04/30 18:19:40 brouard
788: *** empty log message ***
789:
1.138 brouard 790: Revision 1.137 2010/04/29 18:11:38 brouard
791: (Module): Checking covariates for more complex models
792: than V1+V2. A lot of change to be done. Unstable.
793:
1.137 brouard 794: Revision 1.136 2010/04/26 20:30:53 brouard
795: (Module): merging some libgsl code. Fixing computation
796: of likelione (using inter/intrapolation if mle = 0) in order to
797: get same likelihood as if mle=1.
798: Some cleaning of code and comments added.
799:
1.136 brouard 800: Revision 1.135 2009/10/29 15:33:14 brouard
801: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
802:
1.135 brouard 803: Revision 1.134 2009/10/29 13:18:53 brouard
804: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
805:
1.134 brouard 806: Revision 1.133 2009/07/06 10:21:25 brouard
807: just nforces
808:
1.133 brouard 809: Revision 1.132 2009/07/06 08:22:05 brouard
810: Many tings
811:
1.132 brouard 812: Revision 1.131 2009/06/20 16:22:47 brouard
813: Some dimensions resccaled
814:
1.131 brouard 815: Revision 1.130 2009/05/26 06:44:34 brouard
816: (Module): Max Covariate is now set to 20 instead of 8. A
817: lot of cleaning with variables initialized to 0. Trying to make
818: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
819:
1.130 brouard 820: Revision 1.129 2007/08/31 13:49:27 lievre
821: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
822:
1.129 lievre 823: Revision 1.128 2006/06/30 13:02:05 brouard
824: (Module): Clarifications on computing e.j
825:
1.128 brouard 826: Revision 1.127 2006/04/28 18:11:50 brouard
827: (Module): Yes the sum of survivors was wrong since
828: imach-114 because nhstepm was no more computed in the age
829: loop. Now we define nhstepma in the age loop.
830: (Module): In order to speed up (in case of numerous covariates) we
831: compute health expectancies (without variances) in a first step
832: and then all the health expectancies with variances or standard
833: deviation (needs data from the Hessian matrices) which slows the
834: computation.
835: In the future we should be able to stop the program is only health
836: expectancies and graph are needed without standard deviations.
837:
1.127 brouard 838: Revision 1.126 2006/04/28 17:23:28 brouard
839: (Module): Yes the sum of survivors was wrong since
840: imach-114 because nhstepm was no more computed in the age
841: loop. Now we define nhstepma in the age loop.
842: Version 0.98h
843:
1.126 brouard 844: Revision 1.125 2006/04/04 15:20:31 lievre
845: Errors in calculation of health expectancies. Age was not initialized.
846: Forecasting file added.
847:
848: Revision 1.124 2006/03/22 17:13:53 lievre
849: Parameters are printed with %lf instead of %f (more numbers after the comma).
850: The log-likelihood is printed in the log file
851:
852: Revision 1.123 2006/03/20 10:52:43 brouard
853: * imach.c (Module): <title> changed, corresponds to .htm file
854: name. <head> headers where missing.
855:
856: * imach.c (Module): Weights can have a decimal point as for
857: English (a comma might work with a correct LC_NUMERIC environment,
858: otherwise the weight is truncated).
859: Modification of warning when the covariates values are not 0 or
860: 1.
861: Version 0.98g
862:
863: Revision 1.122 2006/03/20 09:45:41 brouard
864: (Module): Weights can have a decimal point as for
865: English (a comma might work with a correct LC_NUMERIC environment,
866: otherwise the weight is truncated).
867: Modification of warning when the covariates values are not 0 or
868: 1.
869: Version 0.98g
870:
871: Revision 1.121 2006/03/16 17:45:01 lievre
872: * imach.c (Module): Comments concerning covariates added
873:
874: * imach.c (Module): refinements in the computation of lli if
875: status=-2 in order to have more reliable computation if stepm is
876: not 1 month. Version 0.98f
877:
878: Revision 1.120 2006/03/16 15:10:38 lievre
879: (Module): refinements in the computation of lli if
880: status=-2 in order to have more reliable computation if stepm is
881: not 1 month. Version 0.98f
882:
883: Revision 1.119 2006/03/15 17:42:26 brouard
884: (Module): Bug if status = -2, the loglikelihood was
885: computed as likelihood omitting the logarithm. Version O.98e
886:
887: Revision 1.118 2006/03/14 18:20:07 brouard
888: (Module): varevsij Comments added explaining the second
889: table of variances if popbased=1 .
890: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
891: (Module): Function pstamp added
892: (Module): Version 0.98d
893:
894: Revision 1.117 2006/03/14 17:16:22 brouard
895: (Module): varevsij Comments added explaining the second
896: table of variances if popbased=1 .
897: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
898: (Module): Function pstamp added
899: (Module): Version 0.98d
900:
901: Revision 1.116 2006/03/06 10:29:27 brouard
902: (Module): Variance-covariance wrong links and
903: varian-covariance of ej. is needed (Saito).
904:
905: Revision 1.115 2006/02/27 12:17:45 brouard
906: (Module): One freematrix added in mlikeli! 0.98c
907:
908: Revision 1.114 2006/02/26 12:57:58 brouard
909: (Module): Some improvements in processing parameter
910: filename with strsep.
911:
912: Revision 1.113 2006/02/24 14:20:24 brouard
913: (Module): Memory leaks checks with valgrind and:
914: datafile was not closed, some imatrix were not freed and on matrix
915: allocation too.
916:
917: Revision 1.112 2006/01/30 09:55:26 brouard
918: (Module): Back to gnuplot.exe instead of wgnuplot.exe
919:
920: Revision 1.111 2006/01/25 20:38:18 brouard
921: (Module): Lots of cleaning and bugs added (Gompertz)
922: (Module): Comments can be added in data file. Missing date values
923: can be a simple dot '.'.
924:
925: Revision 1.110 2006/01/25 00:51:50 brouard
926: (Module): Lots of cleaning and bugs added (Gompertz)
927:
928: Revision 1.109 2006/01/24 19:37:15 brouard
929: (Module): Comments (lines starting with a #) are allowed in data.
930:
931: Revision 1.108 2006/01/19 18:05:42 lievre
932: Gnuplot problem appeared...
933: To be fixed
934:
935: Revision 1.107 2006/01/19 16:20:37 brouard
936: Test existence of gnuplot in imach path
937:
938: Revision 1.106 2006/01/19 13:24:36 brouard
939: Some cleaning and links added in html output
940:
941: Revision 1.105 2006/01/05 20:23:19 lievre
942: *** empty log message ***
943:
944: Revision 1.104 2005/09/30 16:11:43 lievre
945: (Module): sump fixed, loop imx fixed, and simplifications.
946: (Module): If the status is missing at the last wave but we know
947: that the person is alive, then we can code his/her status as -2
948: (instead of missing=-1 in earlier versions) and his/her
949: contributions to the likelihood is 1 - Prob of dying from last
950: health status (= 1-p13= p11+p12 in the easiest case of somebody in
951: the healthy state at last known wave). Version is 0.98
952:
953: Revision 1.103 2005/09/30 15:54:49 lievre
954: (Module): sump fixed, loop imx fixed, and simplifications.
955:
956: Revision 1.102 2004/09/15 17:31:30 brouard
957: Add the possibility to read data file including tab characters.
958:
959: Revision 1.101 2004/09/15 10:38:38 brouard
960: Fix on curr_time
961:
962: Revision 1.100 2004/07/12 18:29:06 brouard
963: Add version for Mac OS X. Just define UNIX in Makefile
964:
965: Revision 1.99 2004/06/05 08:57:40 brouard
966: *** empty log message ***
967:
968: Revision 1.98 2004/05/16 15:05:56 brouard
969: New version 0.97 . First attempt to estimate force of mortality
970: directly from the data i.e. without the need of knowing the health
971: state at each age, but using a Gompertz model: log u =a + b*age .
972: This is the basic analysis of mortality and should be done before any
973: other analysis, in order to test if the mortality estimated from the
974: cross-longitudinal survey is different from the mortality estimated
975: from other sources like vital statistic data.
976:
977: The same imach parameter file can be used but the option for mle should be -3.
978:
1.324 brouard 979: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 980: former routines in order to include the new code within the former code.
981:
982: The output is very simple: only an estimate of the intercept and of
983: the slope with 95% confident intervals.
984:
985: Current limitations:
986: A) Even if you enter covariates, i.e. with the
987: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
988: B) There is no computation of Life Expectancy nor Life Table.
989:
990: Revision 1.97 2004/02/20 13:25:42 lievre
991: Version 0.96d. Population forecasting command line is (temporarily)
992: suppressed.
993:
994: Revision 1.96 2003/07/15 15:38:55 brouard
995: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
996: rewritten within the same printf. Workaround: many printfs.
997:
998: Revision 1.95 2003/07/08 07:54:34 brouard
999: * imach.c (Repository):
1000: (Repository): Using imachwizard code to output a more meaningful covariance
1001: matrix (cov(a12,c31) instead of numbers.
1002:
1003: Revision 1.94 2003/06/27 13:00:02 brouard
1004: Just cleaning
1005:
1006: Revision 1.93 2003/06/25 16:33:55 brouard
1007: (Module): On windows (cygwin) function asctime_r doesn't
1008: exist so I changed back to asctime which exists.
1009: (Module): Version 0.96b
1010:
1011: Revision 1.92 2003/06/25 16:30:45 brouard
1012: (Module): On windows (cygwin) function asctime_r doesn't
1013: exist so I changed back to asctime which exists.
1014:
1015: Revision 1.91 2003/06/25 15:30:29 brouard
1016: * imach.c (Repository): Duplicated warning errors corrected.
1017: (Repository): Elapsed time after each iteration is now output. It
1018: helps to forecast when convergence will be reached. Elapsed time
1019: is stamped in powell. We created a new html file for the graphs
1020: concerning matrix of covariance. It has extension -cov.htm.
1021:
1022: Revision 1.90 2003/06/24 12:34:15 brouard
1023: (Module): Some bugs corrected for windows. Also, when
1024: mle=-1 a template is output in file "or"mypar.txt with the design
1025: of the covariance matrix to be input.
1026:
1027: Revision 1.89 2003/06/24 12:30:52 brouard
1028: (Module): Some bugs corrected for windows. Also, when
1029: mle=-1 a template is output in file "or"mypar.txt with the design
1030: of the covariance matrix to be input.
1031:
1032: Revision 1.88 2003/06/23 17:54:56 brouard
1033: * 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.
1034:
1035: Revision 1.87 2003/06/18 12:26:01 brouard
1036: Version 0.96
1037:
1038: Revision 1.86 2003/06/17 20:04:08 brouard
1039: (Module): Change position of html and gnuplot routines and added
1040: routine fileappend.
1041:
1042: Revision 1.85 2003/06/17 13:12:43 brouard
1043: * imach.c (Repository): Check when date of death was earlier that
1044: current date of interview. It may happen when the death was just
1045: prior to the death. In this case, dh was negative and likelihood
1046: was wrong (infinity). We still send an "Error" but patch by
1047: assuming that the date of death was just one stepm after the
1048: interview.
1049: (Repository): Because some people have very long ID (first column)
1050: we changed int to long in num[] and we added a new lvector for
1051: memory allocation. But we also truncated to 8 characters (left
1052: truncation)
1053: (Repository): No more line truncation errors.
1054:
1055: Revision 1.84 2003/06/13 21:44:43 brouard
1056: * imach.c (Repository): Replace "freqsummary" at a correct
1057: place. It differs from routine "prevalence" which may be called
1058: many times. Probs is memory consuming and must be used with
1059: parcimony.
1060: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1061:
1062: Revision 1.83 2003/06/10 13:39:11 lievre
1063: *** empty log message ***
1064:
1065: Revision 1.82 2003/06/05 15:57:20 brouard
1066: Add log in imach.c and fullversion number is now printed.
1067:
1068: */
1069: /*
1070: Interpolated Markov Chain
1071:
1072: Short summary of the programme:
1073:
1.227 brouard 1074: This program computes Healthy Life Expectancies or State-specific
1075: (if states aren't health statuses) Expectancies from
1076: cross-longitudinal data. Cross-longitudinal data consist in:
1077:
1078: -1- a first survey ("cross") where individuals from different ages
1079: are interviewed on their health status or degree of disability (in
1080: the case of a health survey which is our main interest)
1081:
1082: -2- at least a second wave of interviews ("longitudinal") which
1083: measure each change (if any) in individual health status. Health
1084: expectancies are computed from the time spent in each health state
1085: according to a model. More health states you consider, more time is
1086: necessary to reach the Maximum Likelihood of the parameters involved
1087: in the model. The simplest model is the multinomial logistic model
1088: where pij is the probability to be observed in state j at the second
1089: wave conditional to be observed in state i at the first
1090: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1091: etc , where 'age' is age and 'sex' is a covariate. If you want to
1092: have a more complex model than "constant and age", you should modify
1093: the program where the markup *Covariates have to be included here
1094: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1095: convergence.
1096:
1097: The advantage of this computer programme, compared to a simple
1098: multinomial logistic model, is clear when the delay between waves is not
1099: identical for each individual. Also, if a individual missed an
1100: intermediate interview, the information is lost, but taken into
1101: account using an interpolation or extrapolation.
1102:
1103: hPijx is the probability to be observed in state i at age x+h
1104: conditional to the observed state i at age x. The delay 'h' can be
1105: split into an exact number (nh*stepm) of unobserved intermediate
1106: states. This elementary transition (by month, quarter,
1107: semester or year) is modelled as a multinomial logistic. The hPx
1108: matrix is simply the matrix product of nh*stepm elementary matrices
1109: and the contribution of each individual to the likelihood is simply
1110: hPijx.
1111:
1112: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1113: of the life expectancies. It also computes the period (stable) prevalence.
1114:
1115: Back prevalence and projections:
1.227 brouard 1116:
1117: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1118: double agemaxpar, double ftolpl, int *ncvyearp, double
1119: dateprev1,double dateprev2, int firstpass, int lastpass, int
1120: mobilavproj)
1121:
1122: Computes the back prevalence limit for any combination of
1123: covariate values k at any age between ageminpar and agemaxpar and
1124: returns it in **bprlim. In the loops,
1125:
1126: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1127: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1128:
1129: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1130: Computes for any combination of covariates k and any age between bage and fage
1131: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1132: oldm=oldms;savm=savms;
1.227 brouard 1133:
1.267 brouard 1134: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1135: Computes the transition matrix starting at age 'age' over
1136: 'nhstepm*hstepm*stepm' months (i.e. until
1137: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1138: nhstepm*hstepm matrices.
1139:
1140: Returns p3mat[i][j][h] after calling
1141: p3mat[i][j][h]=matprod2(newm,
1142: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1143: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1144: oldm);
1.226 brouard 1145:
1146: Important routines
1147:
1148: - func (or funcone), computes logit (pij) distinguishing
1149: o fixed variables (single or product dummies or quantitative);
1150: o varying variables by:
1151: (1) wave (single, product dummies, quantitative),
1152: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1153: % fixed dummy (treated) or quantitative (not done because time-consuming);
1154: % varying dummy (not done) or quantitative (not done);
1155: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1156: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1157: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1158: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1159: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1160:
1.226 brouard 1161:
1162:
1.324 brouard 1163: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1164: Institut national d'études démographiques, Paris.
1.126 brouard 1165: This software have been partly granted by Euro-REVES, a concerted action
1166: from the European Union.
1167: It is copyrighted identically to a GNU software product, ie programme and
1168: software can be distributed freely for non commercial use. Latest version
1169: can be accessed at http://euroreves.ined.fr/imach .
1170:
1171: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1172: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1173:
1174: **********************************************************************/
1175: /*
1176: main
1177: read parameterfile
1178: read datafile
1179: concatwav
1180: freqsummary
1181: if (mle >= 1)
1182: mlikeli
1183: print results files
1184: if mle==1
1185: computes hessian
1186: read end of parameter file: agemin, agemax, bage, fage, estepm
1187: begin-prev-date,...
1188: open gnuplot file
1189: open html file
1.145 brouard 1190: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1191: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1192: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1193: freexexit2 possible for memory heap.
1194:
1195: h Pij x | pij_nom ficrestpij
1196: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1197: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1198: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1199:
1200: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1201: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1202: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1203: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1204: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1205:
1.126 brouard 1206: forecasting if prevfcast==1 prevforecast call prevalence()
1207: health expectancies
1208: Variance-covariance of DFLE
1209: prevalence()
1210: movingaverage()
1211: varevsij()
1212: if popbased==1 varevsij(,popbased)
1213: total life expectancies
1214: Variance of period (stable) prevalence
1215: end
1216: */
1217:
1.187 brouard 1218: /* #define DEBUG */
1219: /* #define DEBUGBRENT */
1.203 brouard 1220: /* #define DEBUGLINMIN */
1221: /* #define DEBUGHESS */
1222: #define DEBUGHESSIJ
1.224 brouard 1223: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1224: #define POWELL /* Instead of NLOPT */
1.224 brouard 1225: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1226: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1227: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1228: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1229:
1230: #include <math.h>
1231: #include <stdio.h>
1232: #include <stdlib.h>
1233: #include <string.h>
1.226 brouard 1234: #include <ctype.h>
1.159 brouard 1235:
1236: #ifdef _WIN32
1237: #include <io.h>
1.172 brouard 1238: #include <windows.h>
1239: #include <tchar.h>
1.159 brouard 1240: #else
1.126 brouard 1241: #include <unistd.h>
1.159 brouard 1242: #endif
1.126 brouard 1243:
1244: #include <limits.h>
1245: #include <sys/types.h>
1.171 brouard 1246:
1247: #if defined(__GNUC__)
1248: #include <sys/utsname.h> /* Doesn't work on Windows */
1249: #endif
1250:
1.126 brouard 1251: #include <sys/stat.h>
1252: #include <errno.h>
1.159 brouard 1253: /* extern int errno; */
1.126 brouard 1254:
1.157 brouard 1255: /* #ifdef LINUX */
1256: /* #include <time.h> */
1257: /* #include "timeval.h" */
1258: /* #else */
1259: /* #include <sys/time.h> */
1260: /* #endif */
1261:
1.126 brouard 1262: #include <time.h>
1263:
1.136 brouard 1264: #ifdef GSL
1265: #include <gsl/gsl_errno.h>
1266: #include <gsl/gsl_multimin.h>
1267: #endif
1268:
1.167 brouard 1269:
1.162 brouard 1270: #ifdef NLOPT
1271: #include <nlopt.h>
1272: typedef struct {
1273: double (* function)(double [] );
1274: } myfunc_data ;
1275: #endif
1276:
1.126 brouard 1277: /* #include <libintl.h> */
1278: /* #define _(String) gettext (String) */
1279:
1.251 brouard 1280: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1281:
1282: #define GNUPLOTPROGRAM "gnuplot"
1283: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1284: #define FILENAMELENGTH 256
1.126 brouard 1285:
1286: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1287: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1288:
1.144 brouard 1289: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1290: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1291:
1292: #define NINTERVMAX 8
1.144 brouard 1293: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1294: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1295: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1296: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1297: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1298: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1299: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1300: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1301: /* #define AGESUP 130 */
1.288 brouard 1302: /* #define AGESUP 150 */
1303: #define AGESUP 200
1.268 brouard 1304: #define AGEINF 0
1.218 brouard 1305: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1306: #define AGEBASE 40
1.194 brouard 1307: #define AGEOVERFLOW 1.e20
1.164 brouard 1308: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1309: #ifdef _WIN32
1310: #define DIRSEPARATOR '\\'
1311: #define CHARSEPARATOR "\\"
1312: #define ODIRSEPARATOR '/'
1313: #else
1.126 brouard 1314: #define DIRSEPARATOR '/'
1315: #define CHARSEPARATOR "/"
1316: #define ODIRSEPARATOR '\\'
1317: #endif
1318:
1.341 ! brouard 1319: /* $Id: imach.c,v 1.340 2022/09/11 07:53:11 brouard Exp $ */
1.126 brouard 1320: /* $State: Exp $ */
1.196 brouard 1321: #include "version.h"
1322: char version[]=__IMACH_VERSION__;
1.337 brouard 1323: char copyright[]="September 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
1.341 ! brouard 1324: char fullversion[]="$Revision: 1.340 $ $Date: 2022/09/11 07:53:11 $";
1.126 brouard 1325: char strstart[80];
1326: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1327: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1328: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1329: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1330: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1331: 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 1332: 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 1333: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1334: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1335: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1336: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1337: 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 1338: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1339: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1340: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.232 brouard 1341: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1342: int nsd=0; /**< Total number of single dummy variables (output) */
1343: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1344: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1345: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1346: int ntveff=0; /**< ntveff number of effective time varying variables */
1347: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1348: int cptcov=0; /* Working variable */
1.334 brouard 1349: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1350: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1351: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1352: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1353: int nlstate=2; /* Number of live states */
1354: int ndeath=1; /* Number of dead states */
1.130 brouard 1355: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1356: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1357: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1358: int popbased=0;
1359:
1360: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1361: int maxwav=0; /* Maxim number of waves */
1362: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1363: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1364: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1365: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1366: int mle=1, weightopt=0;
1.126 brouard 1367: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1368: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1369: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1370: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1371: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1372: int selected(int kvar); /* Is covariate kvar selected for printing results */
1373:
1.130 brouard 1374: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1375: double **matprod2(); /* test */
1.126 brouard 1376: double **oldm, **newm, **savm; /* Working pointers to matrices */
1377: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1378: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1379:
1.136 brouard 1380: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1381: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1382: FILE *ficlog, *ficrespow;
1.130 brouard 1383: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1384: double fretone; /* Only one call to likelihood */
1.130 brouard 1385: long ipmx=0; /* Number of contributions */
1.126 brouard 1386: double sw; /* Sum of weights */
1387: char filerespow[FILENAMELENGTH];
1388: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1389: FILE *ficresilk;
1390: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1391: FILE *ficresprobmorprev;
1392: FILE *fichtm, *fichtmcov; /* Html File */
1393: FILE *ficreseij;
1394: char filerese[FILENAMELENGTH];
1395: FILE *ficresstdeij;
1396: char fileresstde[FILENAMELENGTH];
1397: FILE *ficrescveij;
1398: char filerescve[FILENAMELENGTH];
1399: FILE *ficresvij;
1400: char fileresv[FILENAMELENGTH];
1.269 brouard 1401:
1.126 brouard 1402: char title[MAXLINE];
1.234 brouard 1403: char model[MAXLINE]; /**< The model line */
1.217 brouard 1404: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1405: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1406: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1407: char command[FILENAMELENGTH];
1408: int outcmd=0;
1409:
1.217 brouard 1410: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1411: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1412: char filelog[FILENAMELENGTH]; /* Log file */
1413: char filerest[FILENAMELENGTH];
1414: char fileregp[FILENAMELENGTH];
1415: char popfile[FILENAMELENGTH];
1416:
1417: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1418:
1.157 brouard 1419: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1420: /* struct timezone tzp; */
1421: /* extern int gettimeofday(); */
1422: struct tm tml, *gmtime(), *localtime();
1423:
1424: extern time_t time();
1425:
1426: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1427: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1428: struct tm tm;
1429:
1.126 brouard 1430: char strcurr[80], strfor[80];
1431:
1432: char *endptr;
1433: long lval;
1434: double dval;
1435:
1436: #define NR_END 1
1437: #define FREE_ARG char*
1438: #define FTOL 1.0e-10
1439:
1440: #define NRANSI
1.240 brouard 1441: #define ITMAX 200
1442: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1443:
1444: #define TOL 2.0e-4
1445:
1446: #define CGOLD 0.3819660
1447: #define ZEPS 1.0e-10
1448: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1449:
1450: #define GOLD 1.618034
1451: #define GLIMIT 100.0
1452: #define TINY 1.0e-20
1453:
1454: static double maxarg1,maxarg2;
1455: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1456: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1457:
1458: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1459: #define rint(a) floor(a+0.5)
1.166 brouard 1460: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1461: #define mytinydouble 1.0e-16
1.166 brouard 1462: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1463: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1464: /* static double dsqrarg; */
1465: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1466: static double sqrarg;
1467: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1468: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1469: int agegomp= AGEGOMP;
1470:
1471: int imx;
1472: int stepm=1;
1473: /* Stepm, step in month: minimum step interpolation*/
1474:
1475: int estepm;
1476: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1477:
1478: int m,nb;
1479: long *num;
1.197 brouard 1480: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1481: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1482: covariate for which somebody answered excluding
1483: undefined. Usually 2: 0 and 1. */
1484: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1485: covariate for which somebody answered including
1486: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1487: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1488: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1489: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1490: 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 1491: double *ageexmed,*agecens;
1492: double dateintmean=0;
1.296 brouard 1493: double anprojd, mprojd, jprojd; /* For eventual projections */
1494: double anprojf, mprojf, jprojf;
1.126 brouard 1495:
1.296 brouard 1496: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1497: double anbackf, mbackf, jbackf;
1498: double jintmean,mintmean,aintmean;
1.126 brouard 1499: double *weight;
1500: int **s; /* Status */
1.141 brouard 1501: double *agedc;
1.145 brouard 1502: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1503: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1504: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1505: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 ! brouard 1506: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1507: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1508: double idx;
1509: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1510: /* Some documentation */
1511: /* Design original data
1512: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1513: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1514: * ntv=3 nqtv=1
1.330 brouard 1515: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1516: * For time varying covariate, quanti or dummies
1517: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 ! brouard 1518: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1519: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1520: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1521: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1522: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1523: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1524: * k= 1 2 3 4 5 6 7 8 9 10 11
1525: */
1526: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1527: /* 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
1528: # States 1=Coresidence, 2 Living alone, 3 Institution
1529: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1530: */
1.319 brouard 1531: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1532: /* k 1 2 3 4 5 6 7 8 9 */
1533: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1534: /* fixed or varying), 1 for age product, 2 for*/
1535: /* product */
1536: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1537: /*(single or product without age), 2 dummy*/
1538: /* with age product, 3 quant with age product*/
1539: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1540: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1.330 brouard 1541: /*TnsdVar[Tvar] 1 2 3 */
1.337 brouard 1542: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.319 brouard 1543: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.338 brouard 1544: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1.319 brouard 1545: /* nsq 1 2 */ /* Counting single quantit tv */
1546: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1547: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1548: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1549: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1550: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1551: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1552: /* 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 1553: /* 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 1554: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1555: /* Type */
1556: /* V 1 2 3 4 5 */
1557: /* F F V V V */
1558: /* D Q D D Q */
1559: /* */
1560: int *TvarsD;
1.330 brouard 1561: int *TnsdVar;
1.234 brouard 1562: int *TvarsDind;
1563: int *TvarsQ;
1564: int *TvarsQind;
1565:
1.318 brouard 1566: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1567: int nresult=0;
1.258 brouard 1568: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1569: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1570: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1571: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1572: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1573: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1574: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1575: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1576: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1577: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1578: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1579:
1580: /* 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
1581: # States 1=Coresidence, 2 Living alone, 3 Institution
1582: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1583: */
1.234 brouard 1584: /* 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 1585: 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 */
1586: 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 */
1587: 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 */
1588: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1589: 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 */
1590: 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 1591: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1592: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1593: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1594: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1595: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1596: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1597: 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 */
1598: 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 1599: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1600: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1601: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1602: /* model V1+V3+age*V1+age*V3+V1*V3 */
1603: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1604: /* TvarVV={3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1605: /* TvarVVind={2,5,5}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1.230 brouard 1606: int *Tvarsel; /**< Selected covariates for output */
1607: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1608: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1609: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1610: 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 1611: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1612: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1613: int *Tage;
1.227 brouard 1614: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1615: 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 1616: 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*/
1617: 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 1618: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1619: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1620: int **Tvard;
1.330 brouard 1621: int **Tvardk;
1.227 brouard 1622: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1623: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1624: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1625: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1626: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1627: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1628: double *lsurv, *lpop, *tpop;
1629:
1.231 brouard 1630: #define FD 1; /* Fixed dummy covariate */
1631: #define FQ 2; /* Fixed quantitative covariate */
1632: #define FP 3; /* Fixed product covariate */
1633: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1634: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1635: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1636: #define VD 10; /* Varying dummy covariate */
1637: #define VQ 11; /* Varying quantitative covariate */
1638: #define VP 12; /* Varying product covariate */
1639: #define VPDD 13; /* Varying product dummy*dummy covariate */
1640: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1641: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1642: #define APFD 16; /* Age product * fixed dummy covariate */
1643: #define APFQ 17; /* Age product * fixed quantitative covariate */
1644: #define APVD 18; /* Age product * varying dummy covariate */
1645: #define APVQ 19; /* Age product * varying quantitative covariate */
1646:
1647: #define FTYPE 1; /* Fixed covariate */
1648: #define VTYPE 2; /* Varying covariate (loop in wave) */
1649: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1650:
1651: struct kmodel{
1652: int maintype; /* main type */
1653: int subtype; /* subtype */
1654: };
1655: struct kmodel modell[NCOVMAX];
1656:
1.143 brouard 1657: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1658: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1659:
1660: /**************** split *************************/
1661: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1662: {
1663: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1664: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1665: */
1666: char *ss; /* pointer */
1.186 brouard 1667: int l1=0, l2=0; /* length counters */
1.126 brouard 1668:
1669: l1 = strlen(path ); /* length of path */
1670: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1671: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1672: if ( ss == NULL ) { /* no directory, so determine current directory */
1673: strcpy( name, path ); /* we got the fullname name because no directory */
1674: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1675: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1676: /* get current working directory */
1677: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1678: #ifdef WIN32
1679: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1680: #else
1681: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1682: #endif
1.126 brouard 1683: return( GLOCK_ERROR_GETCWD );
1684: }
1685: /* got dirc from getcwd*/
1686: printf(" DIRC = %s \n",dirc);
1.205 brouard 1687: } else { /* strip directory from path */
1.126 brouard 1688: ss++; /* after this, the filename */
1689: l2 = strlen( ss ); /* length of filename */
1690: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1691: strcpy( name, ss ); /* save file name */
1692: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1693: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1694: printf(" DIRC2 = %s \n",dirc);
1695: }
1696: /* We add a separator at the end of dirc if not exists */
1697: l1 = strlen( dirc ); /* length of directory */
1698: if( dirc[l1-1] != DIRSEPARATOR ){
1699: dirc[l1] = DIRSEPARATOR;
1700: dirc[l1+1] = 0;
1701: printf(" DIRC3 = %s \n",dirc);
1702: }
1703: ss = strrchr( name, '.' ); /* find last / */
1704: if (ss >0){
1705: ss++;
1706: strcpy(ext,ss); /* save extension */
1707: l1= strlen( name);
1708: l2= strlen(ss)+1;
1709: strncpy( finame, name, l1-l2);
1710: finame[l1-l2]= 0;
1711: }
1712:
1713: return( 0 ); /* we're done */
1714: }
1715:
1716:
1717: /******************************************/
1718:
1719: void replace_back_to_slash(char *s, char*t)
1720: {
1721: int i;
1722: int lg=0;
1723: i=0;
1724: lg=strlen(t);
1725: for(i=0; i<= lg; i++) {
1726: (s[i] = t[i]);
1727: if (t[i]== '\\') s[i]='/';
1728: }
1729: }
1730:
1.132 brouard 1731: char *trimbb(char *out, char *in)
1.137 brouard 1732: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1733: char *s;
1734: s=out;
1735: while (*in != '\0'){
1.137 brouard 1736: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1737: in++;
1738: }
1739: *out++ = *in++;
1740: }
1741: *out='\0';
1742: return s;
1743: }
1744:
1.187 brouard 1745: /* char *substrchaine(char *out, char *in, char *chain) */
1746: /* { */
1747: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1748: /* char *s, *t; */
1749: /* t=in;s=out; */
1750: /* while ((*in != *chain) && (*in != '\0')){ */
1751: /* *out++ = *in++; */
1752: /* } */
1753:
1754: /* /\* *in matches *chain *\/ */
1755: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1756: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1757: /* } */
1758: /* in--; chain--; */
1759: /* while ( (*in != '\0')){ */
1760: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1761: /* *out++ = *in++; */
1762: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1763: /* } */
1764: /* *out='\0'; */
1765: /* out=s; */
1766: /* return out; */
1767: /* } */
1768: char *substrchaine(char *out, char *in, char *chain)
1769: {
1770: /* Substract chain 'chain' from 'in', return and output 'out' */
1771: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1772:
1773: char *strloc;
1774:
1775: strcpy (out, in);
1776: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1777: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1778: if(strloc != NULL){
1779: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1780: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1781: /* strcpy (strloc, strloc +strlen(chain));*/
1782: }
1783: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1784: return out;
1785: }
1786:
1787:
1.145 brouard 1788: char *cutl(char *blocc, char *alocc, char *in, char occ)
1789: {
1.187 brouard 1790: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1791: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1792: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1793: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1794: */
1.160 brouard 1795: char *s, *t;
1.145 brouard 1796: t=in;s=in;
1797: while ((*in != occ) && (*in != '\0')){
1798: *alocc++ = *in++;
1799: }
1800: if( *in == occ){
1801: *(alocc)='\0';
1802: s=++in;
1803: }
1804:
1805: if (s == t) {/* occ not found */
1806: *(alocc-(in-s))='\0';
1807: in=s;
1808: }
1809: while ( *in != '\0'){
1810: *blocc++ = *in++;
1811: }
1812:
1813: *blocc='\0';
1814: return t;
1815: }
1.137 brouard 1816: char *cutv(char *blocc, char *alocc, char *in, char occ)
1817: {
1.187 brouard 1818: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1819: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1820: gives blocc="abcdef2ghi" and alocc="j".
1821: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1822: */
1823: char *s, *t;
1824: t=in;s=in;
1825: while (*in != '\0'){
1826: while( *in == occ){
1827: *blocc++ = *in++;
1828: s=in;
1829: }
1830: *blocc++ = *in++;
1831: }
1832: if (s == t) /* occ not found */
1833: *(blocc-(in-s))='\0';
1834: else
1835: *(blocc-(in-s)-1)='\0';
1836: in=s;
1837: while ( *in != '\0'){
1838: *alocc++ = *in++;
1839: }
1840:
1841: *alocc='\0';
1842: return s;
1843: }
1844:
1.126 brouard 1845: int nbocc(char *s, char occ)
1846: {
1847: int i,j=0;
1848: int lg=20;
1849: i=0;
1850: lg=strlen(s);
1851: for(i=0; i<= lg; i++) {
1.234 brouard 1852: if (s[i] == occ ) j++;
1.126 brouard 1853: }
1854: return j;
1855: }
1856:
1.137 brouard 1857: /* void cutv(char *u,char *v, char*t, char occ) */
1858: /* { */
1859: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1860: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1861: /* gives u="abcdef2ghi" and v="j" *\/ */
1862: /* int i,lg,j,p=0; */
1863: /* i=0; */
1864: /* lg=strlen(t); */
1865: /* for(j=0; j<=lg-1; j++) { */
1866: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1867: /* } */
1.126 brouard 1868:
1.137 brouard 1869: /* for(j=0; j<p; j++) { */
1870: /* (u[j] = t[j]); */
1871: /* } */
1872: /* u[p]='\0'; */
1.126 brouard 1873:
1.137 brouard 1874: /* for(j=0; j<= lg; j++) { */
1875: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1876: /* } */
1877: /* } */
1.126 brouard 1878:
1.160 brouard 1879: #ifdef _WIN32
1880: char * strsep(char **pp, const char *delim)
1881: {
1882: char *p, *q;
1883:
1884: if ((p = *pp) == NULL)
1885: return 0;
1886: if ((q = strpbrk (p, delim)) != NULL)
1887: {
1888: *pp = q + 1;
1889: *q = '\0';
1890: }
1891: else
1892: *pp = 0;
1893: return p;
1894: }
1895: #endif
1896:
1.126 brouard 1897: /********************** nrerror ********************/
1898:
1899: void nrerror(char error_text[])
1900: {
1901: fprintf(stderr,"ERREUR ...\n");
1902: fprintf(stderr,"%s\n",error_text);
1903: exit(EXIT_FAILURE);
1904: }
1905: /*********************** vector *******************/
1906: double *vector(int nl, int nh)
1907: {
1908: double *v;
1909: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1910: if (!v) nrerror("allocation failure in vector");
1911: return v-nl+NR_END;
1912: }
1913:
1914: /************************ free vector ******************/
1915: void free_vector(double*v, int nl, int nh)
1916: {
1917: free((FREE_ARG)(v+nl-NR_END));
1918: }
1919:
1920: /************************ivector *******************************/
1921: int *ivector(long nl,long nh)
1922: {
1923: int *v;
1924: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1925: if (!v) nrerror("allocation failure in ivector");
1926: return v-nl+NR_END;
1927: }
1928:
1929: /******************free ivector **************************/
1930: void free_ivector(int *v, long nl, long nh)
1931: {
1932: free((FREE_ARG)(v+nl-NR_END));
1933: }
1934:
1935: /************************lvector *******************************/
1936: long *lvector(long nl,long nh)
1937: {
1938: long *v;
1939: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1940: if (!v) nrerror("allocation failure in ivector");
1941: return v-nl+NR_END;
1942: }
1943:
1944: /******************free lvector **************************/
1945: void free_lvector(long *v, long nl, long nh)
1946: {
1947: free((FREE_ARG)(v+nl-NR_END));
1948: }
1949:
1950: /******************* imatrix *******************************/
1951: int **imatrix(long nrl, long nrh, long ncl, long nch)
1952: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1953: {
1954: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1955: int **m;
1956:
1957: /* allocate pointers to rows */
1958: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1959: if (!m) nrerror("allocation failure 1 in matrix()");
1960: m += NR_END;
1961: m -= nrl;
1962:
1963:
1964: /* allocate rows and set pointers to them */
1965: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1966: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1967: m[nrl] += NR_END;
1968: m[nrl] -= ncl;
1969:
1970: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1971:
1972: /* return pointer to array of pointers to rows */
1973: return m;
1974: }
1975:
1976: /****************** free_imatrix *************************/
1977: void free_imatrix(m,nrl,nrh,ncl,nch)
1978: int **m;
1979: long nch,ncl,nrh,nrl;
1980: /* free an int matrix allocated by imatrix() */
1981: {
1982: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1983: free((FREE_ARG) (m+nrl-NR_END));
1984: }
1985:
1986: /******************* matrix *******************************/
1987: double **matrix(long nrl, long nrh, long ncl, long nch)
1988: {
1989: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1990: double **m;
1991:
1992: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1993: if (!m) nrerror("allocation failure 1 in matrix()");
1994: m += NR_END;
1995: m -= nrl;
1996:
1997: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1998: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1999: m[nrl] += NR_END;
2000: m[nrl] -= ncl;
2001:
2002: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2003: return m;
1.145 brouard 2004: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2005: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2006: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2007: */
2008: }
2009:
2010: /*************************free matrix ************************/
2011: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2012: {
2013: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2014: free((FREE_ARG)(m+nrl-NR_END));
2015: }
2016:
2017: /******************* ma3x *******************************/
2018: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2019: {
2020: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2021: double ***m;
2022:
2023: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2024: if (!m) nrerror("allocation failure 1 in matrix()");
2025: m += NR_END;
2026: m -= nrl;
2027:
2028: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2029: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2030: m[nrl] += NR_END;
2031: m[nrl] -= ncl;
2032:
2033: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2034:
2035: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2036: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2037: m[nrl][ncl] += NR_END;
2038: m[nrl][ncl] -= nll;
2039: for (j=ncl+1; j<=nch; j++)
2040: m[nrl][j]=m[nrl][j-1]+nlay;
2041:
2042: for (i=nrl+1; i<=nrh; i++) {
2043: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2044: for (j=ncl+1; j<=nch; j++)
2045: m[i][j]=m[i][j-1]+nlay;
2046: }
2047: return m;
2048: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2049: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2050: */
2051: }
2052:
2053: /*************************free ma3x ************************/
2054: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2055: {
2056: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2057: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2058: free((FREE_ARG)(m+nrl-NR_END));
2059: }
2060:
2061: /*************** function subdirf ***********/
2062: char *subdirf(char fileres[])
2063: {
2064: /* Caution optionfilefiname is hidden */
2065: strcpy(tmpout,optionfilefiname);
2066: strcat(tmpout,"/"); /* Add to the right */
2067: strcat(tmpout,fileres);
2068: return tmpout;
2069: }
2070:
2071: /*************** function subdirf2 ***********/
2072: char *subdirf2(char fileres[], char *preop)
2073: {
1.314 brouard 2074: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2075: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2076: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2077: /* Caution optionfilefiname is hidden */
2078: strcpy(tmpout,optionfilefiname);
2079: strcat(tmpout,"/");
2080: strcat(tmpout,preop);
2081: strcat(tmpout,fileres);
2082: return tmpout;
2083: }
2084:
2085: /*************** function subdirf3 ***********/
2086: char *subdirf3(char fileres[], char *preop, char *preop2)
2087: {
2088:
2089: /* Caution optionfilefiname is hidden */
2090: strcpy(tmpout,optionfilefiname);
2091: strcat(tmpout,"/");
2092: strcat(tmpout,preop);
2093: strcat(tmpout,preop2);
2094: strcat(tmpout,fileres);
2095: return tmpout;
2096: }
1.213 brouard 2097:
2098: /*************** function subdirfext ***********/
2099: char *subdirfext(char fileres[], char *preop, char *postop)
2100: {
2101:
2102: strcpy(tmpout,preop);
2103: strcat(tmpout,fileres);
2104: strcat(tmpout,postop);
2105: return tmpout;
2106: }
1.126 brouard 2107:
1.213 brouard 2108: /*************** function subdirfext3 ***********/
2109: char *subdirfext3(char fileres[], char *preop, char *postop)
2110: {
2111:
2112: /* Caution optionfilefiname is hidden */
2113: strcpy(tmpout,optionfilefiname);
2114: strcat(tmpout,"/");
2115: strcat(tmpout,preop);
2116: strcat(tmpout,fileres);
2117: strcat(tmpout,postop);
2118: return tmpout;
2119: }
2120:
1.162 brouard 2121: char *asc_diff_time(long time_sec, char ascdiff[])
2122: {
2123: long sec_left, days, hours, minutes;
2124: days = (time_sec) / (60*60*24);
2125: sec_left = (time_sec) % (60*60*24);
2126: hours = (sec_left) / (60*60) ;
2127: sec_left = (sec_left) %(60*60);
2128: minutes = (sec_left) /60;
2129: sec_left = (sec_left) % (60);
2130: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2131: return ascdiff;
2132: }
2133:
1.126 brouard 2134: /***************** f1dim *************************/
2135: extern int ncom;
2136: extern double *pcom,*xicom;
2137: extern double (*nrfunc)(double []);
2138:
2139: double f1dim(double x)
2140: {
2141: int j;
2142: double f;
2143: double *xt;
2144:
2145: xt=vector(1,ncom);
2146: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2147: f=(*nrfunc)(xt);
2148: free_vector(xt,1,ncom);
2149: return f;
2150: }
2151:
2152: /*****************brent *************************/
2153: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2154: {
2155: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2156: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2157: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2158: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2159: * returned function value.
2160: */
1.126 brouard 2161: int iter;
2162: double a,b,d,etemp;
1.159 brouard 2163: double fu=0,fv,fw,fx;
1.164 brouard 2164: double ftemp=0.;
1.126 brouard 2165: double p,q,r,tol1,tol2,u,v,w,x,xm;
2166: double e=0.0;
2167:
2168: a=(ax < cx ? ax : cx);
2169: b=(ax > cx ? ax : cx);
2170: x=w=v=bx;
2171: fw=fv=fx=(*f)(x);
2172: for (iter=1;iter<=ITMAX;iter++) {
2173: xm=0.5*(a+b);
2174: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2175: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2176: printf(".");fflush(stdout);
2177: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2178: #ifdef DEBUGBRENT
1.126 brouard 2179: 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);
2180: 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);
2181: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2182: #endif
2183: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2184: *xmin=x;
2185: return fx;
2186: }
2187: ftemp=fu;
2188: if (fabs(e) > tol1) {
2189: r=(x-w)*(fx-fv);
2190: q=(x-v)*(fx-fw);
2191: p=(x-v)*q-(x-w)*r;
2192: q=2.0*(q-r);
2193: if (q > 0.0) p = -p;
2194: q=fabs(q);
2195: etemp=e;
2196: e=d;
2197: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2198: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2199: else {
1.224 brouard 2200: d=p/q;
2201: u=x+d;
2202: if (u-a < tol2 || b-u < tol2)
2203: d=SIGN(tol1,xm-x);
1.126 brouard 2204: }
2205: } else {
2206: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2207: }
2208: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2209: fu=(*f)(u);
2210: if (fu <= fx) {
2211: if (u >= x) a=x; else b=x;
2212: SHFT(v,w,x,u)
1.183 brouard 2213: SHFT(fv,fw,fx,fu)
2214: } else {
2215: if (u < x) a=u; else b=u;
2216: if (fu <= fw || w == x) {
1.224 brouard 2217: v=w;
2218: w=u;
2219: fv=fw;
2220: fw=fu;
1.183 brouard 2221: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2222: v=u;
2223: fv=fu;
1.183 brouard 2224: }
2225: }
1.126 brouard 2226: }
2227: nrerror("Too many iterations in brent");
2228: *xmin=x;
2229: return fx;
2230: }
2231:
2232: /****************** mnbrak ***********************/
2233:
2234: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2235: double (*func)(double))
1.183 brouard 2236: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2237: the downhill direction (defined by the function as evaluated at the initial points) and returns
2238: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2239: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2240: */
1.126 brouard 2241: double ulim,u,r,q, dum;
2242: double fu;
1.187 brouard 2243:
2244: double scale=10.;
2245: int iterscale=0;
2246:
2247: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2248: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2249:
2250:
2251: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2252: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2253: /* *bx = *ax - (*ax - *bx)/scale; */
2254: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2255: /* } */
2256:
1.126 brouard 2257: if (*fb > *fa) {
2258: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2259: SHFT(dum,*fb,*fa,dum)
2260: }
1.126 brouard 2261: *cx=(*bx)+GOLD*(*bx-*ax);
2262: *fc=(*func)(*cx);
1.183 brouard 2263: #ifdef DEBUG
1.224 brouard 2264: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2265: 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 2266: #endif
1.224 brouard 2267: 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 2268: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2269: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2270: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2271: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2272: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2273: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2274: fu=(*func)(u);
1.163 brouard 2275: #ifdef DEBUG
2276: /* f(x)=A(x-u)**2+f(u) */
2277: double A, fparabu;
2278: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2279: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2280: 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);
2281: 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 2282: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2283: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2284: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2285: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2286: #endif
1.184 brouard 2287: #ifdef MNBRAKORIGINAL
1.183 brouard 2288: #else
1.191 brouard 2289: /* if (fu > *fc) { */
2290: /* #ifdef DEBUG */
2291: /* printf("mnbrak4 fu > fc \n"); */
2292: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2293: /* #endif */
2294: /* /\* 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 *\\/ *\/ */
2295: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2296: /* dum=u; /\* Shifting c and u *\/ */
2297: /* u = *cx; */
2298: /* *cx = dum; */
2299: /* dum = fu; */
2300: /* fu = *fc; */
2301: /* *fc =dum; */
2302: /* } else { /\* end *\/ */
2303: /* #ifdef DEBUG */
2304: /* printf("mnbrak3 fu < fc \n"); */
2305: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2306: /* #endif */
2307: /* dum=u; /\* Shifting c and u *\/ */
2308: /* u = *cx; */
2309: /* *cx = dum; */
2310: /* dum = fu; */
2311: /* fu = *fc; */
2312: /* *fc =dum; */
2313: /* } */
1.224 brouard 2314: #ifdef DEBUGMNBRAK
2315: double A, fparabu;
2316: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2317: fparabu= *fa - A*(*ax-u)*(*ax-u);
2318: 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);
2319: 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 2320: #endif
1.191 brouard 2321: dum=u; /* Shifting c and u */
2322: u = *cx;
2323: *cx = dum;
2324: dum = fu;
2325: fu = *fc;
2326: *fc =dum;
1.183 brouard 2327: #endif
1.162 brouard 2328: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2329: #ifdef DEBUG
1.224 brouard 2330: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2331: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2332: #endif
1.126 brouard 2333: fu=(*func)(u);
2334: if (fu < *fc) {
1.183 brouard 2335: #ifdef DEBUG
1.224 brouard 2336: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2337: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2338: #endif
2339: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2340: SHFT(*fb,*fc,fu,(*func)(u))
2341: #ifdef DEBUG
2342: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2343: #endif
2344: }
1.162 brouard 2345: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2346: #ifdef DEBUG
1.224 brouard 2347: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2348: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2349: #endif
1.126 brouard 2350: u=ulim;
2351: fu=(*func)(u);
1.183 brouard 2352: } else { /* u could be left to b (if r > q parabola has a maximum) */
2353: #ifdef DEBUG
1.224 brouard 2354: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2355: 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 2356: #endif
1.126 brouard 2357: u=(*cx)+GOLD*(*cx-*bx);
2358: fu=(*func)(u);
1.224 brouard 2359: #ifdef DEBUG
2360: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2361: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2362: #endif
1.183 brouard 2363: } /* end tests */
1.126 brouard 2364: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2365: SHFT(*fa,*fb,*fc,fu)
2366: #ifdef DEBUG
1.224 brouard 2367: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2368: 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 2369: #endif
2370: } /* 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 2371: }
2372:
2373: /*************** linmin ************************/
1.162 brouard 2374: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2375: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2376: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2377: the value of func at the returned location p . This is actually all accomplished by calling the
2378: routines mnbrak and brent .*/
1.126 brouard 2379: int ncom;
2380: double *pcom,*xicom;
2381: double (*nrfunc)(double []);
2382:
1.224 brouard 2383: #ifdef LINMINORIGINAL
1.126 brouard 2384: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2385: #else
2386: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2387: #endif
1.126 brouard 2388: {
2389: double brent(double ax, double bx, double cx,
2390: double (*f)(double), double tol, double *xmin);
2391: double f1dim(double x);
2392: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2393: double *fc, double (*func)(double));
2394: int j;
2395: double xx,xmin,bx,ax;
2396: double fx,fb,fa;
1.187 brouard 2397:
1.203 brouard 2398: #ifdef LINMINORIGINAL
2399: #else
2400: double scale=10., axs, xxs; /* Scale added for infinity */
2401: #endif
2402:
1.126 brouard 2403: ncom=n;
2404: pcom=vector(1,n);
2405: xicom=vector(1,n);
2406: nrfunc=func;
2407: for (j=1;j<=n;j++) {
2408: pcom[j]=p[j];
1.202 brouard 2409: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2410: }
1.187 brouard 2411:
1.203 brouard 2412: #ifdef LINMINORIGINAL
2413: xx=1.;
2414: #else
2415: axs=0.0;
2416: xxs=1.;
2417: do{
2418: xx= xxs;
2419: #endif
1.187 brouard 2420: ax=0.;
2421: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2422: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2423: /* 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)) */
2424: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2425: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2426: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2427: /* 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 2428: #ifdef LINMINORIGINAL
2429: #else
2430: if (fx != fx){
1.224 brouard 2431: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2432: printf("|");
2433: fprintf(ficlog,"|");
1.203 brouard 2434: #ifdef DEBUGLINMIN
1.224 brouard 2435: 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 2436: #endif
2437: }
1.224 brouard 2438: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2439: #endif
2440:
1.191 brouard 2441: #ifdef DEBUGLINMIN
2442: 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 2443: 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 2444: #endif
1.224 brouard 2445: #ifdef LINMINORIGINAL
2446: #else
1.317 brouard 2447: if(fb == fx){ /* Flat function in the direction */
2448: xmin=xx;
1.224 brouard 2449: *flat=1;
1.317 brouard 2450: }else{
1.224 brouard 2451: *flat=0;
2452: #endif
2453: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2454: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2455: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2456: /* fmin = f(p[j] + xmin * xi[j]) */
2457: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2458: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2459: #ifdef DEBUG
1.224 brouard 2460: 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);
2461: 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);
2462: #endif
2463: #ifdef LINMINORIGINAL
2464: #else
2465: }
1.126 brouard 2466: #endif
1.191 brouard 2467: #ifdef DEBUGLINMIN
2468: printf("linmin end ");
1.202 brouard 2469: fprintf(ficlog,"linmin end ");
1.191 brouard 2470: #endif
1.126 brouard 2471: for (j=1;j<=n;j++) {
1.203 brouard 2472: #ifdef LINMINORIGINAL
2473: xi[j] *= xmin;
2474: #else
2475: #ifdef DEBUGLINMIN
2476: if(xxs <1.0)
2477: printf(" before xi[%d]=%12.8f", j,xi[j]);
2478: #endif
2479: 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) */
2480: #ifdef DEBUGLINMIN
2481: if(xxs <1.0)
2482: 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 );
2483: #endif
2484: #endif
1.187 brouard 2485: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2486: }
1.191 brouard 2487: #ifdef DEBUGLINMIN
1.203 brouard 2488: printf("\n");
1.191 brouard 2489: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2490: 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 2491: for (j=1;j<=n;j++) {
1.202 brouard 2492: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2493: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2494: if(j % ncovmodel == 0){
1.191 brouard 2495: printf("\n");
1.202 brouard 2496: fprintf(ficlog,"\n");
2497: }
1.191 brouard 2498: }
1.203 brouard 2499: #else
1.191 brouard 2500: #endif
1.126 brouard 2501: free_vector(xicom,1,n);
2502: free_vector(pcom,1,n);
2503: }
2504:
2505:
2506: /*************** powell ************************/
1.162 brouard 2507: /*
1.317 brouard 2508: Minimization of a function func of n variables. Input consists in an initial starting point
2509: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2510: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2511: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2512: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2513: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2514: */
1.224 brouard 2515: #ifdef LINMINORIGINAL
2516: #else
2517: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2518: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2519: #endif
1.126 brouard 2520: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2521: double (*func)(double []))
2522: {
1.224 brouard 2523: #ifdef LINMINORIGINAL
2524: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2525: double (*func)(double []));
1.224 brouard 2526: #else
1.241 brouard 2527: void linmin(double p[], double xi[], int n, double *fret,
2528: double (*func)(double []),int *flat);
1.224 brouard 2529: #endif
1.239 brouard 2530: int i,ibig,j,jk,k;
1.126 brouard 2531: double del,t,*pt,*ptt,*xit;
1.181 brouard 2532: double directest;
1.126 brouard 2533: double fp,fptt;
2534: double *xits;
2535: int niterf, itmp;
2536:
2537: pt=vector(1,n);
2538: ptt=vector(1,n);
2539: xit=vector(1,n);
2540: xits=vector(1,n);
2541: *fret=(*func)(p);
2542: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2543: rcurr_time = time(NULL);
2544: fp=(*fret); /* Initialisation */
1.126 brouard 2545: for (*iter=1;;++(*iter)) {
2546: ibig=0;
2547: del=0.0;
1.157 brouard 2548: rlast_time=rcurr_time;
2549: /* (void) gettimeofday(&curr_time,&tzp); */
2550: rcurr_time = time(NULL);
2551: curr_time = *localtime(&rcurr_time);
1.337 brouard 2552: /* 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); */
2553: /* 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); */
2554: printf("\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2555: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
1.157 brouard 2556: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2557: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2558: for (i=1;i<=n;i++) {
1.126 brouard 2559: fprintf(ficrespow," %.12lf", p[i]);
2560: }
1.239 brouard 2561: fprintf(ficrespow,"\n");fflush(ficrespow);
2562: printf("\n#model= 1 + age ");
2563: fprintf(ficlog,"\n#model= 1 + age ");
2564: if(nagesqr==1){
1.241 brouard 2565: printf(" + age*age ");
2566: fprintf(ficlog," + age*age ");
1.239 brouard 2567: }
2568: for(j=1;j <=ncovmodel-2;j++){
2569: if(Typevar[j]==0) {
2570: printf(" + V%d ",Tvar[j]);
2571: fprintf(ficlog," + V%d ",Tvar[j]);
2572: }else if(Typevar[j]==1) {
2573: printf(" + V%d*age ",Tvar[j]);
2574: fprintf(ficlog," + V%d*age ",Tvar[j]);
2575: }else if(Typevar[j]==2) {
2576: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2577: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2578: }
2579: }
1.126 brouard 2580: printf("\n");
1.239 brouard 2581: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2582: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2583: fprintf(ficlog,"\n");
1.239 brouard 2584: for(i=1,jk=1; i <=nlstate; i++){
2585: for(k=1; k <=(nlstate+ndeath); k++){
2586: if (k != i) {
2587: printf("%d%d ",i,k);
2588: fprintf(ficlog,"%d%d ",i,k);
2589: for(j=1; j <=ncovmodel; j++){
2590: printf("%12.7f ",p[jk]);
2591: fprintf(ficlog,"%12.7f ",p[jk]);
2592: jk++;
2593: }
2594: printf("\n");
2595: fprintf(ficlog,"\n");
2596: }
2597: }
2598: }
1.241 brouard 2599: if(*iter <=3 && *iter >1){
1.157 brouard 2600: tml = *localtime(&rcurr_time);
2601: strcpy(strcurr,asctime(&tml));
2602: rforecast_time=rcurr_time;
1.126 brouard 2603: itmp = strlen(strcurr);
2604: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2605: strcurr[itmp-1]='\0';
1.162 brouard 2606: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2607: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2608: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2609: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2610: forecast_time = *localtime(&rforecast_time);
2611: strcpy(strfor,asctime(&forecast_time));
2612: itmp = strlen(strfor);
2613: if(strfor[itmp-1]=='\n')
2614: strfor[itmp-1]='\0';
2615: printf(" - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
2616: fprintf(ficlog," - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2617: }
2618: }
1.187 brouard 2619: for (i=1;i<=n;i++) { /* For each direction i */
2620: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2621: fptt=(*fret);
2622: #ifdef DEBUG
1.203 brouard 2623: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2624: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2625: #endif
1.203 brouard 2626: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2627: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2628: #ifdef LINMINORIGINAL
1.188 brouard 2629: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2630: #else
2631: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2632: flatdir[i]=flat; /* Function is vanishing in that direction i */
2633: #endif
2634: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2635: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2636: /* because that direction will be replaced unless the gain del is small */
2637: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2638: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2639: /* with the new direction. */
2640: del=fabs(fptt-(*fret));
2641: ibig=i;
1.126 brouard 2642: }
2643: #ifdef DEBUG
2644: printf("%d %.12e",i,(*fret));
2645: fprintf(ficlog,"%d %.12e",i,(*fret));
2646: for (j=1;j<=n;j++) {
1.224 brouard 2647: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2648: printf(" x(%d)=%.12e",j,xit[j]);
2649: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2650: }
2651: for(j=1;j<=n;j++) {
1.225 brouard 2652: printf(" p(%d)=%.12e",j,p[j]);
2653: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2654: }
2655: printf("\n");
2656: fprintf(ficlog,"\n");
2657: #endif
1.187 brouard 2658: } /* end loop on each direction i */
2659: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2660: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2661: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2662: for(j=1;j<=n;j++) {
2663: if(flatdir[j] >0){
2664: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2665: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2666: }
1.319 brouard 2667: /* printf("\n"); */
2668: /* fprintf(ficlog,"\n"); */
2669: }
1.243 brouard 2670: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2671: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2672: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2673: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2674: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2675: /* decreased of more than 3.84 */
2676: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2677: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2678: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2679:
1.188 brouard 2680: /* Starting the program with initial values given by a former maximization will simply change */
2681: /* the scales of the directions and the directions, because the are reset to canonical directions */
2682: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2683: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2684: #ifdef DEBUG
2685: int k[2],l;
2686: k[0]=1;
2687: k[1]=-1;
2688: printf("Max: %.12e",(*func)(p));
2689: fprintf(ficlog,"Max: %.12e",(*func)(p));
2690: for (j=1;j<=n;j++) {
2691: printf(" %.12e",p[j]);
2692: fprintf(ficlog," %.12e",p[j]);
2693: }
2694: printf("\n");
2695: fprintf(ficlog,"\n");
2696: for(l=0;l<=1;l++) {
2697: for (j=1;j<=n;j++) {
2698: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2699: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2700: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2701: }
2702: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2703: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2704: }
2705: #endif
2706:
2707: free_vector(xit,1,n);
2708: free_vector(xits,1,n);
2709: free_vector(ptt,1,n);
2710: free_vector(pt,1,n);
2711: return;
1.192 brouard 2712: } /* enough precision */
1.240 brouard 2713: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2714: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2715: ptt[j]=2.0*p[j]-pt[j];
2716: xit[j]=p[j]-pt[j];
2717: pt[j]=p[j];
2718: }
1.181 brouard 2719: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2720: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2721: if (*iter <=4) {
1.225 brouard 2722: #else
2723: #endif
1.224 brouard 2724: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2725: #else
1.161 brouard 2726: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2727: #endif
1.162 brouard 2728: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2729: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2730: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2731: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2732: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2733: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2734: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2735: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2736: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2737: /* Even if f3 <f1, directest can be negative and t >0 */
2738: /* mu² and del² are equal when f3=f1 */
2739: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2740: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2741: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2742: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2743: #ifdef NRCORIGINAL
2744: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2745: #else
2746: 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 2747: t= t- del*SQR(fp-fptt);
1.183 brouard 2748: #endif
1.202 brouard 2749: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2750: #ifdef DEBUG
1.181 brouard 2751: 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);
2752: 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 2753: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2754: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2755: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2756: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2757: 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);
2758: 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);
2759: #endif
1.183 brouard 2760: #ifdef POWELLORIGINAL
2761: if (t < 0.0) { /* Then we use it for new direction */
2762: #else
1.182 brouard 2763: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2764: 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 2765: 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 2766: 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 2767: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2768: }
1.181 brouard 2769: if (directest < 0.0) { /* Then we use it for new direction */
2770: #endif
1.191 brouard 2771: #ifdef DEBUGLINMIN
1.234 brouard 2772: printf("Before linmin in direction P%d-P0\n",n);
2773: for (j=1;j<=n;j++) {
2774: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2775: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2776: if(j % ncovmodel == 0){
2777: printf("\n");
2778: fprintf(ficlog,"\n");
2779: }
2780: }
1.224 brouard 2781: #endif
2782: #ifdef LINMINORIGINAL
1.234 brouard 2783: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2784: #else
1.234 brouard 2785: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2786: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2787: #endif
1.234 brouard 2788:
1.191 brouard 2789: #ifdef DEBUGLINMIN
1.234 brouard 2790: for (j=1;j<=n;j++) {
2791: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2792: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2793: if(j % ncovmodel == 0){
2794: printf("\n");
2795: fprintf(ficlog,"\n");
2796: }
2797: }
1.224 brouard 2798: #endif
1.234 brouard 2799: for (j=1;j<=n;j++) {
2800: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2801: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2802: }
1.224 brouard 2803: #ifdef LINMINORIGINAL
2804: #else
1.234 brouard 2805: for (j=1, flatd=0;j<=n;j++) {
2806: if(flatdir[j]>0)
2807: flatd++;
2808: }
2809: if(flatd >0){
1.255 brouard 2810: printf("%d flat directions: ",flatd);
2811: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2812: for (j=1;j<=n;j++) {
2813: if(flatdir[j]>0){
2814: printf("%d ",j);
2815: fprintf(ficlog,"%d ",j);
2816: }
2817: }
2818: printf("\n");
2819: fprintf(ficlog,"\n");
1.319 brouard 2820: #ifdef FLATSUP
2821: free_vector(xit,1,n);
2822: free_vector(xits,1,n);
2823: free_vector(ptt,1,n);
2824: free_vector(pt,1,n);
2825: return;
2826: #endif
1.234 brouard 2827: }
1.191 brouard 2828: #endif
1.234 brouard 2829: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2830: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2831:
1.126 brouard 2832: #ifdef DEBUG
1.234 brouard 2833: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2834: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2835: for(j=1;j<=n;j++){
2836: printf(" %lf",xit[j]);
2837: fprintf(ficlog," %lf",xit[j]);
2838: }
2839: printf("\n");
2840: fprintf(ficlog,"\n");
1.126 brouard 2841: #endif
1.192 brouard 2842: } /* end of t or directest negative */
1.224 brouard 2843: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2844: #else
1.234 brouard 2845: } /* end if (fptt < fp) */
1.192 brouard 2846: #endif
1.225 brouard 2847: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2848: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2849: #else
1.224 brouard 2850: #endif
1.234 brouard 2851: } /* loop iteration */
1.126 brouard 2852: }
1.234 brouard 2853:
1.126 brouard 2854: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2855:
1.235 brouard 2856: 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 2857: {
1.338 brouard 2858: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2859: * (and selected quantitative values in nres)
2860: * by left multiplying the unit
2861: * matrix by transitions matrix until convergence is reached with precision ftolpl
2862: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2863: * Wx is row vector: population in state 1, population in state 2, population dead
2864: * or prevalence in state 1, prevalence in state 2, 0
2865: * newm is the matrix after multiplications, its rows are identical at a factor.
2866: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2867: * Output is prlim.
2868: * Initial matrix pimij
2869: */
1.206 brouard 2870: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2871: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2872: /* 0, 0 , 1} */
2873: /*
2874: * and after some iteration: */
2875: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2876: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2877: /* 0, 0 , 1} */
2878: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2879: /* {0.51571254859325999, 0.4842874514067399, */
2880: /* 0.51326036147820708, 0.48673963852179264} */
2881: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2882:
1.332 brouard 2883: int i, ii,j,k, k1;
1.209 brouard 2884: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2885: /* double **matprod2(); */ /* test */
1.218 brouard 2886: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2887: double **newm;
1.209 brouard 2888: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2889: int ncvloop=0;
1.288 brouard 2890: int first=0;
1.169 brouard 2891:
1.209 brouard 2892: min=vector(1,nlstate);
2893: max=vector(1,nlstate);
2894: meandiff=vector(1,nlstate);
2895:
1.218 brouard 2896: /* Starting with matrix unity */
1.126 brouard 2897: for (ii=1;ii<=nlstate+ndeath;ii++)
2898: for (j=1;j<=nlstate+ndeath;j++){
2899: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2900: }
1.169 brouard 2901:
2902: cov[1]=1.;
2903:
2904: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2905: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2906: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2907: ncvloop++;
1.126 brouard 2908: newm=savm;
2909: /* Covariates have to be included here again */
1.138 brouard 2910: cov[2]=agefin;
1.319 brouard 2911: if(nagesqr==1){
2912: cov[3]= agefin*agefin;
2913: }
1.332 brouard 2914: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
2915: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
2916: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
2917: if(Typevar[k1]==1){ /* A product with age */
2918: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
2919: }else{
2920: cov[2+nagesqr+k1]=precov[nres][k1];
2921: }
2922: }/* End of loop on model equation */
2923:
2924: /* Start of old code (replaced by a loop on position in the model equation */
2925: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
2926: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
2927: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
2928: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
2929: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
2930: /* * k 1 2 3 4 5 6 7 8 */
2931: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
2932: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
2933: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
2934: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
2935: /* *nsd=3 (1) (2) (3) */
2936: /* *TvarsD[nsd] [1]=2 1 3 */
2937: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
2938: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
2939: /* *Tage[] [1]=1 [2]=2 [3]=3 */
2940: /* *Tvard[] [1][1]=1 [2][1]=1 */
2941: /* * [1][2]=3 [2][2]=2 */
2942: /* *Tprod[](=k) [1]=1 [2]=8 */
2943: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
2944: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
2945: /* *TvarsDpType */
2946: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
2947: /* * nsd=1 (1) (2) */
2948: /* *TvarsD[nsd] 3 2 */
2949: /* *TnsdVar (3)=1 (2)=2 */
2950: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
2951: /* *Tage[] [1]=2 [2]= 3 */
2952: /* *\/ */
2953: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
2954: /* /\* 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)); *\/ */
2955: /* } */
2956: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
2957: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
2958: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
2959: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
2960: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
2961: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2962: /* /\* 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]); *\/ */
2963: /* } */
2964: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
2965: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
2966: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
2967: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
2968: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
2969: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
2970: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2971: /* } */
2972: /* /\* 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]); *\/ */
2973: /* } */
2974: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
2975: /* /\* 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]); *\/ */
2976: /* if(Dummy[Tvard[k][1]]==0){ */
2977: /* if(Dummy[Tvard[k][2]]==0){ */
2978: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
2979: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
2980: /* }else{ */
2981: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
2982: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
2983: /* } */
2984: /* }else{ */
2985: /* if(Dummy[Tvard[k][2]]==0){ */
2986: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
2987: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
2988: /* }else{ */
2989: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
2990: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
2991: /* } */
2992: /* } */
2993: /* } /\* End product without age *\/ */
2994: /* ENd of old code */
1.138 brouard 2995: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2996: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2997: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2998: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2999: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3000: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3001: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3002:
1.126 brouard 3003: savm=oldm;
3004: oldm=newm;
1.209 brouard 3005:
3006: for(j=1; j<=nlstate; j++){
3007: max[j]=0.;
3008: min[j]=1.;
3009: }
3010: for(i=1;i<=nlstate;i++){
3011: sumnew=0;
3012: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3013: for(j=1; j<=nlstate; j++){
3014: prlim[i][j]= newm[i][j]/(1-sumnew);
3015: max[j]=FMAX(max[j],prlim[i][j]);
3016: min[j]=FMIN(min[j],prlim[i][j]);
3017: }
3018: }
3019:
1.126 brouard 3020: maxmax=0.;
1.209 brouard 3021: for(j=1; j<=nlstate; j++){
3022: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3023: maxmax=FMAX(maxmax,meandiff[j]);
3024: /* 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 3025: } /* j loop */
1.203 brouard 3026: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3027: /* 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 3028: if(maxmax < ftolpl){
1.209 brouard 3029: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3030: free_vector(min,1,nlstate);
3031: free_vector(max,1,nlstate);
3032: free_vector(meandiff,1,nlstate);
1.126 brouard 3033: return prlim;
3034: }
1.288 brouard 3035: } /* agefin loop */
1.208 brouard 3036: /* After some age loop it doesn't converge */
1.288 brouard 3037: if(!first){
3038: first=1;
3039: 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 3040: 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);
3041: }else if (first >=1 && first <10){
3042: 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);
3043: first++;
3044: }else if (first ==10){
3045: 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);
3046: 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");
3047: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3048: first++;
1.288 brouard 3049: }
3050:
1.209 brouard 3051: /* 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); */
3052: free_vector(min,1,nlstate);
3053: free_vector(max,1,nlstate);
3054: free_vector(meandiff,1,nlstate);
1.208 brouard 3055:
1.169 brouard 3056: return prlim; /* should not reach here */
1.126 brouard 3057: }
3058:
1.217 brouard 3059:
3060: /**** Back Prevalence limit (stable or period prevalence) ****************/
3061:
1.218 brouard 3062: /* 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) */
3063: /* 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 3064: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3065: {
1.264 brouard 3066: /* 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 3067: matrix by transitions matrix until convergence is reached with precision ftolpl */
3068: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3069: /* Wx is row vector: population in state 1, population in state 2, population dead */
3070: /* or prevalence in state 1, prevalence in state 2, 0 */
3071: /* newm is the matrix after multiplications, its rows are identical at a factor */
3072: /* Initial matrix pimij */
3073: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3074: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3075: /* 0, 0 , 1} */
3076: /*
3077: * and after some iteration: */
3078: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3079: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3080: /* 0, 0 , 1} */
3081: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3082: /* {0.51571254859325999, 0.4842874514067399, */
3083: /* 0.51326036147820708, 0.48673963852179264} */
3084: /* If we start from prlim again, prlim tends to a constant matrix */
3085:
1.332 brouard 3086: int i, ii,j,k, k1;
1.247 brouard 3087: int first=0;
1.217 brouard 3088: double *min, *max, *meandiff, maxmax,sumnew=0.;
3089: /* double **matprod2(); */ /* test */
3090: double **out, cov[NCOVMAX+1], **bmij();
3091: double **newm;
1.218 brouard 3092: double **dnewm, **doldm, **dsavm; /* for use */
3093: double **oldm, **savm; /* for use */
3094:
1.217 brouard 3095: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3096: int ncvloop=0;
3097:
3098: min=vector(1,nlstate);
3099: max=vector(1,nlstate);
3100: meandiff=vector(1,nlstate);
3101:
1.266 brouard 3102: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3103: oldm=oldms; savm=savms;
3104:
3105: /* Starting with matrix unity */
3106: for (ii=1;ii<=nlstate+ndeath;ii++)
3107: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3108: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3109: }
3110:
3111: cov[1]=1.;
3112:
3113: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3114: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3115: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3116: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3117: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3118: ncvloop++;
1.218 brouard 3119: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3120: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3121: /* Covariates have to be included here again */
3122: cov[2]=agefin;
1.319 brouard 3123: if(nagesqr==1){
1.217 brouard 3124: cov[3]= agefin*agefin;;
1.319 brouard 3125: }
1.332 brouard 3126: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3127: if(Typevar[k1]==1){ /* A product with age */
3128: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3129: }else{
1.332 brouard 3130: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3131: }
1.332 brouard 3132: }/* End of loop on model equation */
3133:
3134: /* Old code */
3135:
3136: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3137: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3138: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3139: /* /\* 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)); *\/ */
3140: /* } */
3141: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3142: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3143: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3144: /* /\* /\\* 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])]); *\\/ *\/ */
3145: /* /\* } *\/ */
3146: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3147: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3148: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3149: /* /\* 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]); *\/ */
3150: /* } */
3151: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3152: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3153: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3154: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3155: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3156: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3157: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3158: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3159: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3160: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3161: /* } */
3162: /* /\* 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]); *\/ */
3163: /* } */
3164: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3165: /* /\* 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]); *\/ */
3166: /* if(Dummy[Tvard[k][1]]==0){ */
3167: /* if(Dummy[Tvard[k][2]]==0){ */
3168: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3169: /* }else{ */
3170: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3171: /* } */
3172: /* }else{ */
3173: /* if(Dummy[Tvard[k][2]]==0){ */
3174: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3175: /* }else{ */
3176: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3177: /* } */
3178: /* } */
3179: /* } */
1.217 brouard 3180:
3181: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3182: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3183: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3184: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3185: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3186: /* ij should be linked to the correct index of cov */
3187: /* age and covariate values ij are in 'cov', but we need to pass
3188: * ij for the observed prevalence at age and status and covariate
3189: * number: prevacurrent[(int)agefin][ii][ij]
3190: */
3191: /* 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 *\/ */
3192: /* 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 *\/ */
3193: 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 3194: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3195: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3196: /* for(i=1; i<=nlstate+ndeath; i++) { */
3197: /* printf("%d newm= ",i); */
3198: /* for(j=1;j<=nlstate+ndeath;j++) { */
3199: /* printf("%f ",newm[i][j]); */
3200: /* } */
3201: /* printf("oldm * "); */
3202: /* for(j=1;j<=nlstate+ndeath;j++) { */
3203: /* printf("%f ",oldm[i][j]); */
3204: /* } */
1.268 brouard 3205: /* printf(" bmmij "); */
1.266 brouard 3206: /* for(j=1;j<=nlstate+ndeath;j++) { */
3207: /* printf("%f ",pmmij[i][j]); */
3208: /* } */
3209: /* printf("\n"); */
3210: /* } */
3211: /* } */
1.217 brouard 3212: savm=oldm;
3213: oldm=newm;
1.266 brouard 3214:
1.217 brouard 3215: for(j=1; j<=nlstate; j++){
3216: max[j]=0.;
3217: min[j]=1.;
3218: }
3219: for(j=1; j<=nlstate; j++){
3220: for(i=1;i<=nlstate;i++){
1.234 brouard 3221: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3222: bprlim[i][j]= newm[i][j];
3223: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3224: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3225: }
3226: }
1.218 brouard 3227:
1.217 brouard 3228: maxmax=0.;
3229: for(i=1; i<=nlstate; i++){
1.318 brouard 3230: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3231: maxmax=FMAX(maxmax,meandiff[i]);
3232: /* 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 3233: } /* i loop */
1.217 brouard 3234: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3235: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3236: if(maxmax < ftolpl){
1.220 brouard 3237: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3238: free_vector(min,1,nlstate);
3239: free_vector(max,1,nlstate);
3240: free_vector(meandiff,1,nlstate);
3241: return bprlim;
3242: }
1.288 brouard 3243: } /* agefin loop */
1.217 brouard 3244: /* After some age loop it doesn't converge */
1.288 brouard 3245: if(!first){
1.247 brouard 3246: first=1;
3247: 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\
3248: 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);
3249: }
3250: 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 3251: 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);
3252: /* 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); */
3253: free_vector(min,1,nlstate);
3254: free_vector(max,1,nlstate);
3255: free_vector(meandiff,1,nlstate);
3256:
3257: return bprlim; /* should not reach here */
3258: }
3259:
1.126 brouard 3260: /*************** transition probabilities ***************/
3261:
3262: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3263: {
1.138 brouard 3264: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3265: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3266: model to the ncovmodel covariates (including constant and age).
3267: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3268: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3269: ncth covariate in the global vector x is given by the formula:
3270: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3271: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3272: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3273: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3274: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3275: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3276: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3277: */
3278: double s1, lnpijopii;
1.126 brouard 3279: /*double t34;*/
1.164 brouard 3280: int i,j, nc, ii, jj;
1.126 brouard 3281:
1.223 brouard 3282: for(i=1; i<= nlstate; i++){
3283: for(j=1; j<i;j++){
3284: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3285: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3286: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3287: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3288: }
3289: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3290: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3291: }
3292: for(j=i+1; j<=nlstate+ndeath;j++){
3293: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3294: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3295: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3296: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3297: }
3298: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3299: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3300: }
3301: }
1.218 brouard 3302:
1.223 brouard 3303: for(i=1; i<= nlstate; i++){
3304: s1=0;
3305: for(j=1; j<i; j++){
1.339 brouard 3306: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3307: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3308: }
3309: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3310: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3311: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3312: }
3313: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3314: ps[i][i]=1./(s1+1.);
3315: /* Computing other pijs */
3316: for(j=1; j<i; j++)
1.325 brouard 3317: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3318: for(j=i+1; j<=nlstate+ndeath; j++)
3319: ps[i][j]= exp(ps[i][j])*ps[i][i];
3320: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3321: } /* end i */
1.218 brouard 3322:
1.223 brouard 3323: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3324: for(jj=1; jj<= nlstate+ndeath; jj++){
3325: ps[ii][jj]=0;
3326: ps[ii][ii]=1;
3327: }
3328: }
1.294 brouard 3329:
3330:
1.223 brouard 3331: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3332: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3333: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3334: /* } */
3335: /* printf("\n "); */
3336: /* } */
3337: /* printf("\n ");printf("%lf ",cov[2]);*/
3338: /*
3339: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3340: goto end;*/
1.266 brouard 3341: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3342: }
3343:
1.218 brouard 3344: /*************** backward transition probabilities ***************/
3345:
3346: /* 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 ) */
3347: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3348: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3349: {
1.302 brouard 3350: /* 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 3351: * 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 3352: */
1.218 brouard 3353: int i, ii, j,k;
1.222 brouard 3354:
3355: double **out, **pmij();
3356: double sumnew=0.;
1.218 brouard 3357: double agefin;
1.292 brouard 3358: 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 3359: double **dnewm, **dsavm, **doldm;
3360: double **bbmij;
3361:
1.218 brouard 3362: doldm=ddoldms; /* global pointers */
1.222 brouard 3363: dnewm=ddnewms;
3364: dsavm=ddsavms;
1.318 brouard 3365:
3366: /* Debug */
3367: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3368: agefin=cov[2];
1.268 brouard 3369: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3370: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3371: the observed prevalence (with this covariate ij) at beginning of transition */
3372: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3373:
3374: /* P_x */
1.325 brouard 3375: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3376: /* outputs pmmij which is a stochastic matrix in row */
3377:
3378: /* Diag(w_x) */
1.292 brouard 3379: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3380: sumnew=0.;
1.269 brouard 3381: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3382: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3383: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3384: sumnew+=prevacurrent[(int)agefin][ii][ij];
3385: }
3386: if(sumnew >0.01){ /* At least some value in the prevalence */
3387: for (ii=1;ii<=nlstate+ndeath;ii++){
3388: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3389: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3390: }
3391: }else{
3392: for (ii=1;ii<=nlstate+ndeath;ii++){
3393: for (j=1;j<=nlstate+ndeath;j++)
3394: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3395: }
3396: /* if(sumnew <0.9){ */
3397: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3398: /* } */
3399: }
3400: k3=0.0; /* We put the last diagonal to 0 */
3401: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3402: doldm[ii][ii]= k3;
3403: }
3404: /* End doldm, At the end doldm is diag[(w_i)] */
3405:
1.292 brouard 3406: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3407: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3408:
1.292 brouard 3409: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3410: /* 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 3411: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3412: sumnew=0.;
1.222 brouard 3413: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3414: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3415: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3416: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3417: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3418: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3419: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3420: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3421: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3422: /* }else */
1.268 brouard 3423: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3424: } /*End ii */
3425: } /* 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 */
3426:
1.292 brouard 3427: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3428: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3429: /* end bmij */
1.266 brouard 3430: return ps; /*pointer is unchanged */
1.218 brouard 3431: }
1.217 brouard 3432: /*************** transition probabilities ***************/
3433:
1.218 brouard 3434: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3435: {
3436: /* According to parameters values stored in x and the covariate's values stored in cov,
3437: computes the probability to be observed in state j being in state i by appying the
3438: model to the ncovmodel covariates (including constant and age).
3439: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3440: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3441: ncth covariate in the global vector x is given by the formula:
3442: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3443: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3444: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3445: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3446: Outputs ps[i][j] the probability to be observed in j being in j according to
3447: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3448: */
3449: double s1, lnpijopii;
3450: /*double t34;*/
3451: int i,j, nc, ii, jj;
3452:
1.234 brouard 3453: for(i=1; i<= nlstate; i++){
3454: for(j=1; j<i;j++){
3455: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3456: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3457: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3458: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3459: }
3460: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3461: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3462: }
3463: for(j=i+1; j<=nlstate+ndeath;j++){
3464: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3465: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3466: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3467: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3468: }
3469: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3470: }
3471: }
3472:
3473: for(i=1; i<= nlstate; i++){
3474: s1=0;
3475: for(j=1; j<i; j++){
3476: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3477: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3478: }
3479: for(j=i+1; j<=nlstate+ndeath; j++){
3480: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3481: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3482: }
3483: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3484: ps[i][i]=1./(s1+1.);
3485: /* Computing other pijs */
3486: for(j=1; j<i; j++)
3487: ps[i][j]= exp(ps[i][j])*ps[i][i];
3488: for(j=i+1; j<=nlstate+ndeath; j++)
3489: ps[i][j]= exp(ps[i][j])*ps[i][i];
3490: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3491: } /* end i */
3492:
3493: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3494: for(jj=1; jj<= nlstate+ndeath; jj++){
3495: ps[ii][jj]=0;
3496: ps[ii][ii]=1;
3497: }
3498: }
1.296 brouard 3499: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3500: for(jj=1; jj<= nlstate+ndeath; jj++){
3501: s1=0.;
3502: for(ii=1; ii<= nlstate+ndeath; ii++){
3503: s1+=ps[ii][jj];
3504: }
3505: for(ii=1; ii<= nlstate; ii++){
3506: ps[ii][jj]=ps[ii][jj]/s1;
3507: }
3508: }
3509: /* Transposition */
3510: for(jj=1; jj<= nlstate+ndeath; jj++){
3511: for(ii=jj; ii<= nlstate+ndeath; ii++){
3512: s1=ps[ii][jj];
3513: ps[ii][jj]=ps[jj][ii];
3514: ps[jj][ii]=s1;
3515: }
3516: }
3517: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3518: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3519: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3520: /* } */
3521: /* printf("\n "); */
3522: /* } */
3523: /* printf("\n ");printf("%lf ",cov[2]);*/
3524: /*
3525: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3526: goto end;*/
3527: return ps;
1.217 brouard 3528: }
3529:
3530:
1.126 brouard 3531: /**************** Product of 2 matrices ******************/
3532:
1.145 brouard 3533: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3534: {
3535: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3536: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3537: /* in, b, out are matrice of pointers which should have been initialized
3538: before: only the contents of out is modified. The function returns
3539: a pointer to pointers identical to out */
1.145 brouard 3540: int i, j, k;
1.126 brouard 3541: for(i=nrl; i<= nrh; i++)
1.145 brouard 3542: for(k=ncolol; k<=ncoloh; k++){
3543: out[i][k]=0.;
3544: for(j=ncl; j<=nch; j++)
3545: out[i][k] +=in[i][j]*b[j][k];
3546: }
1.126 brouard 3547: return out;
3548: }
3549:
3550:
3551: /************* Higher Matrix Product ***************/
3552:
1.235 brouard 3553: 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 3554: {
1.336 brouard 3555: /* Already optimized with precov.
3556: 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 3557: 'nhstepm*hstepm*stepm' months (i.e. until
3558: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3559: nhstepm*hstepm matrices.
3560: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3561: (typically every 2 years instead of every month which is too big
3562: for the memory).
3563: Model is determined by parameters x and covariates have to be
3564: included manually here.
3565:
3566: */
3567:
1.330 brouard 3568: int i, j, d, h, k, k1;
1.131 brouard 3569: double **out, cov[NCOVMAX+1];
1.126 brouard 3570: double **newm;
1.187 brouard 3571: double agexact;
1.214 brouard 3572: double agebegin, ageend;
1.126 brouard 3573:
3574: /* Hstepm could be zero and should return the unit matrix */
3575: for (i=1;i<=nlstate+ndeath;i++)
3576: for (j=1;j<=nlstate+ndeath;j++){
3577: oldm[i][j]=(i==j ? 1.0 : 0.0);
3578: po[i][j][0]=(i==j ? 1.0 : 0.0);
3579: }
3580: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3581: for(h=1; h <=nhstepm; h++){
3582: for(d=1; d <=hstepm; d++){
3583: newm=savm;
3584: /* Covariates have to be included here again */
3585: cov[1]=1.;
1.214 brouard 3586: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3587: cov[2]=agexact;
1.319 brouard 3588: if(nagesqr==1){
1.227 brouard 3589: cov[3]= agexact*agexact;
1.319 brouard 3590: }
1.330 brouard 3591: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3592: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3593: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.332 brouard 3594: if(Typevar[k1]==1){ /* A product with age */
3595: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3596: }else{
3597: cov[2+nagesqr+k1]=precov[nres][k1];
3598: }
3599: }/* End of loop on model equation */
3600: /* Old code */
3601: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3602: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3603: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3604: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3605: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3606: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3607: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3608: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3609: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3610: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3611: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3612: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3613: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3614: /* /\* 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]])); *\/ */
3615: /* 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); */
3616: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3617: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3618: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3619: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3620: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3621: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3622: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3623: /* 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]]); */
3624: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3625: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3626: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3627: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3628: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3629: /* 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]); */
3630: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3631:
3632: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3633: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3634: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3635: /* /\* *\/ */
1.330 brouard 3636: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3637: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3638: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3639: /* /\*cptcovage=2 1 2 *\/ */
3640: /* /\*Tage[k]= 5 8 *\/ */
3641: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3642: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3643: /* 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]]); */
3644: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3645: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3646: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3647: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3648: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3649: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3650: /* /\* 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); *\/ */
3651: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3652: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3653: /* /\* } *\/ */
3654: /* /\* 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]); *\/ */
3655: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3656: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3657: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3658: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3659: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3660: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3661: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3662: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3663: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3664:
1.332 brouard 3665: /* /\* 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])]); *\/ */
3666: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3667: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3668: /* 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]]); */
3669: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3670:
3671: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3672: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3673: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3674: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3675: /* /\* 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]])]; *\/ */
3676: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3677: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3678: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3679: /* /\* } *\/ */
3680: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3681: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3682: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3683: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3684: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3685: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3686: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3687: /* /\* } *\/ */
3688: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3689: /* }/\*end of products *\/ */
3690: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3691: /* for (k=1; k<=cptcovn;k++) */
3692: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3693: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3694: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3695: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3696: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3697:
3698:
1.126 brouard 3699: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3700: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3701: /* right multiplication of oldm by the current matrix */
1.126 brouard 3702: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3703: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3704: /* if((int)age == 70){ */
3705: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3706: /* for(i=1; i<=nlstate+ndeath; i++) { */
3707: /* printf("%d pmmij ",i); */
3708: /* for(j=1;j<=nlstate+ndeath;j++) { */
3709: /* printf("%f ",pmmij[i][j]); */
3710: /* } */
3711: /* printf(" oldm "); */
3712: /* for(j=1;j<=nlstate+ndeath;j++) { */
3713: /* printf("%f ",oldm[i][j]); */
3714: /* } */
3715: /* printf("\n"); */
3716: /* } */
3717: /* } */
1.126 brouard 3718: savm=oldm;
3719: oldm=newm;
3720: }
3721: for(i=1; i<=nlstate+ndeath; i++)
3722: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3723: po[i][j][h]=newm[i][j];
3724: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3725: }
1.128 brouard 3726: /*printf("h=%d ",h);*/
1.126 brouard 3727: } /* end h */
1.267 brouard 3728: /* printf("\n H=%d \n",h); */
1.126 brouard 3729: return po;
3730: }
3731:
1.217 brouard 3732: /************* Higher Back Matrix Product ***************/
1.218 brouard 3733: /* 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 3734: 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 3735: {
1.332 brouard 3736: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3737: computes the transition matrix starting at age 'age' over
1.217 brouard 3738: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3739: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3740: nhstepm*hstepm matrices.
3741: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3742: (typically every 2 years instead of every month which is too big
1.217 brouard 3743: for the memory).
1.218 brouard 3744: Model is determined by parameters x and covariates have to be
1.266 brouard 3745: included manually here. Then we use a call to bmij(x and cov)
3746: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3747: */
1.217 brouard 3748:
1.332 brouard 3749: int i, j, d, h, k, k1;
1.266 brouard 3750: double **out, cov[NCOVMAX+1], **bmij();
3751: double **newm, ***newmm;
1.217 brouard 3752: double agexact;
3753: double agebegin, ageend;
1.222 brouard 3754: double **oldm, **savm;
1.217 brouard 3755:
1.266 brouard 3756: newmm=po; /* To be saved */
3757: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3758: /* Hstepm could be zero and should return the unit matrix */
3759: for (i=1;i<=nlstate+ndeath;i++)
3760: for (j=1;j<=nlstate+ndeath;j++){
3761: oldm[i][j]=(i==j ? 1.0 : 0.0);
3762: po[i][j][0]=(i==j ? 1.0 : 0.0);
3763: }
3764: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3765: for(h=1; h <=nhstepm; h++){
3766: for(d=1; d <=hstepm; d++){
3767: newm=savm;
3768: /* Covariates have to be included here again */
3769: cov[1]=1.;
1.271 brouard 3770: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3771: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3772: /* Debug */
3773: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3774: cov[2]=agexact;
1.332 brouard 3775: if(nagesqr==1){
1.222 brouard 3776: cov[3]= agexact*agexact;
1.332 brouard 3777: }
3778: /** New code */
3779: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3780: if(Typevar[k1]==1){ /* A product with age */
3781: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3782: }else{
1.332 brouard 3783: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3784: }
1.332 brouard 3785: }/* End of loop on model equation */
3786: /** End of new code */
3787: /** This was old code */
3788: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3789: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3790: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3791: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3792: /* /\* 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)); *\/ */
3793: /* } */
3794: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3795: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3796: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3797: /* /\* 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]); *\/ */
3798: /* } */
3799: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3800: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3801: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3802: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3803: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3804: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3805: /* } */
3806: /* /\* 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]); *\/ */
3807: /* } */
3808: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3809: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3810: /* if(Dummy[Tvard[k][1]]==0){ */
3811: /* if(Dummy[Tvard[k][2]]==0){ */
3812: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3813: /* }else{ */
3814: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3815: /* } */
3816: /* }else{ */
3817: /* if(Dummy[Tvard[k][2]]==0){ */
3818: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3819: /* }else{ */
3820: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3821: /* } */
3822: /* } */
3823: /* } */
3824: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3825: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3826: /** End of old code */
3827:
1.218 brouard 3828: /* Careful transposed matrix */
1.266 brouard 3829: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3830: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3831: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3832: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3833: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3834: /* if((int)age == 70){ */
3835: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3836: /* for(i=1; i<=nlstate+ndeath; i++) { */
3837: /* printf("%d pmmij ",i); */
3838: /* for(j=1;j<=nlstate+ndeath;j++) { */
3839: /* printf("%f ",pmmij[i][j]); */
3840: /* } */
3841: /* printf(" oldm "); */
3842: /* for(j=1;j<=nlstate+ndeath;j++) { */
3843: /* printf("%f ",oldm[i][j]); */
3844: /* } */
3845: /* printf("\n"); */
3846: /* } */
3847: /* } */
3848: savm=oldm;
3849: oldm=newm;
3850: }
3851: for(i=1; i<=nlstate+ndeath; i++)
3852: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3853: po[i][j][h]=newm[i][j];
1.268 brouard 3854: /* if(h==nhstepm) */
3855: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3856: }
1.268 brouard 3857: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3858: } /* end h */
1.268 brouard 3859: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3860: return po;
3861: }
3862:
3863:
1.162 brouard 3864: #ifdef NLOPT
3865: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3866: double fret;
3867: double *xt;
3868: int j;
3869: myfunc_data *d2 = (myfunc_data *) pd;
3870: /* xt = (p1-1); */
3871: xt=vector(1,n);
3872: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3873:
3874: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3875: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3876: printf("Function = %.12lf ",fret);
3877: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3878: printf("\n");
3879: free_vector(xt,1,n);
3880: return fret;
3881: }
3882: #endif
1.126 brouard 3883:
3884: /*************** log-likelihood *************/
3885: double func( double *x)
3886: {
1.336 brouard 3887: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3888: int ioffset=0;
1.339 brouard 3889: int ipos=0,iposold=0,ncovv=0;
3890:
1.340 brouard 3891: double cotvarv, cotvarvold;
1.226 brouard 3892: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3893: double **out;
3894: double lli; /* Individual log likelihood */
3895: int s1, s2;
1.228 brouard 3896: 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 3897:
1.226 brouard 3898: double bbh, survp;
3899: double agexact;
1.336 brouard 3900: double agebegin, ageend;
1.226 brouard 3901: /*extern weight */
3902: /* We are differentiating ll according to initial status */
3903: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3904: /*for(i=1;i<imx;i++)
3905: printf(" %d\n",s[4][i]);
3906: */
1.162 brouard 3907:
1.226 brouard 3908: ++countcallfunc;
1.162 brouard 3909:
1.226 brouard 3910: cov[1]=1.;
1.126 brouard 3911:
1.226 brouard 3912: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3913: ioffset=0;
1.226 brouard 3914: if(mle==1){
3915: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3916: /* Computes the values of the ncovmodel covariates of the model
3917: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3918: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3919: to be observed in j being in i according to the model.
3920: */
1.243 brouard 3921: ioffset=2+nagesqr ;
1.233 brouard 3922: /* Fixed */
1.336 brouard 3923: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummu or quant or prod */
1.319 brouard 3924: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3925: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3926: /* 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 3927: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 3928: 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 3929: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3930: }
1.226 brouard 3931: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3932: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3933: has been calculated etc */
3934: /* For an individual i, wav[i] gives the number of effective waves */
3935: /* We compute the contribution to Likelihood of each effective transition
3936: mw[mi][i] is real wave of the mi th effectve wave */
3937: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3938: s2=s[mw[mi+1][i]][i];
1.341 ! brouard 3939: 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 3940: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3941: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3942: */
1.336 brouard 3943: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
3944: /* Wave varying (but not age varying) */
1.339 brouard 3945: /* 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*\/ */
3946: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
3947: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
3948: /* } */
1.340 brouard 3949: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
3950: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
3951: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
3952: if(TvarFind[itv]==0){ /* Not a fixed covariate */
1.341 ! brouard 3953: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 3954: }else{ /* fixed covariate */
3955: cotvarv=covar[Tvar[TvarFind[itv]]][i];
3956: }
1.339 brouard 3957: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 3958: cotvarvold=cotvarv;
3959: }else{ /* A second product */
3960: cotvarv=cotvarv*cotvarvold;
1.339 brouard 3961: }
3962: iposold=ipos;
1.340 brouard 3963: cov[ioffset+ipos]=cotvarv;
1.234 brouard 3964: }
1.339 brouard 3965: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
3966: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3967: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3968: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3969: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3970: /* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][TmodelInvind[itv]][i]=%f\n", i, mi, itv, TmodelInvind[itv],cotvar[mw[mi][i]][TmodelInvind[itv]][i]); */
3971: /* } */
3972: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
3973: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3974: /* /\* 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]); *\/ */
3975: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
3976: /* } */
3977: /* for products of time varying to be done */
1.234 brouard 3978: for (ii=1;ii<=nlstate+ndeath;ii++)
3979: for (j=1;j<=nlstate+ndeath;j++){
3980: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3981: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3982: }
1.336 brouard 3983:
3984: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3985: 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 3986: for(d=0; d<dh[mi][i]; d++){
3987: newm=savm;
3988: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3989: cov[2]=agexact;
3990: if(nagesqr==1)
3991: cov[3]= agexact*agexact; /* Should be changed here */
3992: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3993: if(!FixedV[Tvar[Tage[kk]]])
3994: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3995: else
1.341 ! brouard 3996: 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) */
1.234 brouard 3997: }
3998: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3999: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4000: savm=oldm;
4001: oldm=newm;
4002: } /* end mult */
4003:
4004: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4005: /* But now since version 0.9 we anticipate for bias at large stepm.
4006: * If stepm is larger than one month (smallest stepm) and if the exact delay
4007: * (in months) between two waves is not a multiple of stepm, we rounded to
4008: * the nearest (and in case of equal distance, to the lowest) interval but now
4009: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4010: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4011: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4012: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4013: * -stepm/2 to stepm/2 .
4014: * For stepm=1 the results are the same as for previous versions of Imach.
4015: * For stepm > 1 the results are less biased than in previous versions.
4016: */
1.234 brouard 4017: s1=s[mw[mi][i]][i];
4018: s2=s[mw[mi+1][i]][i];
4019: bbh=(double)bh[mi][i]/(double)stepm;
4020: /* bias bh is positive if real duration
4021: * is higher than the multiple of stepm and negative otherwise.
4022: */
4023: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4024: if( s2 > nlstate){
4025: /* i.e. if s2 is a death state and if the date of death is known
4026: then the contribution to the likelihood is the probability to
4027: die between last step unit time and current step unit time,
4028: which is also equal to probability to die before dh
4029: minus probability to die before dh-stepm .
4030: In version up to 0.92 likelihood was computed
4031: as if date of death was unknown. Death was treated as any other
4032: health state: the date of the interview describes the actual state
4033: and not the date of a change in health state. The former idea was
4034: to consider that at each interview the state was recorded
4035: (healthy, disable or death) and IMaCh was corrected; but when we
4036: introduced the exact date of death then we should have modified
4037: the contribution of an exact death to the likelihood. This new
4038: contribution is smaller and very dependent of the step unit
4039: stepm. It is no more the probability to die between last interview
4040: and month of death but the probability to survive from last
4041: interview up to one month before death multiplied by the
4042: probability to die within a month. Thanks to Chris
4043: Jackson for correcting this bug. Former versions increased
4044: mortality artificially. The bad side is that we add another loop
4045: which slows down the processing. The difference can be up to 10%
4046: lower mortality.
4047: */
4048: /* If, at the beginning of the maximization mostly, the
4049: cumulative probability or probability to be dead is
4050: constant (ie = 1) over time d, the difference is equal to
4051: 0. out[s1][3] = savm[s1][3]: probability, being at state
4052: s1 at precedent wave, to be dead a month before current
4053: wave is equal to probability, being at state s1 at
4054: precedent wave, to be dead at mont of the current
4055: wave. Then the observed probability (that this person died)
4056: is null according to current estimated parameter. In fact,
4057: it should be very low but not zero otherwise the log go to
4058: infinity.
4059: */
1.183 brouard 4060: /* #ifdef INFINITYORIGINAL */
4061: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4062: /* #else */
4063: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4064: /* lli=log(mytinydouble); */
4065: /* else */
4066: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4067: /* #endif */
1.226 brouard 4068: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4069:
1.226 brouard 4070: } else if ( s2==-1 ) { /* alive */
4071: for (j=1,survp=0. ; j<=nlstate; j++)
4072: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4073: /*survp += out[s1][j]; */
4074: lli= log(survp);
4075: }
1.336 brouard 4076: /* else if (s2==-4) { */
4077: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4078: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4079: /* lli= log(survp); */
4080: /* } */
4081: /* else if (s2==-5) { */
4082: /* for (j=1,survp=0. ; j<=2; j++) */
4083: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4084: /* lli= log(survp); */
4085: /* } */
1.226 brouard 4086: else{
4087: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4088: /* 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 */
4089: }
4090: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4091: /*if(lli ==000.0)*/
1.340 brouard 4092: /* 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 4093: ipmx +=1;
4094: sw += weight[i];
4095: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4096: /* if (lli < log(mytinydouble)){ */
4097: /* 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); */
4098: /* 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]); */
4099: /* } */
4100: } /* end of wave */
4101: } /* end of individual */
4102: } else if(mle==2){
4103: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4104: ioffset=2+nagesqr ;
4105: for (k=1; k<=ncovf;k++)
4106: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4107: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4108: for(k=1; k <= ncovv ; k++){
1.341 ! brouard 4109: 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 4110: }
1.226 brouard 4111: for (ii=1;ii<=nlstate+ndeath;ii++)
4112: for (j=1;j<=nlstate+ndeath;j++){
4113: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4114: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4115: }
4116: for(d=0; d<=dh[mi][i]; d++){
4117: newm=savm;
4118: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4119: cov[2]=agexact;
4120: if(nagesqr==1)
4121: cov[3]= agexact*agexact;
4122: for (kk=1; kk<=cptcovage;kk++) {
4123: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4124: }
4125: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4126: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4127: savm=oldm;
4128: oldm=newm;
4129: } /* end mult */
4130:
4131: s1=s[mw[mi][i]][i];
4132: s2=s[mw[mi+1][i]][i];
4133: bbh=(double)bh[mi][i]/(double)stepm;
4134: 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 */
4135: ipmx +=1;
4136: sw += weight[i];
4137: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4138: } /* end of wave */
4139: } /* end of individual */
4140: } else if(mle==3){ /* exponential inter-extrapolation */
4141: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4142: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4143: for(mi=1; mi<= wav[i]-1; mi++){
4144: for (ii=1;ii<=nlstate+ndeath;ii++)
4145: for (j=1;j<=nlstate+ndeath;j++){
4146: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4147: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4148: }
4149: for(d=0; d<dh[mi][i]; d++){
4150: newm=savm;
4151: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4152: cov[2]=agexact;
4153: if(nagesqr==1)
4154: cov[3]= agexact*agexact;
4155: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4156: if(!FixedV[Tvar[Tage[kk]]])
4157: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4158: else
1.341 ! brouard 4159: 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 4160: }
4161: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4162: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4163: savm=oldm;
4164: oldm=newm;
4165: } /* end mult */
4166:
4167: s1=s[mw[mi][i]][i];
4168: s2=s[mw[mi+1][i]][i];
4169: bbh=(double)bh[mi][i]/(double)stepm;
4170: 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 */
4171: ipmx +=1;
4172: sw += weight[i];
4173: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4174: } /* end of wave */
4175: } /* end of individual */
4176: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4177: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4178: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4179: for(mi=1; mi<= wav[i]-1; mi++){
4180: for (ii=1;ii<=nlstate+ndeath;ii++)
4181: for (j=1;j<=nlstate+ndeath;j++){
4182: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4183: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4184: }
4185: for(d=0; d<dh[mi][i]; d++){
4186: newm=savm;
4187: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4188: cov[2]=agexact;
4189: if(nagesqr==1)
4190: cov[3]= agexact*agexact;
4191: for (kk=1; kk<=cptcovage;kk++) {
4192: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4193: }
1.126 brouard 4194:
1.226 brouard 4195: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4196: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4197: savm=oldm;
4198: oldm=newm;
4199: } /* end mult */
4200:
4201: s1=s[mw[mi][i]][i];
4202: s2=s[mw[mi+1][i]][i];
4203: if( s2 > nlstate){
4204: lli=log(out[s1][s2] - savm[s1][s2]);
4205: } else if ( s2==-1 ) { /* alive */
4206: for (j=1,survp=0. ; j<=nlstate; j++)
4207: survp += out[s1][j];
4208: lli= log(survp);
4209: }else{
4210: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4211: }
4212: ipmx +=1;
4213: sw += weight[i];
4214: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.340 brouard 4215: /* 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]); */
1.226 brouard 4216: } /* end of wave */
4217: } /* end of individual */
4218: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4219: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4220: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4221: for(mi=1; mi<= wav[i]-1; mi++){
4222: for (ii=1;ii<=nlstate+ndeath;ii++)
4223: for (j=1;j<=nlstate+ndeath;j++){
4224: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4225: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4226: }
4227: for(d=0; d<dh[mi][i]; d++){
4228: newm=savm;
4229: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4230: cov[2]=agexact;
4231: if(nagesqr==1)
4232: cov[3]= agexact*agexact;
4233: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4234: if(!FixedV[Tvar[Tage[kk]]])
4235: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4236: else
1.341 ! brouard 4237: 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 4238: }
1.126 brouard 4239:
1.226 brouard 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: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4249: ipmx +=1;
4250: sw += weight[i];
4251: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4252: /*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]);*/
4253: } /* end of wave */
4254: } /* end of individual */
4255: } /* End of if */
4256: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4257: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4258: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4259: return -l;
1.126 brouard 4260: }
4261:
4262: /*************** log-likelihood *************/
4263: double funcone( double *x)
4264: {
1.228 brouard 4265: /* Same as func but slower because of a lot of printf and if */
1.335 brouard 4266: int i, ii, j, k, mi, d, kk, kf=0;
1.228 brouard 4267: int ioffset=0;
1.339 brouard 4268: int ipos=0,iposold=0,ncovv=0;
4269:
1.340 brouard 4270: double cotvarv, cotvarvold;
1.131 brouard 4271: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4272: double **out;
4273: double lli; /* Individual log likelihood */
4274: double llt;
4275: int s1, s2;
1.228 brouard 4276: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4277:
1.126 brouard 4278: double bbh, survp;
1.187 brouard 4279: double agexact;
1.214 brouard 4280: double agebegin, ageend;
1.126 brouard 4281: /*extern weight */
4282: /* We are differentiating ll according to initial status */
4283: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4284: /*for(i=1;i<imx;i++)
4285: printf(" %d\n",s[4][i]);
4286: */
4287: cov[1]=1.;
4288:
4289: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4290: ioffset=0;
4291: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4292: /* Computes the values of the ncovmodel covariates of the model
4293: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4294: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4295: to be observed in j being in i according to the model.
4296: */
1.243 brouard 4297: /* ioffset=2+nagesqr+cptcovage; */
4298: ioffset=2+nagesqr;
1.232 brouard 4299: /* Fixed */
1.224 brouard 4300: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4301: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.335 brouard 4302: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 brouard 4303: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4304: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4305: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4306: 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 4307: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4308: /* cov[2+6]=covar[Tvar[6]][i]; */
4309: /* cov[2+6]=covar[2][i]; V2 */
4310: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4311: /* cov[2+7]=covar[Tvar[7]][i]; */
4312: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4313: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4314: /* cov[2+9]=covar[Tvar[9]][i]; */
4315: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4316: }
1.336 brouard 4317: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4318: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4319: has been calculated etc */
4320: /* For an individual i, wav[i] gives the number of effective waves */
4321: /* We compute the contribution to Likelihood of each effective transition
4322: mw[mi][i] is real wave of the mi th effectve wave */
4323: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4324: s2=s[mw[mi+1][i]][i];
1.341 ! brouard 4325: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4326: */
4327: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4328: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4329: /* 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?)*\/ */
4330: /* } */
1.231 brouard 4331: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4332: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4333: /* } */
1.225 brouard 4334:
1.233 brouard 4335:
4336: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4337: /* 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 */
4338: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4339: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4340: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4341: /* } */
4342:
4343: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4344: /* model V1+V3+age*V1+age*V3+V1*V3 */
4345: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4346: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4347: /* We need the position of the time varying or product in the model */
4348: /* 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 */
4349: /* TvarVV gives the variable name */
1.340 brouard 4350: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4351: * k= 1 2 3 4 5 6 7 8 9
4352: * varying 1 2 3 4 5
4353: * ncovv 1 2 3 4 5 6 7 8
4354: * TvarVV V3 5 1 3 3 5 1 5
4355: * TvarVVind 2 3 7 7 8 8 9 9
4356: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4357: * cotvar starts at ntv=2 (because of V3 V4)
4358: */
4359: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4360: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4361: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4362: if(TvarFind[itv]==0){ /* Not a fixed covariate */
1.341 ! brouard 4363: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.340 brouard 4364: }else{ /* fixed covariate */
4365: cotvarv=covar[Tvar[TvarFind[itv]]][i];
4366: }
1.339 brouard 4367: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4368: cotvarvold=cotvarv;
4369: }else{ /* A second product */
4370: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4371: }
4372: iposold=ipos;
1.340 brouard 4373: cov[ioffset+ipos]=cotvarv;
1.339 brouard 4374: /* For products */
4375: }
4376: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4377: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4378: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4379: /* /\* 1 2 3 4 5 *\/ */
4380: /* /\*itv 1 *\/ */
4381: /* /\* TvarVInd[1]= 2 *\/ */
4382: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4383: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4384: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4385: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4386: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4387: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4388: /* /\* 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]); *\/ */
4389: /* } */
1.232 brouard 4390: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4391: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4392: /* /\* 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]); *\/ */
4393: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4394: /* } */
1.126 brouard 4395: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4396: for (j=1;j<=nlstate+ndeath;j++){
4397: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4398: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4399: }
1.214 brouard 4400:
4401: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4402: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4403: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4404: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4405: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4406: and mw[mi+1][i]. dh depends on stepm.*/
4407: newm=savm;
1.247 brouard 4408: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4409: cov[2]=agexact;
4410: if(nagesqr==1)
4411: cov[3]= agexact*agexact;
4412: for (kk=1; kk<=cptcovage;kk++) {
4413: if(!FixedV[Tvar[Tage[kk]]])
4414: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4415: else
1.341 ! brouard 4416: 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) */
1.242 brouard 4417: }
4418: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4419: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4420: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4421: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4422: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4423: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4424: savm=oldm;
4425: oldm=newm;
1.126 brouard 4426: } /* end mult */
1.336 brouard 4427: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4428: /* But now since version 0.9 we anticipate for bias at large stepm.
4429: * If stepm is larger than one month (smallest stepm) and if the exact delay
4430: * (in months) between two waves is not a multiple of stepm, we rounded to
4431: * the nearest (and in case of equal distance, to the lowest) interval but now
4432: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4433: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4434: * probability in order to take into account the bias as a fraction of the way
4435: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4436: * -stepm/2 to stepm/2 .
4437: * For stepm=1 the results are the same as for previous versions of Imach.
4438: * For stepm > 1 the results are less biased than in previous versions.
4439: */
1.126 brouard 4440: s1=s[mw[mi][i]][i];
4441: s2=s[mw[mi+1][i]][i];
1.217 brouard 4442: /* if(s2==-1){ */
1.268 brouard 4443: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4444: /* /\* exit(1); *\/ */
4445: /* } */
1.126 brouard 4446: bbh=(double)bh[mi][i]/(double)stepm;
4447: /* bias is positive if real duration
4448: * is higher than the multiple of stepm and negative otherwise.
4449: */
4450: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4451: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4452: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4453: for (j=1,survp=0. ; j<=nlstate; j++)
4454: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4455: lli= log(survp);
1.126 brouard 4456: }else if (mle==1){
1.242 brouard 4457: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4458: } else if(mle==2){
1.242 brouard 4459: 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 4460: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4461: 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 4462: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4463: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4464: } else{ /* mle=0 back to 1 */
1.242 brouard 4465: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4466: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4467: } /* End of if */
4468: ipmx +=1;
4469: sw += weight[i];
4470: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.340 brouard 4471: printf("Funcone num[i]=%ld i=%6d V= ", num[i], i);
4472: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4473: printf("%g",covar[Tvar[TvarFind[kf]]][i]);
4474: }
4475: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4476: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4477: if(ipos!=iposold){ /* Not a product or first of a product */
4478: printf(" %g",cov[ioffset+ipos]);
4479: }else{
4480: printf("*");
4481: }
4482: iposold=ipos;
4483: }
4484: for (kk=1; kk<=cptcovage;kk++) {
4485: if(!FixedV[Tvar[Tage[kk]]])
4486: printf(" %g*age",covar[Tvar[Tage[kk]]][i]);
4487: else
1.341 ! brouard 4488: printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.340 brouard 4489: }
4490: printf(" s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",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 4491: if(globpr){
1.246 brouard 4492: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4493: %11.6f %11.6f %11.6f ", \
1.242 brouard 4494: 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 4495: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.335 brouard 4496: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4497: /* %11.6f %11.6f %11.6f ", \ */
4498: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4499: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4500: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4501: llt +=ll[k]*gipmx/gsw;
4502: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4503: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4504: }
4505: fprintf(ficresilk," %10.6f\n", -llt);
1.335 brouard 4506: /* printf(" %10.6f\n", -llt); */
1.126 brouard 4507: }
1.335 brouard 4508: } /* end of wave */
4509: } /* end of individual */
4510: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4511: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4512: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4513: if(globpr==0){ /* First time we count the contributions and weights */
4514: gipmx=ipmx;
4515: gsw=sw;
4516: }
1.232 brouard 4517: return -l;
1.126 brouard 4518: }
4519:
4520:
4521: /*************** function likelione ***********/
1.292 brouard 4522: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4523: {
4524: /* This routine should help understanding what is done with
4525: the selection of individuals/waves and
4526: to check the exact contribution to the likelihood.
4527: Plotting could be done.
4528: */
4529: int k;
4530:
4531: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4532: strcpy(fileresilk,"ILK_");
1.202 brouard 4533: strcat(fileresilk,fileresu);
1.126 brouard 4534: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4535: printf("Problem with resultfile: %s\n", fileresilk);
4536: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4537: }
1.214 brouard 4538: 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");
4539: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4540: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4541: for(k=1; k<=nlstate; k++)
4542: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4543: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4544: }
4545:
1.292 brouard 4546: *fretone=(*func)(p);
1.126 brouard 4547: if(*globpri !=0){
4548: fclose(ficresilk);
1.205 brouard 4549: if (mle ==0)
4550: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4551: else if(mle >=1)
4552: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4553: 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 4554: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4555:
4556: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4557: 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> \
1.208 brouard 4558: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4559: }
1.207 brouard 4560: 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> \
1.204 brouard 4561: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4562: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4563: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4564: fflush(fichtm);
1.205 brouard 4565: }
1.126 brouard 4566: return;
4567: }
4568:
4569:
4570: /*********** Maximum Likelihood Estimation ***************/
4571:
4572: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4573: {
1.319 brouard 4574: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4575: double **xi;
4576: double fret;
4577: double fretone; /* Only one call to likelihood */
4578: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4579:
4580: #ifdef NLOPT
4581: int creturn;
4582: nlopt_opt opt;
4583: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4584: double *lb;
4585: double minf; /* the minimum objective value, upon return */
4586: double * p1; /* Shifted parameters from 0 instead of 1 */
4587: myfunc_data dinst, *d = &dinst;
4588: #endif
4589:
4590:
1.126 brouard 4591: xi=matrix(1,npar,1,npar);
4592: for (i=1;i<=npar;i++)
4593: for (j=1;j<=npar;j++)
4594: xi[i][j]=(i==j ? 1.0 : 0.0);
4595: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4596: strcpy(filerespow,"POW_");
1.126 brouard 4597: strcat(filerespow,fileres);
4598: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4599: printf("Problem with resultfile: %s\n", filerespow);
4600: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4601: }
4602: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4603: for (i=1;i<=nlstate;i++)
4604: for(j=1;j<=nlstate+ndeath;j++)
4605: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4606: fprintf(ficrespow,"\n");
1.162 brouard 4607: #ifdef POWELL
1.319 brouard 4608: #ifdef LINMINORIGINAL
4609: #else /* LINMINORIGINAL */
4610:
4611: flatdir=ivector(1,npar);
4612: for (j=1;j<=npar;j++) flatdir[j]=0;
4613: #endif /*LINMINORIGINAL */
4614:
4615: #ifdef FLATSUP
4616: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4617: /* reorganizing p by suppressing flat directions */
4618: for(i=1, jk=1; i <=nlstate; i++){
4619: for(k=1; k <=(nlstate+ndeath); k++){
4620: if (k != i) {
4621: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4622: if(flatdir[jk]==1){
4623: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4624: }
4625: for(j=1; j <=ncovmodel; j++){
4626: printf("%12.7f ",p[jk]);
4627: jk++;
4628: }
4629: printf("\n");
4630: }
4631: }
4632: }
4633: /* skipping */
4634: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4635: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4636: for(k=1; k <=(nlstate+ndeath); k++){
4637: if (k != i) {
4638: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4639: if(flatdir[jk]==1){
4640: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4641: for(j=1; j <=ncovmodel; jk++,j++){
4642: printf(" p[%d]=%12.7f",jk, p[jk]);
4643: /*q[jjk]=p[jk];*/
4644: }
4645: }else{
4646: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4647: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4648: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4649: /*q[jjk]=p[jk];*/
4650: }
4651: }
4652: printf("\n");
4653: }
4654: fflush(stdout);
4655: }
4656: }
4657: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4658: #else /* FLATSUP */
1.126 brouard 4659: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4660: #endif /* FLATSUP */
4661:
4662: #ifdef LINMINORIGINAL
4663: #else
4664: free_ivector(flatdir,1,npar);
4665: #endif /* LINMINORIGINAL*/
4666: #endif /* POWELL */
1.126 brouard 4667:
1.162 brouard 4668: #ifdef NLOPT
4669: #ifdef NEWUOA
4670: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4671: #else
4672: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4673: #endif
4674: lb=vector(0,npar-1);
4675: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4676: nlopt_set_lower_bounds(opt, lb);
4677: nlopt_set_initial_step1(opt, 0.1);
4678:
4679: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4680: d->function = func;
4681: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4682: nlopt_set_min_objective(opt, myfunc, d);
4683: nlopt_set_xtol_rel(opt, ftol);
4684: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4685: printf("nlopt failed! %d\n",creturn);
4686: }
4687: else {
4688: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4689: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4690: iter=1; /* not equal */
4691: }
4692: nlopt_destroy(opt);
4693: #endif
1.319 brouard 4694: #ifdef FLATSUP
4695: /* npared = npar -flatd/ncovmodel; */
4696: /* xired= matrix(1,npared,1,npared); */
4697: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4698: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4699: /* free_matrix(xire,1,npared,1,npared); */
4700: #else /* FLATSUP */
4701: #endif /* FLATSUP */
1.126 brouard 4702: free_matrix(xi,1,npar,1,npar);
4703: fclose(ficrespow);
1.203 brouard 4704: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4705: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4706: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4707:
4708: }
4709:
4710: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4711: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4712: {
4713: double **a,**y,*x,pd;
1.203 brouard 4714: /* double **hess; */
1.164 brouard 4715: int i, j;
1.126 brouard 4716: int *indx;
4717:
4718: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4719: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4720: void lubksb(double **a, int npar, int *indx, double b[]) ;
4721: void ludcmp(double **a, int npar, int *indx, double *d) ;
4722: double gompertz(double p[]);
1.203 brouard 4723: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4724:
4725: printf("\nCalculation of the hessian matrix. Wait...\n");
4726: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4727: for (i=1;i<=npar;i++){
1.203 brouard 4728: printf("%d-",i);fflush(stdout);
4729: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4730:
4731: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4732:
4733: /* printf(" %f ",p[i]);
4734: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4735: }
4736:
4737: for (i=1;i<=npar;i++) {
4738: for (j=1;j<=npar;j++) {
4739: if (j>i) {
1.203 brouard 4740: printf(".%d-%d",i,j);fflush(stdout);
4741: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4742: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4743:
4744: hess[j][i]=hess[i][j];
4745: /*printf(" %lf ",hess[i][j]);*/
4746: }
4747: }
4748: }
4749: printf("\n");
4750: fprintf(ficlog,"\n");
4751:
4752: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4753: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4754:
4755: a=matrix(1,npar,1,npar);
4756: y=matrix(1,npar,1,npar);
4757: x=vector(1,npar);
4758: indx=ivector(1,npar);
4759: for (i=1;i<=npar;i++)
4760: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4761: ludcmp(a,npar,indx,&pd);
4762:
4763: for (j=1;j<=npar;j++) {
4764: for (i=1;i<=npar;i++) x[i]=0;
4765: x[j]=1;
4766: lubksb(a,npar,indx,x);
4767: for (i=1;i<=npar;i++){
4768: matcov[i][j]=x[i];
4769: }
4770: }
4771:
4772: printf("\n#Hessian matrix#\n");
4773: fprintf(ficlog,"\n#Hessian matrix#\n");
4774: for (i=1;i<=npar;i++) {
4775: for (j=1;j<=npar;j++) {
1.203 brouard 4776: printf("%.6e ",hess[i][j]);
4777: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4778: }
4779: printf("\n");
4780: fprintf(ficlog,"\n");
4781: }
4782:
1.203 brouard 4783: /* printf("\n#Covariance matrix#\n"); */
4784: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4785: /* for (i=1;i<=npar;i++) { */
4786: /* for (j=1;j<=npar;j++) { */
4787: /* printf("%.6e ",matcov[i][j]); */
4788: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4789: /* } */
4790: /* printf("\n"); */
4791: /* fprintf(ficlog,"\n"); */
4792: /* } */
4793:
1.126 brouard 4794: /* Recompute Inverse */
1.203 brouard 4795: /* for (i=1;i<=npar;i++) */
4796: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4797: /* ludcmp(a,npar,indx,&pd); */
4798:
4799: /* printf("\n#Hessian matrix recomputed#\n"); */
4800:
4801: /* for (j=1;j<=npar;j++) { */
4802: /* for (i=1;i<=npar;i++) x[i]=0; */
4803: /* x[j]=1; */
4804: /* lubksb(a,npar,indx,x); */
4805: /* for (i=1;i<=npar;i++){ */
4806: /* y[i][j]=x[i]; */
4807: /* printf("%.3e ",y[i][j]); */
4808: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4809: /* } */
4810: /* printf("\n"); */
4811: /* fprintf(ficlog,"\n"); */
4812: /* } */
4813:
4814: /* Verifying the inverse matrix */
4815: #ifdef DEBUGHESS
4816: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4817:
1.203 brouard 4818: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4819: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4820:
4821: for (j=1;j<=npar;j++) {
4822: for (i=1;i<=npar;i++){
1.203 brouard 4823: printf("%.2f ",y[i][j]);
4824: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4825: }
4826: printf("\n");
4827: fprintf(ficlog,"\n");
4828: }
1.203 brouard 4829: #endif
1.126 brouard 4830:
4831: free_matrix(a,1,npar,1,npar);
4832: free_matrix(y,1,npar,1,npar);
4833: free_vector(x,1,npar);
4834: free_ivector(indx,1,npar);
1.203 brouard 4835: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4836:
4837:
4838: }
4839:
4840: /*************** hessian matrix ****************/
4841: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4842: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4843: int i;
4844: int l=1, lmax=20;
1.203 brouard 4845: double k1,k2, res, fx;
1.132 brouard 4846: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4847: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4848: int k=0,kmax=10;
4849: double l1;
4850:
4851: fx=func(x);
4852: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4853: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4854: l1=pow(10,l);
4855: delts=delt;
4856: for(k=1 ; k <kmax; k=k+1){
4857: delt = delta*(l1*k);
4858: p2[theta]=x[theta] +delt;
1.145 brouard 4859: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4860: p2[theta]=x[theta]-delt;
4861: k2=func(p2)-fx;
4862: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4863: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4864:
1.203 brouard 4865: #ifdef DEBUGHESSII
1.126 brouard 4866: 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);
4867: 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);
4868: #endif
4869: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4870: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4871: k=kmax;
4872: }
4873: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4874: k=kmax; l=lmax*10;
1.126 brouard 4875: }
4876: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4877: delts=delt;
4878: }
1.203 brouard 4879: } /* End loop k */
1.126 brouard 4880: }
4881: delti[theta]=delts;
4882: return res;
4883:
4884: }
4885:
1.203 brouard 4886: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4887: {
4888: int i;
1.164 brouard 4889: int l=1, lmax=20;
1.126 brouard 4890: double k1,k2,k3,k4,res,fx;
1.132 brouard 4891: double p2[MAXPARM+1];
1.203 brouard 4892: int k, kmax=1;
4893: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4894:
4895: int firstime=0;
1.203 brouard 4896:
1.126 brouard 4897: fx=func(x);
1.203 brouard 4898: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4899: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4900: p2[thetai]=x[thetai]+delti[thetai]*k;
4901: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4902: k1=func(p2)-fx;
4903:
1.203 brouard 4904: p2[thetai]=x[thetai]+delti[thetai]*k;
4905: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4906: k2=func(p2)-fx;
4907:
1.203 brouard 4908: p2[thetai]=x[thetai]-delti[thetai]*k;
4909: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4910: k3=func(p2)-fx;
4911:
1.203 brouard 4912: p2[thetai]=x[thetai]-delti[thetai]*k;
4913: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4914: k4=func(p2)-fx;
1.203 brouard 4915: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4916: if(k1*k2*k3*k4 <0.){
1.208 brouard 4917: firstime=1;
1.203 brouard 4918: kmax=kmax+10;
1.208 brouard 4919: }
4920: if(kmax >=10 || firstime ==1){
1.246 brouard 4921: 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);
4922: 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 4923: 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);
4924: 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);
4925: }
4926: #ifdef DEBUGHESSIJ
4927: v1=hess[thetai][thetai];
4928: v2=hess[thetaj][thetaj];
4929: cv12=res;
4930: /* Computing eigen value of Hessian matrix */
4931: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4932: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4933: if ((lc2 <0) || (lc1 <0) ){
4934: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4935: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4936: 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);
4937: 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);
4938: }
1.126 brouard 4939: #endif
4940: }
4941: return res;
4942: }
4943:
1.203 brouard 4944: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4945: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4946: /* { */
4947: /* int i; */
4948: /* int l=1, lmax=20; */
4949: /* double k1,k2,k3,k4,res,fx; */
4950: /* double p2[MAXPARM+1]; */
4951: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4952: /* int k=0,kmax=10; */
4953: /* double l1; */
4954:
4955: /* fx=func(x); */
4956: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4957: /* l1=pow(10,l); */
4958: /* delts=delt; */
4959: /* for(k=1 ; k <kmax; k=k+1){ */
4960: /* delt = delti*(l1*k); */
4961: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4962: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4963: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4964: /* k1=func(p2)-fx; */
4965:
4966: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4967: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4968: /* k2=func(p2)-fx; */
4969:
4970: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4971: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4972: /* k3=func(p2)-fx; */
4973:
4974: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4975: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4976: /* k4=func(p2)-fx; */
4977: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4978: /* #ifdef DEBUGHESSIJ */
4979: /* 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); */
4980: /* 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); */
4981: /* #endif */
4982: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4983: /* k=kmax; */
4984: /* } */
4985: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4986: /* k=kmax; l=lmax*10; */
4987: /* } */
4988: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4989: /* delts=delt; */
4990: /* } */
4991: /* } /\* End loop k *\/ */
4992: /* } */
4993: /* delti[theta]=delts; */
4994: /* return res; */
4995: /* } */
4996:
4997:
1.126 brouard 4998: /************** Inverse of matrix **************/
4999: void ludcmp(double **a, int n, int *indx, double *d)
5000: {
5001: int i,imax,j,k;
5002: double big,dum,sum,temp;
5003: double *vv;
5004:
5005: vv=vector(1,n);
5006: *d=1.0;
5007: for (i=1;i<=n;i++) {
5008: big=0.0;
5009: for (j=1;j<=n;j++)
5010: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5011: if (big == 0.0){
5012: printf(" Singular Hessian matrix at row %d:\n",i);
5013: for (j=1;j<=n;j++) {
5014: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5015: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5016: }
5017: fflush(ficlog);
5018: fclose(ficlog);
5019: nrerror("Singular matrix in routine ludcmp");
5020: }
1.126 brouard 5021: vv[i]=1.0/big;
5022: }
5023: for (j=1;j<=n;j++) {
5024: for (i=1;i<j;i++) {
5025: sum=a[i][j];
5026: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5027: a[i][j]=sum;
5028: }
5029: big=0.0;
5030: for (i=j;i<=n;i++) {
5031: sum=a[i][j];
5032: for (k=1;k<j;k++)
5033: sum -= a[i][k]*a[k][j];
5034: a[i][j]=sum;
5035: if ( (dum=vv[i]*fabs(sum)) >= big) {
5036: big=dum;
5037: imax=i;
5038: }
5039: }
5040: if (j != imax) {
5041: for (k=1;k<=n;k++) {
5042: dum=a[imax][k];
5043: a[imax][k]=a[j][k];
5044: a[j][k]=dum;
5045: }
5046: *d = -(*d);
5047: vv[imax]=vv[j];
5048: }
5049: indx[j]=imax;
5050: if (a[j][j] == 0.0) a[j][j]=TINY;
5051: if (j != n) {
5052: dum=1.0/(a[j][j]);
5053: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5054: }
5055: }
5056: free_vector(vv,1,n); /* Doesn't work */
5057: ;
5058: }
5059:
5060: void lubksb(double **a, int n, int *indx, double b[])
5061: {
5062: int i,ii=0,ip,j;
5063: double sum;
5064:
5065: for (i=1;i<=n;i++) {
5066: ip=indx[i];
5067: sum=b[ip];
5068: b[ip]=b[i];
5069: if (ii)
5070: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5071: else if (sum) ii=i;
5072: b[i]=sum;
5073: }
5074: for (i=n;i>=1;i--) {
5075: sum=b[i];
5076: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5077: b[i]=sum/a[i][i];
5078: }
5079: }
5080:
5081: void pstamp(FILE *fichier)
5082: {
1.196 brouard 5083: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5084: }
5085:
1.297 brouard 5086: void date2dmy(double date,double *day, double *month, double *year){
5087: double yp=0., yp1=0., yp2=0.;
5088:
5089: yp1=modf(date,&yp);/* extracts integral of date in yp and
5090: fractional in yp1 */
5091: *year=yp;
5092: yp2=modf((yp1*12),&yp);
5093: *month=yp;
5094: yp1=modf((yp2*30.5),&yp);
5095: *day=yp;
5096: if(*day==0) *day=1;
5097: if(*month==0) *month=1;
5098: }
5099:
1.253 brouard 5100:
5101:
1.126 brouard 5102: /************ Frequencies ********************/
1.251 brouard 5103: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5104: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5105: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5106: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5107: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5108: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5109: int iind=0, iage=0;
5110: int mi; /* Effective wave */
5111: int first;
5112: double ***freq; /* Frequencies */
1.268 brouard 5113: 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 */
5114: 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 5115: double *meanq, *stdq, *idq;
1.226 brouard 5116: double **meanqt;
5117: double *pp, **prop, *posprop, *pospropt;
5118: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5119: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5120: double agebegin, ageend;
5121:
5122: pp=vector(1,nlstate);
1.251 brouard 5123: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5124: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5125: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5126: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5127: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5128: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5129: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5130: meanqt=matrix(1,lastpass,1,nqtveff);
5131: strcpy(fileresp,"P_");
5132: strcat(fileresp,fileresu);
5133: /*strcat(fileresphtm,fileresu);*/
5134: if((ficresp=fopen(fileresp,"w"))==NULL) {
5135: printf("Problem with prevalence resultfile: %s\n", fileresp);
5136: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5137: exit(0);
5138: }
1.240 brouard 5139:
1.226 brouard 5140: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5141: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5142: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5143: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5144: fflush(ficlog);
5145: exit(70);
5146: }
5147: else{
5148: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5149: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5150: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5151: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5152: }
1.319 brouard 5153: 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 5154:
1.226 brouard 5155: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5156: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5157: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5158: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5159: fflush(ficlog);
5160: exit(70);
1.240 brouard 5161: } else{
1.226 brouard 5162: 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 5163: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5164: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5165: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5166: }
1.319 brouard 5167: 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 5168:
1.253 brouard 5169: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5170: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5171: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5172: j1=0;
1.126 brouard 5173:
1.227 brouard 5174: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5175: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5176: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5177: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5178:
5179:
1.226 brouard 5180: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5181: reference=low_education V1=0,V2=0
5182: med_educ V1=1 V2=0,
5183: high_educ V1=0 V2=1
1.330 brouard 5184: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5185: */
1.249 brouard 5186: dateintsum=0;
5187: k2cpt=0;
5188:
1.253 brouard 5189: if(cptcoveff == 0 )
1.265 brouard 5190: nl=1; /* Constant and age model only */
1.253 brouard 5191: else
5192: nl=2;
1.265 brouard 5193:
5194: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5195: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5196: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5197: * freq[s1][s2][iage] =0.
5198: * Loop on iind
5199: * ++freq[s1][s2][iage] weighted
5200: * end iind
5201: * if covariate and j!0
5202: * headers Variable on one line
5203: * endif cov j!=0
5204: * header of frequency table by age
5205: * Loop on age
5206: * pp[s1]+=freq[s1][s2][iage] weighted
5207: * pos+=freq[s1][s2][iage] weighted
5208: * Loop on s1 initial state
5209: * fprintf(ficresp
5210: * end s1
5211: * end age
5212: * if j!=0 computes starting values
5213: * end compute starting values
5214: * end j1
5215: * end nl
5216: */
1.253 brouard 5217: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5218: if(nj==1)
5219: j=0; /* First pass for the constant */
1.265 brouard 5220: else{
1.335 brouard 5221: 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 5222: }
1.251 brouard 5223: first=1;
1.332 brouard 5224: 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 5225: posproptt=0.;
1.330 brouard 5226: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5227: scanf("%d", i);*/
5228: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5229: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5230: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5231: freq[i][s2][m]=0;
1.251 brouard 5232:
5233: for (i=1; i<=nlstate; i++) {
1.240 brouard 5234: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5235: prop[i][m]=0;
5236: posprop[i]=0;
5237: pospropt[i]=0;
5238: }
1.283 brouard 5239: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5240: idq[z1]=0.;
5241: meanq[z1]=0.;
5242: stdq[z1]=0.;
1.283 brouard 5243: }
5244: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5245: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5246: /* meanqt[m][z1]=0.; */
5247: /* } */
5248: /* } */
1.251 brouard 5249: /* dateintsum=0; */
5250: /* k2cpt=0; */
5251:
1.265 brouard 5252: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5253: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5254: bool=1;
5255: if(j !=0){
5256: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5257: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5258: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5259: /* if(Tvaraff[z1] ==-20){ */
5260: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5261: /* }else if(Tvaraff[z1] ==-10){ */
5262: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5263: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5264: /* 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); */
5265: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5266: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5267: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5268: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5269: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5270: /* 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", */
5271: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5272: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5273: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5274: } /* Onlyf fixed */
5275: } /* end z1 */
1.335 brouard 5276: } /* cptcoveff > 0 */
1.251 brouard 5277: } /* end any */
5278: }/* end j==0 */
1.265 brouard 5279: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5280: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5281: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5282: m=mw[mi][iind];
5283: if(j!=0){
5284: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5285: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5286: if( Fixed[Tmodelind[z1]]==1){
1.341 ! brouard 5287: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
! 5288: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5289: 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 5290: value is -1, we don't select. It differs from the
5291: constant and age model which counts them. */
5292: bool=0; /* not selected */
5293: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5294: /* i1=Tvaraff[z1]; */
5295: /* i2=TnsdVar[i1]; */
5296: /* i3=nbcode[i1][i2]; */
5297: /* i4=covar[i1][iind]; */
5298: /* if(i4 != i3){ */
5299: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5300: bool=0;
5301: }
5302: }
5303: }
5304: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5305: } /* end j==0 */
5306: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5307: if(bool==1){ /*Selected */
1.251 brouard 5308: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5309: and mw[mi+1][iind]. dh depends on stepm. */
5310: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5311: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5312: if(m >=firstpass && m <=lastpass){
5313: k2=anint[m][iind]+(mint[m][iind]/12.);
5314: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5315: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5316: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5317: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5318: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5319: if (m<lastpass) {
5320: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5321: /* 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]); */
5322: if(s[m][iind]==-1)
5323: 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.));
5324: 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 5325: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5326: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5327: idq[z1]=idq[z1]+weight[iind];
5328: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5329: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5330: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5331: }
1.284 brouard 5332: }
1.251 brouard 5333: /* if((int)agev[m][iind] == 55) */
5334: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5335: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5336: 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 5337: }
1.251 brouard 5338: } /* end if between passes */
5339: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5340: dateintsum=dateintsum+k2; /* on all covariates ?*/
5341: k2cpt++;
5342: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5343: }
1.251 brouard 5344: }else{
5345: bool=1;
5346: }/* end bool 2 */
5347: } /* end m */
1.284 brouard 5348: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5349: /* idq[z1]=idq[z1]+weight[iind]; */
5350: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5351: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5352: /* } */
1.251 brouard 5353: } /* end bool */
5354: } /* end iind = 1 to imx */
1.319 brouard 5355: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5356: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5357:
5358:
5359: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5360: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5361: pstamp(ficresp);
1.335 brouard 5362: if (cptcoveff>0 && j!=0){
1.265 brouard 5363: pstamp(ficresp);
1.251 brouard 5364: printf( "\n#********** Variable ");
5365: fprintf(ficresp, "\n#********** Variable ");
5366: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5367: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5368: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5369: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5370: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5371: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5372: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5373: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5374: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5375: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5376: }else{
1.330 brouard 5377: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5378: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5379: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5380: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5381: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5382: }
5383: }
5384: printf( "**********\n#");
5385: fprintf(ficresp, "**********\n#");
5386: fprintf(ficresphtm, "**********</h3>\n");
5387: fprintf(ficresphtmfr, "**********</h3>\n");
5388: fprintf(ficlog, "**********\n");
5389: }
1.284 brouard 5390: /*
5391: Printing means of quantitative variables if any
5392: */
5393: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5394: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5395: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5396: if(weightopt==1){
5397: printf(" Weighted mean and standard deviation of");
5398: fprintf(ficlog," Weighted mean and standard deviation of");
5399: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5400: }
1.311 brouard 5401: /* mu = \frac{w x}{\sum w}
5402: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5403: */
5404: 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]));
5405: 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]));
5406: 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 5407: }
5408: /* for (z1=1; z1<= nqtveff; z1++) { */
5409: /* for(m=1;m<=lastpass;m++){ */
5410: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5411: /* } */
5412: /* } */
1.283 brouard 5413:
1.251 brouard 5414: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5415: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5416: fprintf(ficresp, " Age");
1.335 brouard 5417: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5418: 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]]);
5419: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5420: }
1.251 brouard 5421: for(i=1; i<=nlstate;i++) {
1.335 brouard 5422: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5423: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5424: }
1.335 brouard 5425: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5426: fprintf(ficresphtm, "\n");
5427:
5428: /* Header of frequency table by age */
5429: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5430: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5431: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5432: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5433: if(s2!=0 && m!=0)
5434: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5435: }
1.226 brouard 5436: }
1.251 brouard 5437: fprintf(ficresphtmfr, "\n");
5438:
5439: /* For each age */
5440: for(iage=iagemin; iage <= iagemax+3; iage++){
5441: fprintf(ficresphtm,"<tr>");
5442: if(iage==iagemax+1){
5443: fprintf(ficlog,"1");
5444: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5445: }else if(iage==iagemax+2){
5446: fprintf(ficlog,"0");
5447: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5448: }else if(iage==iagemax+3){
5449: fprintf(ficlog,"Total");
5450: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5451: }else{
1.240 brouard 5452: if(first==1){
1.251 brouard 5453: first=0;
5454: printf("See log file for details...\n");
5455: }
5456: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5457: fprintf(ficlog,"Age %d", iage);
5458: }
1.265 brouard 5459: for(s1=1; s1 <=nlstate ; s1++){
5460: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5461: pp[s1] += freq[s1][m][iage];
1.251 brouard 5462: }
1.265 brouard 5463: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5464: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5465: pos += freq[s1][m][iage];
5466: if(pp[s1]>=1.e-10){
1.251 brouard 5467: if(first==1){
1.265 brouard 5468: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5469: }
1.265 brouard 5470: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5471: }else{
5472: if(first==1)
1.265 brouard 5473: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5474: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5475: }
5476: }
5477:
1.265 brouard 5478: for(s1=1; s1 <=nlstate ; s1++){
5479: /* posprop[s1]=0; */
5480: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5481: pp[s1] += freq[s1][m][iage];
5482: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5483:
5484: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5485: pos += pp[s1]; /* pos is the total number of transitions until this age */
5486: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5487: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5488: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5489: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5490: }
5491:
5492: /* Writing ficresp */
1.335 brouard 5493: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5494: if( iage <= iagemax){
5495: fprintf(ficresp," %d",iage);
5496: }
5497: }else if( nj==2){
5498: if( iage <= iagemax){
5499: fprintf(ficresp," %d",iage);
1.335 brouard 5500: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5501: }
1.240 brouard 5502: }
1.265 brouard 5503: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5504: if(pos>=1.e-5){
1.251 brouard 5505: if(first==1)
1.265 brouard 5506: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5507: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5508: }else{
5509: if(first==1)
1.265 brouard 5510: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5511: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5512: }
5513: if( iage <= iagemax){
5514: if(pos>=1.e-5){
1.335 brouard 5515: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5516: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5517: }else if( nj==2){
5518: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5519: }
5520: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5521: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5522: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5523: } else{
1.335 brouard 5524: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5525: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5526: }
1.240 brouard 5527: }
1.265 brouard 5528: pospropt[s1] +=posprop[s1];
5529: } /* end loop s1 */
1.251 brouard 5530: /* pospropt=0.; */
1.265 brouard 5531: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5532: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5533: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5534: if(first==1){
1.265 brouard 5535: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5536: }
1.265 brouard 5537: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5538: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5539: }
1.265 brouard 5540: if(s1!=0 && m!=0)
5541: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5542: }
1.265 brouard 5543: } /* end loop s1 */
1.251 brouard 5544: posproptt=0.;
1.265 brouard 5545: for(s1=1; s1 <=nlstate; s1++){
5546: posproptt += pospropt[s1];
1.251 brouard 5547: }
5548: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5549: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5550: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5551: if(iage <= iagemax)
5552: fprintf(ficresp,"\n");
1.240 brouard 5553: }
1.251 brouard 5554: if(first==1)
5555: printf("Others in log...\n");
5556: fprintf(ficlog,"\n");
5557: } /* end loop age iage */
1.265 brouard 5558:
1.251 brouard 5559: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5560: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5561: if(posproptt < 1.e-5){
1.265 brouard 5562: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5563: }else{
1.265 brouard 5564: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5565: }
1.226 brouard 5566: }
1.251 brouard 5567: fprintf(ficresphtm,"</tr>\n");
5568: fprintf(ficresphtm,"</table>\n");
5569: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5570: if(posproptt < 1.e-5){
1.251 brouard 5571: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5572: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5573: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5574: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5575: invalidvarcomb[j1]=1;
1.226 brouard 5576: }else{
1.338 brouard 5577: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5578: invalidvarcomb[j1]=0;
1.226 brouard 5579: }
1.251 brouard 5580: fprintf(ficresphtmfr,"</table>\n");
5581: fprintf(ficlog,"\n");
5582: if(j!=0){
5583: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5584: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5585: for(k=1; k <=(nlstate+ndeath); k++){
5586: if (k != i) {
1.265 brouard 5587: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5588: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5589: if(j1==1){ /* All dummy covariates to zero */
5590: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5591: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5592: printf("%d%d ",i,k);
5593: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5594: 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]));
5595: 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]));
5596: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5597: }
1.253 brouard 5598: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5599: for(iage=iagemin; iage <= iagemax+3; iage++){
5600: x[iage]= (double)iage;
5601: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5602: /* 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 5603: }
1.268 brouard 5604: /* Some are not finite, but linreg will ignore these ages */
5605: no=0;
1.253 brouard 5606: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5607: pstart[s1]=b;
5608: pstart[s1-1]=a;
1.252 brouard 5609: }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 */
5610: 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]);
5611: 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 5612: 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 5613: printf("%d%d ",i,k);
5614: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5615: 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 5616: }else{ /* Other cases, like quantitative fixed or varying covariates */
5617: ;
5618: }
5619: /* printf("%12.7f )", param[i][jj][k]); */
5620: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5621: s1++;
1.251 brouard 5622: } /* end jj */
5623: } /* end k!= i */
5624: } /* end k */
1.265 brouard 5625: } /* end i, s1 */
1.251 brouard 5626: } /* end j !=0 */
5627: } /* end selected combination of covariate j1 */
5628: if(j==0){ /* We can estimate starting values from the occurences in each case */
5629: printf("#Freqsummary: Starting values for the constants:\n");
5630: fprintf(ficlog,"\n");
1.265 brouard 5631: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5632: for(k=1; k <=(nlstate+ndeath); k++){
5633: if (k != i) {
5634: printf("%d%d ",i,k);
5635: fprintf(ficlog,"%d%d ",i,k);
5636: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5637: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5638: if(jj==1){ /* Age has to be done */
1.265 brouard 5639: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5640: 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]));
5641: 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 5642: }
5643: /* printf("%12.7f )", param[i][jj][k]); */
5644: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5645: s1++;
1.250 brouard 5646: }
1.251 brouard 5647: printf("\n");
5648: fprintf(ficlog,"\n");
1.250 brouard 5649: }
5650: }
1.284 brouard 5651: } /* end of state i */
1.251 brouard 5652: printf("#Freqsummary\n");
5653: fprintf(ficlog,"\n");
1.265 brouard 5654: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5655: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5656: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5657: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5658: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5659: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5660: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5661: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5662: /* } */
5663: }
1.265 brouard 5664: } /* end loop s1 */
1.251 brouard 5665:
5666: printf("\n");
5667: fprintf(ficlog,"\n");
5668: } /* end j=0 */
1.249 brouard 5669: } /* end j */
1.252 brouard 5670:
1.253 brouard 5671: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5672: for(i=1, jk=1; i <=nlstate; i++){
5673: for(j=1; j <=nlstate+ndeath; j++){
5674: if(j!=i){
5675: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5676: printf("%1d%1d",i,j);
5677: fprintf(ficparo,"%1d%1d",i,j);
5678: for(k=1; k<=ncovmodel;k++){
5679: /* printf(" %lf",param[i][j][k]); */
5680: /* fprintf(ficparo," %lf",param[i][j][k]); */
5681: p[jk]=pstart[jk];
5682: printf(" %f ",pstart[jk]);
5683: fprintf(ficparo," %f ",pstart[jk]);
5684: jk++;
5685: }
5686: printf("\n");
5687: fprintf(ficparo,"\n");
5688: }
5689: }
5690: }
5691: } /* end mle=-2 */
1.226 brouard 5692: dateintmean=dateintsum/k2cpt;
1.296 brouard 5693: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5694:
1.226 brouard 5695: fclose(ficresp);
5696: fclose(ficresphtm);
5697: fclose(ficresphtmfr);
1.283 brouard 5698: free_vector(idq,1,nqfveff);
1.226 brouard 5699: free_vector(meanq,1,nqfveff);
1.284 brouard 5700: free_vector(stdq,1,nqfveff);
1.226 brouard 5701: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5702: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5703: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5704: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5705: free_vector(pospropt,1,nlstate);
5706: free_vector(posprop,1,nlstate);
1.251 brouard 5707: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5708: free_vector(pp,1,nlstate);
5709: /* End of freqsummary */
5710: }
1.126 brouard 5711:
1.268 brouard 5712: /* Simple linear regression */
5713: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5714:
5715: /* y=a+bx regression */
5716: double sumx = 0.0; /* sum of x */
5717: double sumx2 = 0.0; /* sum of x**2 */
5718: double sumxy = 0.0; /* sum of x * y */
5719: double sumy = 0.0; /* sum of y */
5720: double sumy2 = 0.0; /* sum of y**2 */
5721: double sume2 = 0.0; /* sum of square or residuals */
5722: double yhat;
5723:
5724: double denom=0;
5725: int i;
5726: int ne=*no;
5727:
5728: for ( i=ifi, ne=0;i<=ila;i++) {
5729: if(!isfinite(x[i]) || !isfinite(y[i])){
5730: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5731: continue;
5732: }
5733: ne=ne+1;
5734: sumx += x[i];
5735: sumx2 += x[i]*x[i];
5736: sumxy += x[i] * y[i];
5737: sumy += y[i];
5738: sumy2 += y[i]*y[i];
5739: denom = (ne * sumx2 - sumx*sumx);
5740: /* 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); */
5741: }
5742:
5743: denom = (ne * sumx2 - sumx*sumx);
5744: if (denom == 0) {
5745: // vertical, slope m is infinity
5746: *b = INFINITY;
5747: *a = 0;
5748: if (r) *r = 0;
5749: return 1;
5750: }
5751:
5752: *b = (ne * sumxy - sumx * sumy) / denom;
5753: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5754: if (r!=NULL) {
5755: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5756: sqrt((sumx2 - sumx*sumx/ne) *
5757: (sumy2 - sumy*sumy/ne));
5758: }
5759: *no=ne;
5760: for ( i=ifi, ne=0;i<=ila;i++) {
5761: if(!isfinite(x[i]) || !isfinite(y[i])){
5762: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5763: continue;
5764: }
5765: ne=ne+1;
5766: yhat = y[i] - *a -*b* x[i];
5767: sume2 += yhat * yhat ;
5768:
5769: denom = (ne * sumx2 - sumx*sumx);
5770: /* 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); */
5771: }
5772: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5773: *sa= *sb * sqrt(sumx2/ne);
5774:
5775: return 0;
5776: }
5777:
1.126 brouard 5778: /************ Prevalence ********************/
1.227 brouard 5779: 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)
5780: {
5781: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5782: in each health status at the date of interview (if between dateprev1 and dateprev2).
5783: We still use firstpass and lastpass as another selection.
5784: */
1.126 brouard 5785:
1.227 brouard 5786: int i, m, jk, j1, bool, z1,j, iv;
5787: int mi; /* Effective wave */
5788: int iage;
5789: double agebegin, ageend;
5790:
5791: double **prop;
5792: double posprop;
5793: double y2; /* in fractional years */
5794: int iagemin, iagemax;
5795: int first; /** to stop verbosity which is redirected to log file */
5796:
5797: iagemin= (int) agemin;
5798: iagemax= (int) agemax;
5799: /*pp=vector(1,nlstate);*/
1.251 brouard 5800: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5801: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5802: j1=0;
1.222 brouard 5803:
1.227 brouard 5804: /*j=cptcoveff;*/
5805: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5806:
1.288 brouard 5807: first=0;
1.335 brouard 5808: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 5809: for (i=1; i<=nlstate; i++)
1.251 brouard 5810: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5811: prop[i][iage]=0.0;
5812: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5813: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5814: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5815:
5816: for (i=1; i<=imx; i++) { /* Each individual */
5817: bool=1;
5818: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5819: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5820: m=mw[mi][i];
5821: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5822: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5823: for (z1=1; z1<=cptcoveff; z1++){
5824: if( Fixed[Tmodelind[z1]]==1){
1.341 ! brouard 5825: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 5826: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 5827: bool=0;
5828: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 5829: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 5830: bool=0;
5831: }
5832: }
5833: if(bool==1){ /* Otherwise we skip that wave/person */
5834: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5835: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5836: if(m >=firstpass && m <=lastpass){
5837: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5838: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5839: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5840: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5841: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5842: 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);
5843: exit(1);
5844: }
5845: if (s[m][i]>0 && s[m][i]<=nlstate) {
5846: /*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]]);*/
5847: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5848: prop[s[m][i]][iagemax+3] += weight[i];
5849: } /* end valid statuses */
5850: } /* end selection of dates */
5851: } /* end selection of waves */
5852: } /* end bool */
5853: } /* end wave */
5854: } /* end individual */
5855: for(i=iagemin; i <= iagemax+3; i++){
5856: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5857: posprop += prop[jk][i];
5858: }
5859:
5860: for(jk=1; jk <=nlstate ; jk++){
5861: if( i <= iagemax){
5862: if(posprop>=1.e-5){
5863: probs[i][jk][j1]= prop[jk][i]/posprop;
5864: } else{
1.288 brouard 5865: if(!first){
5866: first=1;
1.266 brouard 5867: 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]);
5868: }else{
1.288 brouard 5869: 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 5870: }
5871: }
5872: }
5873: }/* end jk */
5874: }/* end i */
1.222 brouard 5875: /*} *//* end i1 */
1.227 brouard 5876: } /* end j1 */
1.222 brouard 5877:
1.227 brouard 5878: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5879: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5880: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5881: } /* End of prevalence */
1.126 brouard 5882:
5883: /************* Waves Concatenation ***************/
5884:
5885: 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)
5886: {
1.298 brouard 5887: /* 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 5888: Death is a valid wave (if date is known).
5889: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5890: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5891: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5892: */
1.126 brouard 5893:
1.224 brouard 5894: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5895: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5896: double sum=0., jmean=0.;*/
1.224 brouard 5897: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5898: int j, k=0,jk, ju, jl;
5899: double sum=0.;
5900: first=0;
1.214 brouard 5901: firstwo=0;
1.217 brouard 5902: firsthree=0;
1.218 brouard 5903: firstfour=0;
1.164 brouard 5904: jmin=100000;
1.126 brouard 5905: jmax=-1;
5906: jmean=0.;
1.224 brouard 5907:
5908: /* Treating live states */
1.214 brouard 5909: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5910: mi=0; /* First valid wave */
1.227 brouard 5911: mli=0; /* Last valid wave */
1.309 brouard 5912: m=firstpass; /* Loop on waves */
5913: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5914: 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 */
5915: mli=m-1;/* mw[++mi][i]=m-1; */
5916: }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 5917: 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 5918: mli=m;
1.224 brouard 5919: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5920: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5921: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5922: }
1.309 brouard 5923: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5924: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5925: break;
1.224 brouard 5926: #else
1.317 brouard 5927: 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 5928: if(firsthree == 0){
1.302 brouard 5929: 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 5930: firsthree=1;
1.317 brouard 5931: }else if(firsthree >=1 && firsthree < 10){
5932: 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);
5933: firsthree++;
5934: }else if(firsthree == 10){
5935: printf("Information, too many Information flags: no more reported to log either\n");
5936: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5937: firsthree++;
5938: }else{
5939: firsthree++;
1.227 brouard 5940: }
1.309 brouard 5941: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5942: mli=m;
5943: }
5944: if(s[m][i]==-2){ /* Vital status is really unknown */
5945: nbwarn++;
1.309 brouard 5946: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5947: 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);
5948: 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);
5949: }
5950: break;
5951: }
5952: break;
1.224 brouard 5953: #endif
1.227 brouard 5954: }/* End m >= lastpass */
1.126 brouard 5955: }/* end while */
1.224 brouard 5956:
1.227 brouard 5957: /* 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 5958: /* After last pass */
1.224 brouard 5959: /* Treating death states */
1.214 brouard 5960: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5961: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5962: /* } */
1.126 brouard 5963: mi++; /* Death is another wave */
5964: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5965: /* Only death is a correct wave */
1.126 brouard 5966: mw[mi][i]=m;
1.257 brouard 5967: } /* else not in a death state */
1.224 brouard 5968: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5969: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5970: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5971: 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 5972: nbwarn++;
5973: if(firstfiv==0){
1.309 brouard 5974: 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 5975: firstfiv=1;
5976: }else{
1.309 brouard 5977: 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 5978: }
1.309 brouard 5979: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5980: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5981: nberr++;
5982: if(firstwo==0){
1.309 brouard 5983: 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 5984: firstwo=1;
5985: }
1.309 brouard 5986: 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 5987: }
1.257 brouard 5988: }else{ /* if date of interview is unknown */
1.227 brouard 5989: /* death is known but not confirmed by death status at any wave */
5990: if(firstfour==0){
1.309 brouard 5991: 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 5992: firstfour=1;
5993: }
1.309 brouard 5994: 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 5995: }
1.224 brouard 5996: } /* end if date of death is known */
5997: #endif
1.309 brouard 5998: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5999: /* wav[i]=mw[mi][i]; */
1.126 brouard 6000: if(mi==0){
6001: nbwarn++;
6002: if(first==0){
1.227 brouard 6003: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6004: first=1;
1.126 brouard 6005: }
6006: if(first==1){
1.227 brouard 6007: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6008: }
6009: } /* end mi==0 */
6010: } /* End individuals */
1.214 brouard 6011: /* wav and mw are no more changed */
1.223 brouard 6012:
1.317 brouard 6013: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6014: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6015:
6016:
1.126 brouard 6017: for(i=1; i<=imx; i++){
6018: for(mi=1; mi<wav[i];mi++){
6019: if (stepm <=0)
1.227 brouard 6020: dh[mi][i]=1;
1.126 brouard 6021: else{
1.260 brouard 6022: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6023: if (agedc[i] < 2*AGESUP) {
6024: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6025: if(j==0) j=1; /* Survives at least one month after exam */
6026: else if(j<0){
6027: nberr++;
6028: 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]);
6029: j=1; /* Temporary Dangerous patch */
6030: 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);
6031: 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]);
6032: 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);
6033: }
6034: k=k+1;
6035: if (j >= jmax){
6036: jmax=j;
6037: ijmax=i;
6038: }
6039: if (j <= jmin){
6040: jmin=j;
6041: ijmin=i;
6042: }
6043: sum=sum+j;
6044: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6045: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6046: }
6047: }
6048: else{
6049: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6050: /* 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 6051:
1.227 brouard 6052: k=k+1;
6053: if (j >= jmax) {
6054: jmax=j;
6055: ijmax=i;
6056: }
6057: else if (j <= jmin){
6058: jmin=j;
6059: ijmin=i;
6060: }
6061: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6062: /*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]);*/
6063: if(j<0){
6064: nberr++;
6065: 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]);
6066: 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]);
6067: }
6068: sum=sum+j;
6069: }
6070: jk= j/stepm;
6071: jl= j -jk*stepm;
6072: ju= j -(jk+1)*stepm;
6073: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6074: if(jl==0){
6075: dh[mi][i]=jk;
6076: bh[mi][i]=0;
6077: }else{ /* We want a negative bias in order to only have interpolation ie
6078: * to avoid the price of an extra matrix product in likelihood */
6079: dh[mi][i]=jk+1;
6080: bh[mi][i]=ju;
6081: }
6082: }else{
6083: if(jl <= -ju){
6084: dh[mi][i]=jk;
6085: bh[mi][i]=jl; /* bias is positive if real duration
6086: * is higher than the multiple of stepm and negative otherwise.
6087: */
6088: }
6089: else{
6090: dh[mi][i]=jk+1;
6091: bh[mi][i]=ju;
6092: }
6093: if(dh[mi][i]==0){
6094: dh[mi][i]=1; /* At least one step */
6095: bh[mi][i]=ju; /* At least one step */
6096: /* 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);*/
6097: }
6098: } /* end if mle */
1.126 brouard 6099: }
6100: } /* end wave */
6101: }
6102: jmean=sum/k;
6103: 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 6104: 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 6105: }
1.126 brouard 6106:
6107: /*********** Tricode ****************************/
1.220 brouard 6108: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6109: {
6110: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6111: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6112: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6113: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6114: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6115: */
1.130 brouard 6116:
1.242 brouard 6117: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6118: int modmaxcovj=0; /* Modality max of covariates j */
6119: int cptcode=0; /* Modality max of covariates j */
6120: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6121:
6122:
1.242 brouard 6123: /* cptcoveff=0; */
6124: /* *cptcov=0; */
1.126 brouard 6125:
1.242 brouard 6126: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6127: for (k=1; k <= maxncov; k++)
6128: for(j=1; j<=2; j++)
6129: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6130:
1.242 brouard 6131: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6132: 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 6133: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.339 brouard 6134: printf("Testing k=%d, cptcovt=%d\n",k, cptcovt);
6135: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 6136: switch(Fixed[k]) {
6137: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6138: modmaxcovj=0;
6139: modmincovj=0;
1.242 brouard 6140: 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 6141: /* 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 6142: ij=(int)(covar[Tvar[k]][i]);
6143: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6144: * If product of Vn*Vm, still boolean *:
6145: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6146: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6147: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6148: modality of the nth covariate of individual i. */
6149: if (ij > modmaxcovj)
6150: modmaxcovj=ij;
6151: else if (ij < modmincovj)
6152: modmincovj=ij;
1.287 brouard 6153: if (ij <0 || ij >1 ){
1.311 brouard 6154: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6155: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6156: fflush(ficlog);
6157: exit(1);
1.287 brouard 6158: }
6159: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6160: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6161: exit(1);
6162: }else
6163: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6164: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6165: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6166: /* getting the maximum value of the modality of the covariate
6167: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6168: female ies 1, then modmaxcovj=1.
6169: */
6170: } /* end for loop on individuals i */
6171: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6172: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6173: cptcode=modmaxcovj;
6174: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6175: /*for (i=0; i<=cptcode; i++) {*/
6176: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6177: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6178: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6179: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6180: if( j != -1){
6181: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6182: covariate for which somebody answered excluding
6183: undefined. Usually 2: 0 and 1. */
6184: }
6185: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6186: covariate for which somebody answered including
6187: undefined. Usually 3: -1, 0 and 1. */
6188: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6189: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6190: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6191:
1.242 brouard 6192: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6193: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6194: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6195: /* modmincovj=3; modmaxcovj = 7; */
6196: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6197: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6198: /* defining two dummy variables: variables V1_1 and V1_2.*/
6199: /* nbcode[Tvar[j]][ij]=k; */
6200: /* nbcode[Tvar[j]][1]=0; */
6201: /* nbcode[Tvar[j]][2]=1; */
6202: /* nbcode[Tvar[j]][3]=2; */
6203: /* To be continued (not working yet). */
6204: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6205:
6206: /* 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*/
6207: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6208: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6209: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6210: /*, could be restored in the future */
6211: 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 6212: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6213: break;
6214: }
6215: ij++;
1.287 brouard 6216: 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 6217: cptcode = ij; /* New max modality for covar j */
6218: } /* end of loop on modality i=-1 to 1 or more */
6219: break;
6220: case 1: /* Testing on varying covariate, could be simple and
6221: * should look at waves or product of fixed *
6222: * varying. No time to test -1, assuming 0 and 1 only */
6223: ij=0;
6224: for(i=0; i<=1;i++){
6225: nbcode[Tvar[k]][++ij]=i;
6226: }
6227: break;
6228: default:
6229: break;
6230: } /* end switch */
6231: } /* end dummy test */
1.334 brouard 6232: if(Dummy[k]==1 && Typevar[k] !=1){ /* Quantitative covariate and not age product */
1.311 brouard 6233: 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 6234: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6235: printf("Error k=%d \n",k);
6236: exit(1);
6237: }
1.311 brouard 6238: if(isnan(covar[Tvar[k]][i])){
6239: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6240: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6241: fflush(ficlog);
6242: exit(1);
6243: }
6244: }
1.335 brouard 6245: } /* end Quanti */
1.287 brouard 6246: } /* 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 6247:
6248: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6249: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6250: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6251: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6252: 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 */
6253: 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 */
6254: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6255: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6256:
6257: ij=0;
6258: /* 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 6259: 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 */
6260: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6261: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6262: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6263: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6264: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6265: /* 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 6266: /* If product not in single variable we don't print results */
6267: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6268: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6269: /* k= 1 2 3 4 5 6 7 8 9 */
6270: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6271: /* ij 1 2 3 */
6272: /* Tvaraff[ij]= 4 3 1 */
6273: /* Tmodelind[ij]=2 3 9 */
6274: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6275: 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*/
6276: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6277: 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 */
6278: if(Fixed[k]!=0)
6279: anyvaryingduminmodel=1;
6280: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6281: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6282: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6283: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6284: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6285: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6286: }
6287: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6288: /* ij--; */
6289: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6290: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6291: * because they can be excluded from the model and real
6292: * if in the model but excluded because missing values, but how to get k from ij?*/
6293: for(j=ij+1; j<= cptcovt; j++){
6294: Tvaraff[j]=0;
6295: Tmodelind[j]=0;
6296: }
6297: for(j=ntveff+1; j<= cptcovt; j++){
6298: TmodelInvind[j]=0;
6299: }
6300: /* To be sorted */
6301: ;
6302: }
1.126 brouard 6303:
1.145 brouard 6304:
1.126 brouard 6305: /*********** Health Expectancies ****************/
6306:
1.235 brouard 6307: 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 6308:
6309: {
6310: /* Health expectancies, no variances */
1.329 brouard 6311: /* cij is the combination in the list of combination of dummy covariates */
6312: /* strstart is a string of time at start of computing */
1.164 brouard 6313: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6314: int nhstepma, nstepma; /* Decreasing with age */
6315: double age, agelim, hf;
6316: double ***p3mat;
6317: double eip;
6318:
1.238 brouard 6319: /* pstamp(ficreseij); */
1.126 brouard 6320: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6321: fprintf(ficreseij,"# Age");
6322: for(i=1; i<=nlstate;i++){
6323: for(j=1; j<=nlstate;j++){
6324: fprintf(ficreseij," e%1d%1d ",i,j);
6325: }
6326: fprintf(ficreseij," e%1d. ",i);
6327: }
6328: fprintf(ficreseij,"\n");
6329:
6330:
6331: if(estepm < stepm){
6332: printf ("Problem %d lower than %d\n",estepm, stepm);
6333: }
6334: else hstepm=estepm;
6335: /* We compute the life expectancy from trapezoids spaced every estepm months
6336: * This is mainly to measure the difference between two models: for example
6337: * if stepm=24 months pijx are given only every 2 years and by summing them
6338: * we are calculating an estimate of the Life Expectancy assuming a linear
6339: * progression in between and thus overestimating or underestimating according
6340: * to the curvature of the survival function. If, for the same date, we
6341: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6342: * to compare the new estimate of Life expectancy with the same linear
6343: * hypothesis. A more precise result, taking into account a more precise
6344: * curvature will be obtained if estepm is as small as stepm. */
6345:
6346: /* For example we decided to compute the life expectancy with the smallest unit */
6347: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6348: nhstepm is the number of hstepm from age to agelim
6349: nstepm is the number of stepm from age to agelin.
1.270 brouard 6350: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6351: and note for a fixed period like estepm months */
6352: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6353: survival function given by stepm (the optimization length). Unfortunately it
6354: means that if the survival funtion is printed only each two years of age and if
6355: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6356: results. So we changed our mind and took the option of the best precision.
6357: */
6358: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6359:
6360: agelim=AGESUP;
6361: /* If stepm=6 months */
6362: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6363: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6364:
6365: /* nhstepm age range expressed in number of stepm */
6366: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6367: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6368: /* if (stepm >= YEARM) hstepm=1;*/
6369: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6370: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6371:
6372: for (age=bage; age<=fage; age ++){
6373: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6374: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6375: /* if (stepm >= YEARM) hstepm=1;*/
6376: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6377:
6378: /* If stepm=6 months */
6379: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6380: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6381: /* 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 6382: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6383:
6384: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6385:
6386: printf("%d|",(int)age);fflush(stdout);
6387: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6388:
6389: /* Computing expectancies */
6390: for(i=1; i<=nlstate;i++)
6391: for(j=1; j<=nlstate;j++)
6392: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6393: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6394:
6395: /* 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]);*/
6396:
6397: }
6398:
6399: fprintf(ficreseij,"%3.0f",age );
6400: for(i=1; i<=nlstate;i++){
6401: eip=0;
6402: for(j=1; j<=nlstate;j++){
6403: eip +=eij[i][j][(int)age];
6404: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6405: }
6406: fprintf(ficreseij,"%9.4f", eip );
6407: }
6408: fprintf(ficreseij,"\n");
6409:
6410: }
6411: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6412: printf("\n");
6413: fprintf(ficlog,"\n");
6414:
6415: }
6416:
1.235 brouard 6417: 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 6418:
6419: {
6420: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6421: to initial status i, ei. .
1.126 brouard 6422: */
1.336 brouard 6423: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6424: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6425: int nhstepma, nstepma; /* Decreasing with age */
6426: double age, agelim, hf;
6427: double ***p3matp, ***p3matm, ***varhe;
6428: double **dnewm,**doldm;
6429: double *xp, *xm;
6430: double **gp, **gm;
6431: double ***gradg, ***trgradg;
6432: int theta;
6433:
6434: double eip, vip;
6435:
6436: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6437: xp=vector(1,npar);
6438: xm=vector(1,npar);
6439: dnewm=matrix(1,nlstate*nlstate,1,npar);
6440: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6441:
6442: pstamp(ficresstdeij);
6443: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6444: fprintf(ficresstdeij,"# Age");
6445: for(i=1; i<=nlstate;i++){
6446: for(j=1; j<=nlstate;j++)
6447: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6448: fprintf(ficresstdeij," e%1d. ",i);
6449: }
6450: fprintf(ficresstdeij,"\n");
6451:
6452: pstamp(ficrescveij);
6453: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6454: fprintf(ficrescveij,"# Age");
6455: for(i=1; i<=nlstate;i++)
6456: for(j=1; j<=nlstate;j++){
6457: cptj= (j-1)*nlstate+i;
6458: for(i2=1; i2<=nlstate;i2++)
6459: for(j2=1; j2<=nlstate;j2++){
6460: cptj2= (j2-1)*nlstate+i2;
6461: if(cptj2 <= cptj)
6462: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6463: }
6464: }
6465: fprintf(ficrescveij,"\n");
6466:
6467: if(estepm < stepm){
6468: printf ("Problem %d lower than %d\n",estepm, stepm);
6469: }
6470: else hstepm=estepm;
6471: /* We compute the life expectancy from trapezoids spaced every estepm months
6472: * This is mainly to measure the difference between two models: for example
6473: * if stepm=24 months pijx are given only every 2 years and by summing them
6474: * we are calculating an estimate of the Life Expectancy assuming a linear
6475: * progression in between and thus overestimating or underestimating according
6476: * to the curvature of the survival function. If, for the same date, we
6477: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6478: * to compare the new estimate of Life expectancy with the same linear
6479: * hypothesis. A more precise result, taking into account a more precise
6480: * curvature will be obtained if estepm is as small as stepm. */
6481:
6482: /* For example we decided to compute the life expectancy with the smallest unit */
6483: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6484: nhstepm is the number of hstepm from age to agelim
6485: nstepm is the number of stepm from age to agelin.
6486: Look at hpijx to understand the reason of that which relies in memory size
6487: and note for a fixed period like estepm months */
6488: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6489: survival function given by stepm (the optimization length). Unfortunately it
6490: means that if the survival funtion is printed only each two years of age and if
6491: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6492: results. So we changed our mind and took the option of the best precision.
6493: */
6494: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6495:
6496: /* If stepm=6 months */
6497: /* nhstepm age range expressed in number of stepm */
6498: agelim=AGESUP;
6499: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6500: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6501: /* if (stepm >= YEARM) hstepm=1;*/
6502: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6503:
6504: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6505: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6506: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6507: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6508: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6509: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6510:
6511: for (age=bage; age<=fage; age ++){
6512: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6513: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6514: /* if (stepm >= YEARM) hstepm=1;*/
6515: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6516:
1.126 brouard 6517: /* If stepm=6 months */
6518: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6519: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6520:
6521: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6522:
1.126 brouard 6523: /* Computing Variances of health expectancies */
6524: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6525: decrease memory allocation */
6526: for(theta=1; theta <=npar; theta++){
6527: for(i=1; i<=npar; i++){
1.222 brouard 6528: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6529: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6530: }
1.235 brouard 6531: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6532: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6533:
1.126 brouard 6534: for(j=1; j<= nlstate; j++){
1.222 brouard 6535: for(i=1; i<=nlstate; i++){
6536: for(h=0; h<=nhstepm-1; h++){
6537: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6538: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6539: }
6540: }
1.126 brouard 6541: }
1.218 brouard 6542:
1.126 brouard 6543: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6544: for(h=0; h<=nhstepm-1; h++){
6545: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6546: }
1.126 brouard 6547: }/* End theta */
6548:
6549:
6550: for(h=0; h<=nhstepm-1; h++)
6551: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6552: for(theta=1; theta <=npar; theta++)
6553: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6554:
1.218 brouard 6555:
1.222 brouard 6556: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6557: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6558: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6559:
1.222 brouard 6560: printf("%d|",(int)age);fflush(stdout);
6561: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6562: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6563: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6564: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6565: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6566: for(ij=1;ij<=nlstate*nlstate;ij++)
6567: for(ji=1;ji<=nlstate*nlstate;ji++)
6568: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6569: }
6570: }
1.320 brouard 6571: /* if((int)age ==50){ */
6572: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6573: /* } */
1.126 brouard 6574: /* Computing expectancies */
1.235 brouard 6575: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6576: for(i=1; i<=nlstate;i++)
6577: for(j=1; j<=nlstate;j++)
1.222 brouard 6578: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6579: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6580:
1.222 brouard 6581: /* 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 6582:
1.222 brouard 6583: }
1.269 brouard 6584:
6585: /* Standard deviation of expectancies ij */
1.126 brouard 6586: fprintf(ficresstdeij,"%3.0f",age );
6587: for(i=1; i<=nlstate;i++){
6588: eip=0.;
6589: vip=0.;
6590: for(j=1; j<=nlstate;j++){
1.222 brouard 6591: eip += eij[i][j][(int)age];
6592: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6593: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6594: 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 6595: }
6596: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6597: }
6598: fprintf(ficresstdeij,"\n");
1.218 brouard 6599:
1.269 brouard 6600: /* Variance of expectancies ij */
1.126 brouard 6601: fprintf(ficrescveij,"%3.0f",age );
6602: for(i=1; i<=nlstate;i++)
6603: for(j=1; j<=nlstate;j++){
1.222 brouard 6604: cptj= (j-1)*nlstate+i;
6605: for(i2=1; i2<=nlstate;i2++)
6606: for(j2=1; j2<=nlstate;j2++){
6607: cptj2= (j2-1)*nlstate+i2;
6608: if(cptj2 <= cptj)
6609: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6610: }
1.126 brouard 6611: }
6612: fprintf(ficrescveij,"\n");
1.218 brouard 6613:
1.126 brouard 6614: }
6615: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6616: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6617: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6618: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6619: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6620: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6621: printf("\n");
6622: fprintf(ficlog,"\n");
1.218 brouard 6623:
1.126 brouard 6624: free_vector(xm,1,npar);
6625: free_vector(xp,1,npar);
6626: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6627: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6628: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6629: }
1.218 brouard 6630:
1.126 brouard 6631: /************ Variance ******************/
1.235 brouard 6632: 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 6633: {
1.279 brouard 6634: /** Variance of health expectancies
6635: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6636: * double **newm;
6637: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6638: */
1.218 brouard 6639:
6640: /* int movingaverage(); */
6641: double **dnewm,**doldm;
6642: double **dnewmp,**doldmp;
6643: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6644: int first=0;
1.218 brouard 6645: int k;
6646: double *xp;
1.279 brouard 6647: double **gp, **gm; /**< for var eij */
6648: double ***gradg, ***trgradg; /**< for var eij */
6649: double **gradgp, **trgradgp; /**< for var p point j */
6650: double *gpp, *gmp; /**< for var p point j */
6651: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6652: double ***p3mat;
6653: double age,agelim, hf;
6654: /* double ***mobaverage; */
6655: int theta;
6656: char digit[4];
6657: char digitp[25];
6658:
6659: char fileresprobmorprev[FILENAMELENGTH];
6660:
6661: if(popbased==1){
6662: if(mobilav!=0)
6663: strcpy(digitp,"-POPULBASED-MOBILAV_");
6664: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6665: }
6666: else
6667: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6668:
1.218 brouard 6669: /* if (mobilav!=0) { */
6670: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6671: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6672: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6673: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6674: /* } */
6675: /* } */
6676:
6677: strcpy(fileresprobmorprev,"PRMORPREV-");
6678: sprintf(digit,"%-d",ij);
6679: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6680: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6681: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6682: strcat(fileresprobmorprev,fileresu);
6683: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6684: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6685: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6686: }
6687: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6688: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6689: pstamp(ficresprobmorprev);
6690: 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 6691: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 6692:
6693: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
6694: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
6695: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
6696: /* } */
6697: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
6698: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 6699: }
1.337 brouard 6700: /* for(j=1;j<=cptcoveff;j++) */
6701: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 6702: fprintf(ficresprobmorprev,"\n");
6703:
1.218 brouard 6704: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6705: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6706: fprintf(ficresprobmorprev," p.%-d SE",j);
6707: for(i=1; i<=nlstate;i++)
6708: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6709: }
6710: fprintf(ficresprobmorprev,"\n");
6711:
6712: fprintf(ficgp,"\n# Routine varevsij");
6713: fprintf(ficgp,"\nunset title \n");
6714: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6715: 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");
6716: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6717:
1.218 brouard 6718: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6719: pstamp(ficresvij);
6720: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6721: if(popbased==1)
6722: 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);
6723: else
6724: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6725: fprintf(ficresvij,"# Age");
6726: for(i=1; i<=nlstate;i++)
6727: for(j=1; j<=nlstate;j++)
6728: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6729: fprintf(ficresvij,"\n");
6730:
6731: xp=vector(1,npar);
6732: dnewm=matrix(1,nlstate,1,npar);
6733: doldm=matrix(1,nlstate,1,nlstate);
6734: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6735: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6736:
6737: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6738: gpp=vector(nlstate+1,nlstate+ndeath);
6739: gmp=vector(nlstate+1,nlstate+ndeath);
6740: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6741:
1.218 brouard 6742: if(estepm < stepm){
6743: printf ("Problem %d lower than %d\n",estepm, stepm);
6744: }
6745: else hstepm=estepm;
6746: /* For example we decided to compute the life expectancy with the smallest unit */
6747: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6748: nhstepm is the number of hstepm from age to agelim
6749: nstepm is the number of stepm from age to agelim.
6750: Look at function hpijx to understand why because of memory size limitations,
6751: we decided (b) to get a life expectancy respecting the most precise curvature of the
6752: survival function given by stepm (the optimization length). Unfortunately it
6753: means that if the survival funtion is printed every two years of age and if
6754: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6755: results. So we changed our mind and took the option of the best precision.
6756: */
6757: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6758: agelim = AGESUP;
6759: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6760: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6761: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6762: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6763: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6764: gp=matrix(0,nhstepm,1,nlstate);
6765: gm=matrix(0,nhstepm,1,nlstate);
6766:
6767:
6768: for(theta=1; theta <=npar; theta++){
6769: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6770: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6771: }
1.279 brouard 6772: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6773: * returns into prlim .
1.288 brouard 6774: */
1.242 brouard 6775: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6776:
6777: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6778: if (popbased==1) {
6779: if(mobilav ==0){
6780: for(i=1; i<=nlstate;i++)
6781: prlim[i][i]=probs[(int)age][i][ij];
6782: }else{ /* mobilav */
6783: for(i=1; i<=nlstate;i++)
6784: prlim[i][i]=mobaverage[(int)age][i][ij];
6785: }
6786: }
1.295 brouard 6787: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6788: */
6789: 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 6790: /**< 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 6791: * at horizon h in state j including mortality.
6792: */
1.218 brouard 6793: for(j=1; j<= nlstate; j++){
6794: for(h=0; h<=nhstepm; h++){
6795: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6796: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6797: }
6798: }
1.279 brouard 6799: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6800: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6801: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6802: */
6803: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6804: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6805: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6806: }
6807:
6808: /* Again with minus shift */
1.218 brouard 6809:
6810: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6811: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6812:
1.242 brouard 6813: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6814:
6815: if (popbased==1) {
6816: if(mobilav ==0){
6817: for(i=1; i<=nlstate;i++)
6818: prlim[i][i]=probs[(int)age][i][ij];
6819: }else{ /* mobilav */
6820: for(i=1; i<=nlstate;i++)
6821: prlim[i][i]=mobaverage[(int)age][i][ij];
6822: }
6823: }
6824:
1.235 brouard 6825: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6826:
6827: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6828: for(h=0; h<=nhstepm; h++){
6829: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6830: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6831: }
6832: }
6833: /* This for computing probability of death (h=1 means
6834: computed over hstepm matrices product = hstepm*stepm months)
6835: as a weighted average of prlim.
6836: */
6837: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6838: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6839: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6840: }
1.279 brouard 6841: /* end shifting computations */
6842:
6843: /**< Computing gradient matrix at horizon h
6844: */
1.218 brouard 6845: for(j=1; j<= nlstate; j++) /* vareij */
6846: for(h=0; h<=nhstepm; h++){
6847: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6848: }
1.279 brouard 6849: /**< Gradient of overall mortality p.3 (or p.j)
6850: */
6851: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6852: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6853: }
6854:
6855: } /* End theta */
1.279 brouard 6856:
6857: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6858: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6859:
6860: for(h=0; h<=nhstepm; h++) /* veij */
6861: for(j=1; j<=nlstate;j++)
6862: for(theta=1; theta <=npar; theta++)
6863: trgradg[h][j][theta]=gradg[h][theta][j];
6864:
6865: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6866: for(theta=1; theta <=npar; theta++)
6867: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6868: /**< as well as its transposed matrix
6869: */
1.218 brouard 6870:
6871: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6872: for(i=1;i<=nlstate;i++)
6873: for(j=1;j<=nlstate;j++)
6874: vareij[i][j][(int)age] =0.;
1.279 brouard 6875:
6876: /* Computing trgradg by matcov by gradg at age and summing over h
6877: * and k (nhstepm) formula 15 of article
6878: * Lievre-Brouard-Heathcote
6879: */
6880:
1.218 brouard 6881: for(h=0;h<=nhstepm;h++){
6882: for(k=0;k<=nhstepm;k++){
6883: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6884: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6885: for(i=1;i<=nlstate;i++)
6886: for(j=1;j<=nlstate;j++)
6887: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6888: }
6889: }
6890:
1.279 brouard 6891: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6892: * p.j overall mortality formula 49 but computed directly because
6893: * we compute the grad (wix pijx) instead of grad (pijx),even if
6894: * wix is independent of theta.
6895: */
1.218 brouard 6896: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6897: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6898: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6899: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6900: varppt[j][i]=doldmp[j][i];
6901: /* end ppptj */
6902: /* x centered again */
6903:
1.242 brouard 6904: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6905:
6906: if (popbased==1) {
6907: if(mobilav ==0){
6908: for(i=1; i<=nlstate;i++)
6909: prlim[i][i]=probs[(int)age][i][ij];
6910: }else{ /* mobilav */
6911: for(i=1; i<=nlstate;i++)
6912: prlim[i][i]=mobaverage[(int)age][i][ij];
6913: }
6914: }
6915:
6916: /* This for computing probability of death (h=1 means
6917: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6918: as a weighted average of prlim.
6919: */
1.235 brouard 6920: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6921: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6922: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6923: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6924: }
6925: /* end probability of death */
6926:
6927: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6928: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6929: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6930: for(i=1; i<=nlstate;i++){
6931: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6932: }
6933: }
6934: fprintf(ficresprobmorprev,"\n");
6935:
6936: fprintf(ficresvij,"%.0f ",age );
6937: for(i=1; i<=nlstate;i++)
6938: for(j=1; j<=nlstate;j++){
6939: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6940: }
6941: fprintf(ficresvij,"\n");
6942: free_matrix(gp,0,nhstepm,1,nlstate);
6943: free_matrix(gm,0,nhstepm,1,nlstate);
6944: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6945: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6946: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6947: } /* End age */
6948: free_vector(gpp,nlstate+1,nlstate+ndeath);
6949: free_vector(gmp,nlstate+1,nlstate+ndeath);
6950: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6951: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6952: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6953: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6954: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6955: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6956: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6957: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6958: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6959: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6960: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6961: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6962: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6963: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6964: 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);
6965: /* 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 6966: */
1.218 brouard 6967: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6968: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6969:
1.218 brouard 6970: free_vector(xp,1,npar);
6971: free_matrix(doldm,1,nlstate,1,nlstate);
6972: free_matrix(dnewm,1,nlstate,1,npar);
6973: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6974: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6975: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6976: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6977: fclose(ficresprobmorprev);
6978: fflush(ficgp);
6979: fflush(fichtm);
6980: } /* end varevsij */
1.126 brouard 6981:
6982: /************ Variance of prevlim ******************/
1.269 brouard 6983: 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 6984: {
1.205 brouard 6985: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6986: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6987:
1.268 brouard 6988: double **dnewmpar,**doldm;
1.126 brouard 6989: int i, j, nhstepm, hstepm;
6990: double *xp;
6991: double *gp, *gm;
6992: double **gradg, **trgradg;
1.208 brouard 6993: double **mgm, **mgp;
1.126 brouard 6994: double age,agelim;
6995: int theta;
6996:
6997: pstamp(ficresvpl);
1.288 brouard 6998: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6999: fprintf(ficresvpl,"# Age ");
7000: if(nresult >=1)
7001: fprintf(ficresvpl," Result# ");
1.126 brouard 7002: for(i=1; i<=nlstate;i++)
7003: fprintf(ficresvpl," %1d-%1d",i,i);
7004: fprintf(ficresvpl,"\n");
7005:
7006: xp=vector(1,npar);
1.268 brouard 7007: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7008: doldm=matrix(1,nlstate,1,nlstate);
7009:
7010: hstepm=1*YEARM; /* Every year of age */
7011: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7012: agelim = AGESUP;
7013: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7014: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7015: if (stepm >= YEARM) hstepm=1;
7016: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7017: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7018: mgp=matrix(1,npar,1,nlstate);
7019: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7020: gp=vector(1,nlstate);
7021: gm=vector(1,nlstate);
7022:
7023: for(theta=1; theta <=npar; theta++){
7024: for(i=1; i<=npar; i++){ /* Computes gradient */
7025: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7026: }
1.288 brouard 7027: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7028: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7029: /* else */
7030: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7031: for(i=1;i<=nlstate;i++){
1.126 brouard 7032: gp[i] = prlim[i][i];
1.208 brouard 7033: mgp[theta][i] = prlim[i][i];
7034: }
1.126 brouard 7035: for(i=1; i<=npar; i++) /* Computes gradient */
7036: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7037: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7038: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7039: /* else */
7040: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7041: for(i=1;i<=nlstate;i++){
1.126 brouard 7042: gm[i] = prlim[i][i];
1.208 brouard 7043: mgm[theta][i] = prlim[i][i];
7044: }
1.126 brouard 7045: for(i=1;i<=nlstate;i++)
7046: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7047: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7048: } /* End theta */
7049:
7050: trgradg =matrix(1,nlstate,1,npar);
7051:
7052: for(j=1; j<=nlstate;j++)
7053: for(theta=1; theta <=npar; theta++)
7054: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7055: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7056: /* printf("\nmgm mgp %d ",(int)age); */
7057: /* for(j=1; j<=nlstate;j++){ */
7058: /* printf(" %d ",j); */
7059: /* for(theta=1; theta <=npar; theta++) */
7060: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7061: /* printf("\n "); */
7062: /* } */
7063: /* } */
7064: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7065: /* printf("\n gradg %d ",(int)age); */
7066: /* for(j=1; j<=nlstate;j++){ */
7067: /* printf("%d ",j); */
7068: /* for(theta=1; theta <=npar; theta++) */
7069: /* printf("%d %lf ",theta,gradg[theta][j]); */
7070: /* printf("\n "); */
7071: /* } */
7072: /* } */
1.126 brouard 7073:
7074: for(i=1;i<=nlstate;i++)
7075: varpl[i][(int)age] =0.;
1.209 brouard 7076: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7077: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7078: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7079: }else{
1.268 brouard 7080: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7081: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7082: }
1.126 brouard 7083: for(i=1;i<=nlstate;i++)
7084: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7085:
7086: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7087: if(nresult >=1)
7088: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7089: for(i=1; i<=nlstate;i++){
1.126 brouard 7090: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7091: /* for(j=1;j<=nlstate;j++) */
7092: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7093: }
1.126 brouard 7094: fprintf(ficresvpl,"\n");
7095: free_vector(gp,1,nlstate);
7096: free_vector(gm,1,nlstate);
1.208 brouard 7097: free_matrix(mgm,1,npar,1,nlstate);
7098: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7099: free_matrix(gradg,1,npar,1,nlstate);
7100: free_matrix(trgradg,1,nlstate,1,npar);
7101: } /* End age */
7102:
7103: free_vector(xp,1,npar);
7104: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7105: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7106:
7107: }
7108:
7109:
7110: /************ Variance of backprevalence limit ******************/
1.269 brouard 7111: 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 7112: {
7113: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7114: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7115:
7116: double **dnewmpar,**doldm;
7117: int i, j, nhstepm, hstepm;
7118: double *xp;
7119: double *gp, *gm;
7120: double **gradg, **trgradg;
7121: double **mgm, **mgp;
7122: double age,agelim;
7123: int theta;
7124:
7125: pstamp(ficresvbl);
7126: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7127: fprintf(ficresvbl,"# Age ");
7128: if(nresult >=1)
7129: fprintf(ficresvbl," Result# ");
7130: for(i=1; i<=nlstate;i++)
7131: fprintf(ficresvbl," %1d-%1d",i,i);
7132: fprintf(ficresvbl,"\n");
7133:
7134: xp=vector(1,npar);
7135: dnewmpar=matrix(1,nlstate,1,npar);
7136: doldm=matrix(1,nlstate,1,nlstate);
7137:
7138: hstepm=1*YEARM; /* Every year of age */
7139: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7140: agelim = AGEINF;
7141: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7142: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7143: if (stepm >= YEARM) hstepm=1;
7144: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7145: gradg=matrix(1,npar,1,nlstate);
7146: mgp=matrix(1,npar,1,nlstate);
7147: mgm=matrix(1,npar,1,nlstate);
7148: gp=vector(1,nlstate);
7149: gm=vector(1,nlstate);
7150:
7151: for(theta=1; theta <=npar; theta++){
7152: for(i=1; i<=npar; i++){ /* Computes gradient */
7153: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7154: }
7155: if(mobilavproj > 0 )
7156: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7157: else
7158: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7159: for(i=1;i<=nlstate;i++){
7160: gp[i] = bprlim[i][i];
7161: mgp[theta][i] = bprlim[i][i];
7162: }
7163: for(i=1; i<=npar; i++) /* Computes gradient */
7164: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7165: if(mobilavproj > 0 )
7166: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7167: else
7168: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7169: for(i=1;i<=nlstate;i++){
7170: gm[i] = bprlim[i][i];
7171: mgm[theta][i] = bprlim[i][i];
7172: }
7173: for(i=1;i<=nlstate;i++)
7174: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7175: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7176: } /* End theta */
7177:
7178: trgradg =matrix(1,nlstate,1,npar);
7179:
7180: for(j=1; j<=nlstate;j++)
7181: for(theta=1; theta <=npar; theta++)
7182: trgradg[j][theta]=gradg[theta][j];
7183: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7184: /* printf("\nmgm mgp %d ",(int)age); */
7185: /* for(j=1; j<=nlstate;j++){ */
7186: /* printf(" %d ",j); */
7187: /* for(theta=1; theta <=npar; theta++) */
7188: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7189: /* printf("\n "); */
7190: /* } */
7191: /* } */
7192: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7193: /* printf("\n gradg %d ",(int)age); */
7194: /* for(j=1; j<=nlstate;j++){ */
7195: /* printf("%d ",j); */
7196: /* for(theta=1; theta <=npar; theta++) */
7197: /* printf("%d %lf ",theta,gradg[theta][j]); */
7198: /* printf("\n "); */
7199: /* } */
7200: /* } */
7201:
7202: for(i=1;i<=nlstate;i++)
7203: varbpl[i][(int)age] =0.;
7204: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7205: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7206: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7207: }else{
7208: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7209: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7210: }
7211: for(i=1;i<=nlstate;i++)
7212: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7213:
7214: fprintf(ficresvbl,"%.0f ",age );
7215: if(nresult >=1)
7216: fprintf(ficresvbl,"%d ",nres );
7217: for(i=1; i<=nlstate;i++)
7218: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7219: fprintf(ficresvbl,"\n");
7220: free_vector(gp,1,nlstate);
7221: free_vector(gm,1,nlstate);
7222: free_matrix(mgm,1,npar,1,nlstate);
7223: free_matrix(mgp,1,npar,1,nlstate);
7224: free_matrix(gradg,1,npar,1,nlstate);
7225: free_matrix(trgradg,1,nlstate,1,npar);
7226: } /* End age */
7227:
7228: free_vector(xp,1,npar);
7229: free_matrix(doldm,1,nlstate,1,npar);
7230: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7231:
7232: }
7233:
7234: /************ Variance of one-step probabilities ******************/
7235: 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 7236: {
7237: int i, j=0, k1, l1, tj;
7238: int k2, l2, j1, z1;
7239: int k=0, l;
7240: int first=1, first1, first2;
1.326 brouard 7241: int nres=0; /* New */
1.222 brouard 7242: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7243: double **dnewm,**doldm;
7244: double *xp;
7245: double *gp, *gm;
7246: double **gradg, **trgradg;
7247: double **mu;
7248: double age, cov[NCOVMAX+1];
7249: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7250: int theta;
7251: char fileresprob[FILENAMELENGTH];
7252: char fileresprobcov[FILENAMELENGTH];
7253: char fileresprobcor[FILENAMELENGTH];
7254: double ***varpij;
7255:
7256: strcpy(fileresprob,"PROB_");
7257: strcat(fileresprob,fileres);
7258: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7259: printf("Problem with resultfile: %s\n", fileresprob);
7260: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7261: }
7262: strcpy(fileresprobcov,"PROBCOV_");
7263: strcat(fileresprobcov,fileresu);
7264: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7265: printf("Problem with resultfile: %s\n", fileresprobcov);
7266: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7267: }
7268: strcpy(fileresprobcor,"PROBCOR_");
7269: strcat(fileresprobcor,fileresu);
7270: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7271: printf("Problem with resultfile: %s\n", fileresprobcor);
7272: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7273: }
7274: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7275: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7276: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7277: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7278: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7279: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7280: pstamp(ficresprob);
7281: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7282: fprintf(ficresprob,"# Age");
7283: pstamp(ficresprobcov);
7284: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7285: fprintf(ficresprobcov,"# Age");
7286: pstamp(ficresprobcor);
7287: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7288: fprintf(ficresprobcor,"# Age");
1.126 brouard 7289:
7290:
1.222 brouard 7291: for(i=1; i<=nlstate;i++)
7292: for(j=1; j<=(nlstate+ndeath);j++){
7293: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7294: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7295: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7296: }
7297: /* fprintf(ficresprob,"\n");
7298: fprintf(ficresprobcov,"\n");
7299: fprintf(ficresprobcor,"\n");
7300: */
7301: xp=vector(1,npar);
7302: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7303: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7304: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7305: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7306: first=1;
7307: fprintf(ficgp,"\n# Routine varprob");
7308: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7309: fprintf(fichtm,"\n");
7310:
1.288 brouard 7311: 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 7312: 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);
7313: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7314: and drawn. It helps understanding how is the covariance between two incidences.\
7315: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7316: 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 7317: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7318: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7319: standard deviations wide on each axis. <br>\
7320: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7321: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7322: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7323:
1.222 brouard 7324: cov[1]=1;
7325: /* tj=cptcoveff; */
1.225 brouard 7326: tj = (int) pow(2,cptcoveff);
1.222 brouard 7327: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7328: j1=0;
1.332 brouard 7329:
7330: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7331: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.334 brouard 7332: 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 7333: if(tj != 1 && TKresult[nres]!= j1)
7334: continue;
7335:
7336: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7337: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7338: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7339: if (cptcovn>0) {
1.334 brouard 7340: fprintf(ficresprob, "\n#********** Variable ");
7341: fprintf(ficresprobcov, "\n#********** Variable ");
7342: fprintf(ficgp, "\n#********** Variable ");
7343: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7344: fprintf(ficresprobcor, "\n#********** Variable ");
7345:
7346: /* Including quantitative variables of the resultline to be done */
7347: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.338 brouard 7348: printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7349: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7350: /* 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 7351: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7352: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7353: 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 */
7354: 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 */
7355: 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 */
7356: 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 */
7357: 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 */
7358: fprintf(ficresprob,"fixed ");
7359: fprintf(ficresprobcov,"fixed ");
7360: fprintf(ficgp,"fixed ");
7361: fprintf(fichtmcov,"fixed ");
7362: fprintf(ficresprobcor,"fixed ");
7363: }else{
7364: fprintf(ficresprob,"varyi ");
7365: fprintf(ficresprobcov,"varyi ");
7366: fprintf(ficgp,"varyi ");
7367: fprintf(fichtmcov,"varyi ");
7368: fprintf(ficresprobcor,"varyi ");
7369: }
7370: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7371: /* For each selected (single) quantitative value */
1.337 brouard 7372: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7373: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7374: fprintf(ficresprob,"fixed ");
7375: fprintf(ficresprobcov,"fixed ");
7376: fprintf(ficgp,"fixed ");
7377: fprintf(fichtmcov,"fixed ");
7378: fprintf(ficresprobcor,"fixed ");
7379: }else{
7380: fprintf(ficresprob,"varyi ");
7381: fprintf(ficresprobcov,"varyi ");
7382: fprintf(ficgp,"varyi ");
7383: fprintf(fichtmcov,"varyi ");
7384: fprintf(ficresprobcor,"varyi ");
7385: }
7386: }else{
7387: 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 */
7388: 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 */
7389: exit(1);
7390: }
7391: } /* End loop on variable of this resultline */
7392: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7393: fprintf(ficresprob, "**********\n#\n");
7394: fprintf(ficresprobcov, "**********\n#\n");
7395: fprintf(ficgp, "**********\n#\n");
7396: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7397: fprintf(ficresprobcor, "**********\n#");
7398: if(invalidvarcomb[j1]){
7399: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7400: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7401: continue;
7402: }
7403: }
7404: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7405: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7406: gp=vector(1,(nlstate)*(nlstate+ndeath));
7407: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7408: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7409: cov[2]=age;
7410: if(nagesqr==1)
7411: cov[3]= age*age;
1.334 brouard 7412: /* New code end of combination but for each resultline */
7413: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
7414: if(Typevar[k1]==1){ /* A product with age */
7415: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7416: }else{
1.334 brouard 7417: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7418: }
1.334 brouard 7419: }/* End of loop on model equation */
7420: /* Old code */
7421: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7422: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7423: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7424: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7425: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7426: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7427: /* * 1 1 1 1 1 */
7428: /* * 2 2 1 1 1 */
7429: /* * 3 1 2 1 1 */
7430: /* *\/ */
7431: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7432: /* } */
7433: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7434: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7435: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7436: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7437: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7438: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7439: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7440: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7441: /* 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]); */
7442: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7443: /* /\* exit(1); *\/ */
7444: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7445: /* } */
7446: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7447: /* } */
7448: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7449: /* if(Dummy[Tvard[k][1]]==0){ */
7450: /* if(Dummy[Tvard[k][2]]==0){ */
7451: /* 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]])]; */
7452: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7453: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7454: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7455: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7456: /* } */
7457: /* }else{ */
7458: /* if(Dummy[Tvard[k][2]]==0){ */
7459: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7460: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7461: /* }else{ */
7462: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7463: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7464: /* } */
7465: /* } */
7466: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7467: /* } */
1.326 brouard 7468: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7469: for(theta=1; theta <=npar; theta++){
7470: for(i=1; i<=npar; i++)
7471: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7472:
1.222 brouard 7473: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7474:
1.222 brouard 7475: k=0;
7476: for(i=1; i<= (nlstate); i++){
7477: for(j=1; j<=(nlstate+ndeath);j++){
7478: k=k+1;
7479: gp[k]=pmmij[i][j];
7480: }
7481: }
1.220 brouard 7482:
1.222 brouard 7483: for(i=1; i<=npar; i++)
7484: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7485:
1.222 brouard 7486: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7487: k=0;
7488: for(i=1; i<=(nlstate); i++){
7489: for(j=1; j<=(nlstate+ndeath);j++){
7490: k=k+1;
7491: gm[k]=pmmij[i][j];
7492: }
7493: }
1.220 brouard 7494:
1.222 brouard 7495: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7496: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7497: }
1.126 brouard 7498:
1.222 brouard 7499: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7500: for(theta=1; theta <=npar; theta++)
7501: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7502:
1.222 brouard 7503: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7504: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7505:
1.222 brouard 7506: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7507:
1.222 brouard 7508: k=0;
7509: for(i=1; i<=(nlstate); i++){
7510: for(j=1; j<=(nlstate+ndeath);j++){
7511: k=k+1;
7512: mu[k][(int) age]=pmmij[i][j];
7513: }
7514: }
7515: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7516: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7517: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7518:
1.222 brouard 7519: /*printf("\n%d ",(int)age);
7520: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7521: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7522: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7523: }*/
1.220 brouard 7524:
1.222 brouard 7525: fprintf(ficresprob,"\n%d ",(int)age);
7526: fprintf(ficresprobcov,"\n%d ",(int)age);
7527: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7528:
1.222 brouard 7529: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7530: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7531: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7532: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7533: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7534: }
7535: i=0;
7536: for (k=1; k<=(nlstate);k++){
7537: for (l=1; l<=(nlstate+ndeath);l++){
7538: i++;
7539: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7540: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7541: for (j=1; j<=i;j++){
7542: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7543: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7544: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7545: }
7546: }
7547: }/* end of loop for state */
7548: } /* end of loop for age */
7549: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7550: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7551: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7552: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7553:
7554: /* Confidence intervalle of pij */
7555: /*
7556: fprintf(ficgp,"\nunset parametric;unset label");
7557: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7558: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7559: 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);
7560: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7561: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7562: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7563: */
7564:
7565: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7566: first1=1;first2=2;
7567: for (k2=1; k2<=(nlstate);k2++){
7568: for (l2=1; l2<=(nlstate+ndeath);l2++){
7569: if(l2==k2) continue;
7570: j=(k2-1)*(nlstate+ndeath)+l2;
7571: for (k1=1; k1<=(nlstate);k1++){
7572: for (l1=1; l1<=(nlstate+ndeath);l1++){
7573: if(l1==k1) continue;
7574: i=(k1-1)*(nlstate+ndeath)+l1;
7575: if(i<=j) continue;
7576: for (age=bage; age<=fage; age ++){
7577: if ((int)age %5==0){
7578: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7579: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7580: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7581: mu1=mu[i][(int) age]/stepm*YEARM ;
7582: mu2=mu[j][(int) age]/stepm*YEARM;
7583: c12=cv12/sqrt(v1*v2);
7584: /* Computing eigen value of matrix of covariance */
7585: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7586: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7587: if ((lc2 <0) || (lc1 <0) ){
7588: if(first2==1){
7589: first1=0;
7590: 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);
7591: }
7592: 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);
7593: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7594: /* lc2=fabs(lc2); */
7595: }
1.220 brouard 7596:
1.222 brouard 7597: /* Eigen vectors */
1.280 brouard 7598: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7599: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7600: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7601: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7602: }else
7603: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7604: /*v21=sqrt(1.-v11*v11); *//* error */
7605: v21=(lc1-v1)/cv12*v11;
7606: v12=-v21;
7607: v22=v11;
7608: tnalp=v21/v11;
7609: if(first1==1){
7610: first1=0;
7611: 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);
7612: }
7613: 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);
7614: /*printf(fignu*/
7615: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7616: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7617: if(first==1){
7618: first=0;
7619: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7620: fprintf(ficgp,"\nset parametric;unset label");
7621: 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);
7622: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7623: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7624: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7625: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7626: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7627: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7628: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7629: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7630: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7631: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7632: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7633: 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 7634: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7635: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7636: }else{
7637: first=0;
7638: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7639: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7640: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7641: 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 7642: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7643: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7644: }/* if first */
7645: } /* age mod 5 */
7646: } /* end loop age */
7647: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7648: first=1;
7649: } /*l12 */
7650: } /* k12 */
7651: } /*l1 */
7652: }/* k1 */
1.332 brouard 7653: } /* loop on combination of covariates j1 */
1.326 brouard 7654: } /* loop on nres */
1.222 brouard 7655: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7656: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7657: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7658: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7659: free_vector(xp,1,npar);
7660: fclose(ficresprob);
7661: fclose(ficresprobcov);
7662: fclose(ficresprobcor);
7663: fflush(ficgp);
7664: fflush(fichtmcov);
7665: }
1.126 brouard 7666:
7667:
7668: /******************* Printing html file ***********/
1.201 brouard 7669: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7670: int lastpass, int stepm, int weightopt, char model[],\
7671: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7672: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7673: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7674: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7675: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7676: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7677: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7678: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7679: </ul>");
1.319 brouard 7680: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7681: /* </ul>", model); */
1.214 brouard 7682: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7683: 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",
7684: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 7685: 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 7686: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7687: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7688: fprintf(fichtm,"\
7689: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7690: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7691: fprintf(fichtm,"\
1.217 brouard 7692: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7693: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7694: fprintf(fichtm,"\
1.288 brouard 7695: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7696: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7697: fprintf(fichtm,"\
1.288 brouard 7698: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7699: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7700: fprintf(fichtm,"\
1.211 brouard 7701: - (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 7702: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7703: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7704: if(prevfcast==1){
7705: fprintf(fichtm,"\
7706: - Prevalence projections by age and states: \
1.201 brouard 7707: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7708: }
1.126 brouard 7709:
7710:
1.225 brouard 7711: m=pow(2,cptcoveff);
1.222 brouard 7712: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7713:
1.317 brouard 7714: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7715:
7716: jj1=0;
7717:
7718: fprintf(fichtm," \n<ul>");
1.337 brouard 7719: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7720: /* k1=nres; */
1.338 brouard 7721: k1=TKresult[nres];
7722: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 7723: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7724: /* if(m != 1 && TKresult[nres]!= k1) */
7725: /* continue; */
1.264 brouard 7726: jj1++;
7727: if (cptcovn > 0) {
7728: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 7729: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
7730: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7731: }
1.337 brouard 7732: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7733: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7734: /* } */
7735: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7736: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7737: /* } */
1.264 brouard 7738: fprintf(fichtm,"\">");
7739:
7740: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7741: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7742: for (cpt=1; cpt<=cptcovs;cpt++){
7743: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7744: }
1.337 brouard 7745: /* fprintf(fichtm,"************ Results for covariates"); */
7746: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7747: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7748: /* } */
7749: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7750: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7751: /* } */
1.264 brouard 7752: if(invalidvarcomb[k1]){
7753: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7754: continue;
7755: }
7756: fprintf(fichtm,"</a></li>");
7757: } /* cptcovn >0 */
7758: }
1.317 brouard 7759: fprintf(fichtm," \n</ul>");
1.264 brouard 7760:
1.222 brouard 7761: jj1=0;
1.237 brouard 7762:
1.337 brouard 7763: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7764: /* k1=nres; */
1.338 brouard 7765: k1=TKresult[nres];
7766: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7767: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7768: /* if(m != 1 && TKresult[nres]!= k1) */
7769: /* continue; */
1.220 brouard 7770:
1.222 brouard 7771: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7772: jj1++;
7773: if (cptcovn > 0) {
1.264 brouard 7774: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 7775: for (cpt=1; cpt<=cptcovs;cpt++){
7776: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7777: }
1.337 brouard 7778: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7779: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7780: /* } */
1.264 brouard 7781: fprintf(fichtm,"\"</a>");
7782:
1.222 brouard 7783: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7784: for (cpt=1; cpt<=cptcovs;cpt++){
7785: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7786: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7787: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7788: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7789: }
1.230 brouard 7790: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 7791: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7792: if(invalidvarcomb[k1]){
7793: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7794: printf("\nCombination (%d) ignored because no cases \n",k1);
7795: continue;
7796: }
7797: }
7798: /* aij, bij */
1.259 brouard 7799: 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 7800: <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 7801: /* Pij */
1.241 brouard 7802: 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> \
7803: <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 7804: /* Quasi-incidences */
7805: 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 7806: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7807: 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 7808: 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> \
7809: <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 7810: /* Survival functions (period) in state j */
7811: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7812: 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);
7813: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7814: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7815: }
7816: /* State specific survival functions (period) */
7817: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7818: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7819: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 7820: <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);
7821: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7822: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7823: }
1.288 brouard 7824: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7825: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7826: 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 7827: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 7828: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7829: }
1.296 brouard 7830: if(prevbcast==1){
1.288 brouard 7831: /* Backward prevalence in each health state */
1.222 brouard 7832: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 7833: 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);
7834: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
7835: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 7836: }
1.217 brouard 7837: }
1.222 brouard 7838: if(prevfcast==1){
1.288 brouard 7839: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7840: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7841: 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);
7842: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7843: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7844: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7845: }
7846: }
1.296 brouard 7847: if(prevbcast==1){
1.268 brouard 7848: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7849: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7850: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7851: 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 \
7852: 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 7853: 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);
7854: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7855: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7856: }
7857: }
1.220 brouard 7858:
1.222 brouard 7859: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7860: 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);
7861: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7862: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7863: }
7864: /* } /\* end i1 *\/ */
1.337 brouard 7865: }/* End k1=nres */
1.222 brouard 7866: fprintf(fichtm,"</ul>");
1.126 brouard 7867:
1.222 brouard 7868: fprintf(fichtm,"\
1.126 brouard 7869: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7870: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7871: - 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 7872: But because parameters are usually highly correlated (a higher incidence of disability \
7873: and a higher incidence of recovery can give very close observed transition) it might \
7874: be very useful to look not only at linear confidence intervals estimated from the \
7875: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7876: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7877: covariance matrix of the one-step probabilities. \
7878: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7879:
1.222 brouard 7880: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7881: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7882: fprintf(fichtm,"\
1.126 brouard 7883: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7884: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7885:
1.222 brouard 7886: fprintf(fichtm,"\
1.126 brouard 7887: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7888: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7889: fprintf(fichtm,"\
1.126 brouard 7890: - 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): \
7891: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7892: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7893: fprintf(fichtm,"\
1.126 brouard 7894: - (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): \
7895: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7896: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7897: fprintf(fichtm,"\
1.288 brouard 7898: - 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 7899: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7900: fprintf(fichtm,"\
1.128 brouard 7901: - 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 7902: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7903: fprintf(fichtm,"\
1.288 brouard 7904: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7905: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7906:
7907: /* if(popforecast==1) fprintf(fichtm,"\n */
7908: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7909: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7910: /* <br>",fileres,fileres,fileres,fileres); */
7911: /* else */
1.338 brouard 7912: /* 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 7913: fflush(fichtm);
1.126 brouard 7914:
1.225 brouard 7915: m=pow(2,cptcoveff);
1.222 brouard 7916: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7917:
1.317 brouard 7918: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7919:
7920: jj1=0;
7921:
7922: fprintf(fichtm," \n<ul>");
1.337 brouard 7923: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7924: /* k1=nres; */
1.338 brouard 7925: k1=TKresult[nres];
1.337 brouard 7926: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7927: /* if(m != 1 && TKresult[nres]!= k1) */
7928: /* continue; */
1.317 brouard 7929: jj1++;
7930: if (cptcovn > 0) {
7931: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 7932: for (cpt=1; cpt<=cptcovs;cpt++){
7933: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7934: }
7935: fprintf(fichtm,"\">");
7936:
7937: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7938: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7939: for (cpt=1; cpt<=cptcovs;cpt++){
7940: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7941: }
7942: if(invalidvarcomb[k1]){
7943: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7944: continue;
7945: }
7946: fprintf(fichtm,"</a></li>");
7947: } /* cptcovn >0 */
1.337 brouard 7948: } /* End nres */
1.317 brouard 7949: fprintf(fichtm," \n</ul>");
7950:
1.222 brouard 7951: jj1=0;
1.237 brouard 7952:
1.241 brouard 7953: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 7954: /* k1=nres; */
1.338 brouard 7955: k1=TKresult[nres];
7956: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7957: /* for(k1=1; k1<=m;k1++){ */
7958: /* if(m != 1 && TKresult[nres]!= k1) */
7959: /* continue; */
1.222 brouard 7960: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7961: jj1++;
1.126 brouard 7962: if (cptcovn > 0) {
1.317 brouard 7963: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 7964: for (cpt=1; cpt<=cptcovs;cpt++){
7965: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7966: }
7967: fprintf(fichtm,"\"</a>");
7968:
1.126 brouard 7969: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7970: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
7971: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7972: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7973: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7974: }
1.237 brouard 7975:
1.338 brouard 7976: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7977:
1.222 brouard 7978: if(invalidvarcomb[k1]){
7979: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7980: continue;
7981: }
1.337 brouard 7982: } /* If cptcovn >0 */
1.126 brouard 7983: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7984: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7985: 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);
7986: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7987: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7988: }
7989: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7990: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7991: true period expectancies (those weighted with period prevalences are also\
7992: drawn in addition to the population based expectancies computed using\
1.314 brouard 7993: 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);
7994: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7995: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7996: /* } /\* end i1 *\/ */
1.241 brouard 7997: }/* End nres */
1.222 brouard 7998: fprintf(fichtm,"</ul>");
7999: fflush(fichtm);
1.126 brouard 8000: }
8001:
8002: /******************* Gnuplot file **************/
1.296 brouard 8003: 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 8004:
8005: char dirfileres[132],optfileres[132];
1.264 brouard 8006: char gplotcondition[132], gplotlabel[132];
1.237 brouard 8007: int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,ij=0, ijp=0, l=0;
1.211 brouard 8008: int lv=0, vlv=0, kl=0;
1.130 brouard 8009: int ng=0;
1.201 brouard 8010: int vpopbased;
1.223 brouard 8011: int ioffset; /* variable offset for columns */
1.270 brouard 8012: int iyearc=1; /* variable column for year of projection */
8013: int iagec=1; /* variable column for age of projection */
1.235 brouard 8014: int nres=0; /* Index of resultline */
1.266 brouard 8015: int istart=1; /* For starting graphs in projections */
1.219 brouard 8016:
1.126 brouard 8017: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8018: /* printf("Problem with file %s",optionfilegnuplot); */
8019: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8020: /* } */
8021:
8022: /*#ifdef windows */
8023: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8024: /*#endif */
1.225 brouard 8025: m=pow(2,cptcoveff);
1.126 brouard 8026:
1.274 brouard 8027: /* diagram of the model */
8028: fprintf(ficgp,"\n#Diagram of the model \n");
8029: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8030: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8031: 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);
8032:
8033: fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=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);
8034: fprintf(ficgp,"\n#show arrow\nunset label\n");
8035: 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);
8036: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8037: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8038: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8039: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8040:
1.202 brouard 8041: /* Contribution to likelihood */
8042: /* Plot the probability implied in the likelihood */
1.223 brouard 8043: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8044: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8045: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8046: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8047: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8048: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8049: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8050: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8051: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8052: 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));
8053: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8054: 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));
8055: for (i=1; i<= nlstate ; i ++) {
8056: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8057: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8058: 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);
8059: for (j=2; j<= nlstate+ndeath ; j ++) {
8060: 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);
8061: }
8062: fprintf(ficgp,";\nset out; unset ylabel;\n");
8063: }
8064: /* 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 */
8065: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8066: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8067: fprintf(ficgp,"\nset out;unset log\n");
8068: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8069:
1.126 brouard 8070: strcpy(dirfileres,optionfilefiname);
8071: strcpy(optfileres,"vpl");
1.223 brouard 8072: /* 1eme*/
1.238 brouard 8073: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8074: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8075: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8076: k1=TKresult[nres];
1.338 brouard 8077: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8078: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8079: /* if(m != 1 && TKresult[nres]!= k1) */
8080: /* continue; */
1.238 brouard 8081: /* We are interested in selected combination by the resultline */
1.246 brouard 8082: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8083: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8084: strcpy(gplotlabel,"(");
1.337 brouard 8085: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8086: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8087: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8088:
8089: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8090: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8091: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8092: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8093: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8094: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8095: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8096: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8097: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8098: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8099: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8100: /* } */
8101: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8102: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8103: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8104: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8105: }
8106: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8107: /* printf("\n#\n"); */
1.238 brouard 8108: fprintf(ficgp,"\n#\n");
8109: if(invalidvarcomb[k1]){
1.260 brouard 8110: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8111: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8112: continue;
8113: }
1.235 brouard 8114:
1.241 brouard 8115: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8116: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8117: /* 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 8118: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8119: 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);
8120: /* 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); */
8121: /* k1-1 error should be nres-1*/
1.238 brouard 8122: for (i=1; i<= nlstate ; i ++) {
8123: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8124: else fprintf(ficgp," %%*lf (%%*lf)");
8125: }
1.288 brouard 8126: 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 8127: for (i=1; i<= nlstate ; i ++) {
8128: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8129: else fprintf(ficgp," %%*lf (%%*lf)");
8130: }
1.260 brouard 8131: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8132: for (i=1; i<= nlstate ; i ++) {
8133: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8134: else fprintf(ficgp," %%*lf (%%*lf)");
8135: }
1.265 brouard 8136: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8137:
8138: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8139: if(cptcoveff ==0){
1.271 brouard 8140: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8141: }else{
8142: kl=0;
8143: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8144: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8145: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8146: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8147: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8148: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8149: vlv= nbcode[Tvaraff[k]][lv];
8150: kl++;
8151: /* 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 *\/ */
8152: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8153: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8154: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8155: if(k==cptcoveff){
8156: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8157: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8158: }else{
8159: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8160: kl++;
8161: }
8162: } /* end covariate */
8163: } /* end if no covariate */
8164:
1.296 brouard 8165: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8166: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8167: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8168: if(cptcoveff ==0){
1.245 brouard 8169: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8170: }else{
8171: kl=0;
8172: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8173: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8174: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8175: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8176: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8177: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8178: /* vlv= nbcode[Tvaraff[k]][lv]; */
8179: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8180: kl++;
1.238 brouard 8181: /* 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 *\/ */
8182: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8183: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8184: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8185: if(k==cptcoveff){
1.245 brouard 8186: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8187: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8188: }else{
1.332 brouard 8189: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8190: kl++;
8191: }
8192: } /* end covariate */
8193: } /* end if no covariate */
1.296 brouard 8194: if(prevbcast == 1){
1.268 brouard 8195: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8196: /* k1-1 error should be nres-1*/
8197: for (i=1; i<= nlstate ; i ++) {
8198: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8199: else fprintf(ficgp," %%*lf (%%*lf)");
8200: }
1.271 brouard 8201: 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 8202: for (i=1; i<= nlstate ; i ++) {
8203: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8204: else fprintf(ficgp," %%*lf (%%*lf)");
8205: }
1.276 brouard 8206: 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 8207: for (i=1; i<= nlstate ; i ++) {
8208: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8209: else fprintf(ficgp," %%*lf (%%*lf)");
8210: }
1.274 brouard 8211: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8212: } /* end if backprojcast */
1.296 brouard 8213: } /* end if prevbcast */
1.276 brouard 8214: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8215: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8216: } /* nres */
1.337 brouard 8217: /* } /\* k1 *\/ */
1.201 brouard 8218: } /* cpt */
1.235 brouard 8219:
8220:
1.126 brouard 8221: /*2 eme*/
1.337 brouard 8222: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8223: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8224: k1=TKresult[nres];
1.338 brouard 8225: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8226: /* if(m != 1 && TKresult[nres]!= k1) */
8227: /* continue; */
1.238 brouard 8228: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8229: strcpy(gplotlabel,"(");
1.337 brouard 8230: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8231: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8232: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8233: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8234: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8235: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8236: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8237: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8238: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8239: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8240: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8241: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8242: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8243: /* } */
8244: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8245: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8246: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8247: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8248: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8249: }
1.264 brouard 8250: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8251: fprintf(ficgp,"\n#\n");
1.223 brouard 8252: if(invalidvarcomb[k1]){
8253: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8254: continue;
8255: }
1.219 brouard 8256:
1.241 brouard 8257: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8258: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8259: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8260: if(vpopbased==0){
1.238 brouard 8261: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8262: }else
1.238 brouard 8263: fprintf(ficgp,"\nreplot ");
8264: for (i=1; i<= nlstate+1 ; i ++) {
8265: k=2*i;
1.261 brouard 8266: 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 8267: for (j=1; j<= nlstate+1 ; j ++) {
8268: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8269: else fprintf(ficgp," %%*lf (%%*lf)");
8270: }
8271: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8272: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8273: 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 8274: for (j=1; j<= nlstate+1 ; j ++) {
8275: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8276: else fprintf(ficgp," %%*lf (%%*lf)");
8277: }
8278: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8279: 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 8280: for (j=1; j<= nlstate+1 ; j ++) {
8281: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8282: else fprintf(ficgp," %%*lf (%%*lf)");
8283: }
8284: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8285: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8286: } /* state */
8287: } /* vpopbased */
1.264 brouard 8288: 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 8289: } /* end nres */
1.337 brouard 8290: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8291:
8292:
8293: /*3eme*/
1.337 brouard 8294: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8295: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8296: k1=TKresult[nres];
1.338 brouard 8297: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8298: /* if(m != 1 && TKresult[nres]!= k1) */
8299: /* continue; */
1.238 brouard 8300:
1.332 brouard 8301: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8302: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8303: strcpy(gplotlabel,"(");
1.337 brouard 8304: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8305: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8306: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8307: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8308: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8309: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8310: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8311: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8312: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8313: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8314: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8315: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8316: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8317: /* } */
8318: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8319: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8320: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8321: }
1.264 brouard 8322: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8323: fprintf(ficgp,"\n#\n");
8324: if(invalidvarcomb[k1]){
8325: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8326: continue;
8327: }
8328:
8329: /* k=2+nlstate*(2*cpt-2); */
8330: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8331: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8332: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8333: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8334: 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 8335: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8336: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8337: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8338: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8339: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8340: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8341:
1.238 brouard 8342: */
8343: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8344: 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 8345: /* 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 8346:
1.238 brouard 8347: }
1.261 brouard 8348: 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 8349: }
1.264 brouard 8350: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8351: } /* end nres */
1.337 brouard 8352: /* } /\* end kl 3eme *\/ */
1.126 brouard 8353:
1.223 brouard 8354: /* 4eme */
1.201 brouard 8355: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8356: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8357: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8358: k1=TKresult[nres];
1.338 brouard 8359: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8360: /* if(m != 1 && TKresult[nres]!= k1) */
8361: /* continue; */
1.238 brouard 8362: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8363: strcpy(gplotlabel,"(");
1.337 brouard 8364: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8365: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8366: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8367: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8368: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8369: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8370: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8371: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8372: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8373: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8374: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8375: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8376: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8377: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8378: /* } */
8379: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8380: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8381: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8382: }
1.264 brouard 8383: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8384: fprintf(ficgp,"\n#\n");
8385: if(invalidvarcomb[k1]){
8386: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8387: continue;
1.223 brouard 8388: }
1.238 brouard 8389:
1.241 brouard 8390: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8391: 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 8392: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8393: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8394: k=3;
8395: for (i=1; i<= nlstate ; i ++){
8396: if(i==1){
8397: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8398: }else{
8399: fprintf(ficgp,", '' ");
8400: }
8401: l=(nlstate+ndeath)*(i-1)+1;
8402: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8403: for (j=2; j<= nlstate+ndeath ; j ++)
8404: fprintf(ficgp,"+$%d",k+l+j-1);
8405: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8406: } /* nlstate */
1.264 brouard 8407: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8408: } /* end cpt state*/
8409: } /* end nres */
1.337 brouard 8410: /* } /\* end covariate k1 *\/ */
1.238 brouard 8411:
1.220 brouard 8412: /* 5eme */
1.201 brouard 8413: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8414: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8415: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8416: k1=TKresult[nres];
1.338 brouard 8417: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8418: /* if(m != 1 && TKresult[nres]!= k1) */
8419: /* continue; */
1.238 brouard 8420: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8421: strcpy(gplotlabel,"(");
1.238 brouard 8422: 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 8423: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8424: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8425: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8426: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8427: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8428: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8429: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8430: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8431: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8432: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8433: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8434: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8435: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8436: /* } */
8437: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8438: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8439: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8440: }
1.264 brouard 8441: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8442: fprintf(ficgp,"\n#\n");
8443: if(invalidvarcomb[k1]){
8444: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8445: continue;
8446: }
1.227 brouard 8447:
1.241 brouard 8448: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8449: 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 8450: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8451: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8452: k=3;
8453: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8454: if(j==1)
8455: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8456: else
8457: fprintf(ficgp,", '' ");
8458: l=(nlstate+ndeath)*(cpt-1) +j;
8459: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8460: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8461: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8462: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8463: } /* nlstate */
8464: fprintf(ficgp,", '' ");
8465: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8466: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8467: l=(nlstate+ndeath)*(cpt-1) +j;
8468: if(j < nlstate)
8469: fprintf(ficgp,"$%d +",k+l);
8470: else
8471: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8472: }
1.264 brouard 8473: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8474: } /* end cpt state*/
1.337 brouard 8475: /* } /\* end covariate *\/ */
1.238 brouard 8476: } /* end nres */
1.227 brouard 8477:
1.220 brouard 8478: /* 6eme */
1.202 brouard 8479: /* CV preval stable (period) for each covariate */
1.337 brouard 8480: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8481: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8482: k1=TKresult[nres];
1.338 brouard 8483: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8484: /* if(m != 1 && TKresult[nres]!= k1) */
8485: /* continue; */
1.255 brouard 8486: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8487: strcpy(gplotlabel,"(");
1.288 brouard 8488: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8489: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8490: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8491: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8492: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8493: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8494: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8495: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8496: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8497: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8498: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8499: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8500: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8501: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8502: /* } */
8503: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8504: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8505: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8506: }
1.264 brouard 8507: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8508: fprintf(ficgp,"\n#\n");
1.223 brouard 8509: if(invalidvarcomb[k1]){
1.227 brouard 8510: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8511: continue;
1.223 brouard 8512: }
1.227 brouard 8513:
1.241 brouard 8514: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8515: 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 8516: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8517: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8518: k=3; /* Offset */
1.255 brouard 8519: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8520: if(i==1)
8521: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8522: else
8523: fprintf(ficgp,", '' ");
1.255 brouard 8524: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8525: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8526: for (j=2; j<= nlstate ; j ++)
8527: fprintf(ficgp,"+$%d",k+l+j-1);
8528: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8529: } /* nlstate */
1.264 brouard 8530: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8531: } /* end cpt state*/
8532: } /* end covariate */
1.227 brouard 8533:
8534:
1.220 brouard 8535: /* 7eme */
1.296 brouard 8536: if(prevbcast == 1){
1.288 brouard 8537: /* CV backward prevalence for each covariate */
1.337 brouard 8538: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8539: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8540: k1=TKresult[nres];
1.338 brouard 8541: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8542: /* if(m != 1 && TKresult[nres]!= k1) */
8543: /* continue; */
1.268 brouard 8544: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8545: strcpy(gplotlabel,"(");
1.288 brouard 8546: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8547: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8548: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8549: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8550: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8551: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8552: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8553: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8554: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8555: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8556: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8557: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8558: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8559: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8560: /* } */
8561: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8562: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8563: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8564: }
1.264 brouard 8565: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8566: fprintf(ficgp,"\n#\n");
8567: if(invalidvarcomb[k1]){
8568: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8569: continue;
8570: }
8571:
1.241 brouard 8572: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8573: 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 8574: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8575: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8576: k=3; /* Offset */
1.268 brouard 8577: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8578: if(i==1)
8579: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8580: else
8581: fprintf(ficgp,", '' ");
8582: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8583: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8584: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8585: /* 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 8586: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8587: /* for (j=2; j<= nlstate ; j ++) */
8588: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8589: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8590: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8591: } /* nlstate */
1.264 brouard 8592: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8593: } /* end cpt state*/
8594: } /* end covariate */
1.296 brouard 8595: } /* End if prevbcast */
1.218 brouard 8596:
1.223 brouard 8597: /* 8eme */
1.218 brouard 8598: if(prevfcast==1){
1.288 brouard 8599: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8600:
1.337 brouard 8601: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8602: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8603: k1=TKresult[nres];
1.338 brouard 8604: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8605: /* if(m != 1 && TKresult[nres]!= k1) */
8606: /* continue; */
1.211 brouard 8607: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8608: strcpy(gplotlabel,"(");
1.288 brouard 8609: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8610: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8611: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8612: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8613: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8614: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8615: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8616: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8617: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8618: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8619: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8620: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8621: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8622: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8623: /* } */
8624: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8625: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8626: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8627: }
1.264 brouard 8628: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8629: fprintf(ficgp,"\n#\n");
8630: if(invalidvarcomb[k1]){
8631: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8632: continue;
8633: }
8634:
8635: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8636: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8637: 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 8638: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8639: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8640:
8641: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8642: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8643: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8644: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8645: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8646: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8647: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8648: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8649: if(i==istart){
1.227 brouard 8650: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8651: }else{
8652: fprintf(ficgp,",\\\n '' ");
8653: }
8654: if(cptcoveff ==0){ /* No covariate */
8655: ioffset=2; /* Age is in 2 */
8656: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8657: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8658: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8659: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8660: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8661: if(i==nlstate+1){
1.270 brouard 8662: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8663: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8664: fprintf(ficgp,",\\\n '' ");
8665: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8666: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8667: offyear, \
1.268 brouard 8668: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8669: }else
1.227 brouard 8670: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8671: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8672: }else{ /* more than 2 covariates */
1.270 brouard 8673: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8674: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8675: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8676: iyearc=ioffset-1;
8677: iagec=ioffset;
1.227 brouard 8678: fprintf(ficgp," u %d:(",ioffset);
8679: kl=0;
8680: strcpy(gplotcondition,"(");
8681: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 8682: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8683: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8684: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8685: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8686: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8687: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8688: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8689: kl++;
8690: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8691: kl++;
8692: if(k <cptcoveff && cptcoveff>1)
8693: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8694: }
8695: strcpy(gplotcondition+strlen(gplotcondition),")");
8696: /* 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 *\/ */
8697: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8698: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8699: /* '' 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*/
8700: if(i==nlstate+1){
1.270 brouard 8701: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8702: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8703: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8704: fprintf(ficgp," u %d:(",iagec);
8705: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8706: iyearc, iagec, offyear, \
8707: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8708: /* '' 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 8709: }else{
8710: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8711: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8712: }
8713: } /* end if covariate */
8714: } /* nlstate */
1.264 brouard 8715: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8716: } /* end cpt state*/
8717: } /* end covariate */
8718: } /* End if prevfcast */
1.227 brouard 8719:
1.296 brouard 8720: if(prevbcast==1){
1.268 brouard 8721: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8722:
1.337 brouard 8723: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 8724: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8725: k1=TKresult[nres];
1.338 brouard 8726: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8727: /* if(m != 1 && TKresult[nres]!= k1) */
8728: /* continue; */
1.268 brouard 8729: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8730: strcpy(gplotlabel,"(");
8731: 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 8732: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8733: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8734: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8735: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8736: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8737: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8738: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8739: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8740: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8741: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8742: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8743: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8744: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8745: /* } */
8746: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8747: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8748: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 8749: }
8750: strcpy(gplotlabel+strlen(gplotlabel),")");
8751: fprintf(ficgp,"\n#\n");
8752: if(invalidvarcomb[k1]){
8753: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8754: continue;
8755: }
8756:
8757: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8758: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8759: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8760: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8761: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8762:
8763: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8764: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8765: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8766: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8767: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8768: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8769: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8770: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8771: if(i==istart){
8772: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8773: }else{
8774: fprintf(ficgp,",\\\n '' ");
8775: }
8776: if(cptcoveff ==0){ /* No covariate */
8777: ioffset=2; /* Age is in 2 */
8778: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8779: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8780: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8781: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8782: fprintf(ficgp," u %d:(", ioffset);
8783: if(i==nlstate+1){
1.270 brouard 8784: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8785: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8786: fprintf(ficgp,",\\\n '' ");
8787: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8788: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8789: offbyear, \
8790: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8791: }else
8792: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8793: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8794: }else{ /* more than 2 covariates */
1.270 brouard 8795: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8796: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8797: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8798: iyearc=ioffset-1;
8799: iagec=ioffset;
1.268 brouard 8800: fprintf(ficgp," u %d:(",ioffset);
8801: kl=0;
8802: strcpy(gplotcondition,"(");
1.337 brouard 8803: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 8804: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 8805: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
8806: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8807: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8808: lv=Tvresult[nres][k];
8809: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
8810: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8811: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8812: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8813: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8814: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8815: kl++;
8816: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
8817: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
8818: kl++;
1.338 brouard 8819: if(k <cptcovs && cptcovs>1)
1.337 brouard 8820: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8821: }
1.268 brouard 8822: }
8823: strcpy(gplotcondition+strlen(gplotcondition),")");
8824: /* 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 *\/ */
8825: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8826: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8827: /* '' 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*/
8828: if(i==nlstate+1){
1.270 brouard 8829: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8830: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8831: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8832: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8833: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8834: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8835: iyearc,iagec,offbyear, \
8836: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8837: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8838: }else{
8839: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8840: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8841: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8842: }
8843: } /* end if covariate */
8844: } /* nlstate */
8845: fprintf(ficgp,"\nset out; unset label;\n");
8846: } /* end cpt state*/
8847: } /* end covariate */
1.296 brouard 8848: } /* End if prevbcast */
1.268 brouard 8849:
1.227 brouard 8850:
1.238 brouard 8851: /* 9eme writing MLE parameters */
8852: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8853: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8854: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8855: for(k=1; k <=(nlstate+ndeath); k++){
8856: if (k != i) {
1.227 brouard 8857: fprintf(ficgp,"# current state %d\n",k);
8858: for(j=1; j <=ncovmodel; j++){
8859: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8860: jk++;
8861: }
8862: fprintf(ficgp,"\n");
1.126 brouard 8863: }
8864: }
1.223 brouard 8865: }
1.187 brouard 8866: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8867:
1.145 brouard 8868: /*goto avoid;*/
1.238 brouard 8869: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8870: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8871: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8872: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8873: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8874: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8875: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8876: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8877: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8878: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8879: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8880: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8881: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8882: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8883: fprintf(ficgp,"#\n");
1.223 brouard 8884: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8885: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 8886: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 8887: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8888: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
1.337 brouard 8889: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 8890: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8891: /* k1=nres; */
1.338 brouard 8892: k1=TKresult[nres];
8893: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8894: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 8895: strcpy(gplotlabel,"(");
1.276 brouard 8896: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 8897: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8898: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
8899: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
8900: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8901: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8902: }
8903: /* if(m != 1 && TKresult[nres]!= k1) */
8904: /* continue; */
8905: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
8906: /* strcpy(gplotlabel,"("); */
8907: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
8908: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8909: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8910: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8911: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8912: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8913: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8914: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8915: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8916: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8917: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8918: /* } */
8919: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8920: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8921: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8922: /* } */
1.264 brouard 8923: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8924: fprintf(ficgp,"\n#\n");
1.264 brouard 8925: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8926: fprintf(ficgp,"\nset key outside ");
8927: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8928: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8929: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8930: if (ng==1){
8931: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8932: fprintf(ficgp,"\nunset log y");
8933: }else if (ng==2){
8934: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8935: fprintf(ficgp,"\nset log y");
8936: }else if (ng==3){
8937: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8938: fprintf(ficgp,"\nset log y");
8939: }else
8940: fprintf(ficgp,"\nunset title ");
8941: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8942: i=1;
8943: for(k2=1; k2<=nlstate; k2++) {
8944: k3=i;
8945: for(k=1; k<=(nlstate+ndeath); k++) {
8946: if (k != k2){
8947: switch( ng) {
8948: case 1:
8949: if(nagesqr==0)
8950: fprintf(ficgp," p%d+p%d*x",i,i+1);
8951: else /* nagesqr =1 */
8952: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8953: break;
8954: case 2: /* ng=2 */
8955: if(nagesqr==0)
8956: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8957: else /* nagesqr =1 */
8958: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8959: break;
8960: case 3:
8961: if(nagesqr==0)
8962: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8963: else /* nagesqr =1 */
8964: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8965: break;
8966: }
8967: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8968: ijp=1; /* product no age */
8969: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8970: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8971: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 8972: switch(Typevar[j]){
8973: case 1:
8974: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8975: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
8976: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8977: if(DummyV[j]==0){/* Bug valgrind */
8978: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8979: }else{ /* quantitative */
8980: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8981: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8982: }
8983: ij++;
1.268 brouard 8984: }
1.237 brouard 8985: }
1.329 brouard 8986: }
8987: break;
8988: case 2:
8989: if(cptcovprod >0){
8990: if(j==Tprod[ijp]) { /* */
8991: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8992: if(ijp <=cptcovprod) { /* Product */
8993: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8994: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8995: /* 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)]); */
8996: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8997: }else{ /* Vn is dummy and Vm is quanti */
8998: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8999: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9000: }
9001: }else{ /* Vn*Vm Vn is quanti */
9002: if(DummyV[Tvard[ijp][2]]==0){
9003: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9004: }else{ /* Both quanti */
9005: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9006: }
1.268 brouard 9007: }
1.329 brouard 9008: ijp++;
1.237 brouard 9009: }
1.329 brouard 9010: } /* end Tprod */
9011: }
9012: break;
9013: case 0:
9014: /* simple covariate */
1.264 brouard 9015: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9016: if(Dummy[j]==0){
9017: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9018: }else{ /* quantitative */
9019: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9020: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9021: }
1.329 brouard 9022: /* end simple */
9023: break;
9024: default:
9025: break;
9026: } /* end switch */
1.237 brouard 9027: } /* end j */
1.329 brouard 9028: }else{ /* k=k2 */
9029: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9030: fprintf(ficgp," (1.");i=i-ncovmodel;
9031: }else
9032: i=i-ncovmodel;
1.223 brouard 9033: }
1.227 brouard 9034:
1.223 brouard 9035: if(ng != 1){
9036: fprintf(ficgp,")/(1");
1.227 brouard 9037:
1.264 brouard 9038: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9039: if(nagesqr==0)
1.264 brouard 9040: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9041: else /* nagesqr =1 */
1.264 brouard 9042: 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 9043:
1.223 brouard 9044: ij=1;
1.329 brouard 9045: ijp=1;
9046: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9047: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9048: switch(Typevar[j]){
9049: case 1:
9050: if(cptcovage >0){
9051: if(j==Tage[ij]) { /* Bug valgrind */
9052: if(ij <=cptcovage) { /* Bug valgrind */
9053: if(DummyV[j]==0){/* Bug valgrind */
9054: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9055: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9056: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9057: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9058: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9059: }else{ /* quantitative */
9060: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9061: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9062: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9063: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9064: }
9065: ij++;
9066: }
9067: }
9068: }
9069: break;
9070: case 2:
9071: if(cptcovprod >0){
9072: if(j==Tprod[ijp]) { /* */
9073: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9074: if(ijp <=cptcovprod) { /* Product */
9075: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9076: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9077: /* 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)]); */
9078: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9079: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9080: }else{ /* Vn is dummy and Vm is quanti */
9081: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9082: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9083: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9084: }
9085: }else{ /* Vn*Vm Vn is quanti */
9086: if(DummyV[Tvard[ijp][2]]==0){
9087: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9088: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9089: }else{ /* Both quanti */
9090: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9091: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9092: }
9093: }
9094: ijp++;
9095: }
9096: } /* end Tprod */
9097: } /* end if */
9098: break;
9099: case 0:
9100: /* simple covariate */
9101: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9102: if(Dummy[j]==0){
9103: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9104: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9105: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9106: }else{ /* quantitative */
9107: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9108: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9109: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9110: }
9111: /* end simple */
9112: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9113: break;
9114: default:
9115: break;
9116: } /* end switch */
1.223 brouard 9117: }
9118: fprintf(ficgp,")");
9119: }
9120: fprintf(ficgp,")");
9121: if(ng ==2)
1.276 brouard 9122: 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 9123: else /* ng= 3 */
1.276 brouard 9124: 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 9125: }else{ /* end ng <> 1 */
1.223 brouard 9126: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9127: 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 9128: }
9129: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9130: fprintf(ficgp,",");
9131: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9132: fprintf(ficgp,",");
9133: i=i+ncovmodel;
9134: } /* end k */
9135: } /* end k2 */
1.276 brouard 9136: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9137: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9138: } /* end resultline */
1.223 brouard 9139: } /* end ng */
9140: /* avoid: */
9141: fflush(ficgp);
1.126 brouard 9142: } /* end gnuplot */
9143:
9144:
9145: /*************** Moving average **************/
1.219 brouard 9146: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9147: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9148:
1.222 brouard 9149: int i, cpt, cptcod;
9150: int modcovmax =1;
9151: int mobilavrange, mob;
9152: int iage=0;
1.288 brouard 9153: int firstA1=0, firstA2=0;
1.222 brouard 9154:
1.266 brouard 9155: double sum=0., sumr=0.;
1.222 brouard 9156: double age;
1.266 brouard 9157: double *sumnewp, *sumnewm, *sumnewmr;
9158: double *agemingood, *agemaxgood;
9159: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9160:
9161:
1.278 brouard 9162: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9163: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9164:
9165: sumnewp = vector(1,ncovcombmax);
9166: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9167: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9168: agemingood = vector(1,ncovcombmax);
1.266 brouard 9169: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9170: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9171: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9172:
9173: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9174: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9175: sumnewp[cptcod]=0.;
1.266 brouard 9176: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9177: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9178: }
9179: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9180:
1.266 brouard 9181: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9182: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9183: else mobilavrange=mobilav;
9184: for (age=bage; age<=fage; age++)
9185: for (i=1; i<=nlstate;i++)
9186: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9187: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9188: /* We keep the original values on the extreme ages bage, fage and for
9189: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9190: we use a 5 terms etc. until the borders are no more concerned.
9191: */
9192: for (mob=3;mob <=mobilavrange;mob=mob+2){
9193: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9194: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9195: sumnewm[cptcod]=0.;
9196: for (i=1; i<=nlstate;i++){
1.222 brouard 9197: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9198: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9199: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9200: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9201: }
9202: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9203: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9204: } /* end i */
9205: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9206: } /* end cptcod */
1.222 brouard 9207: }/* end age */
9208: }/* end mob */
1.266 brouard 9209: }else{
9210: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9211: return -1;
1.266 brouard 9212: }
9213:
9214: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9215: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9216: if(invalidvarcomb[cptcod]){
9217: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9218: continue;
9219: }
1.219 brouard 9220:
1.266 brouard 9221: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9222: sumnewm[cptcod]=0.;
9223: sumnewmr[cptcod]=0.;
9224: for (i=1; i<=nlstate;i++){
9225: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9226: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9227: }
9228: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9229: agemingoodr[cptcod]=age;
9230: }
9231: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9232: agemingood[cptcod]=age;
9233: }
9234: } /* age */
9235: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9236: sumnewm[cptcod]=0.;
1.266 brouard 9237: sumnewmr[cptcod]=0.;
1.222 brouard 9238: for (i=1; i<=nlstate;i++){
9239: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9240: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9241: }
9242: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9243: agemaxgoodr[cptcod]=age;
1.222 brouard 9244: }
9245: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9246: agemaxgood[cptcod]=age;
9247: }
9248: } /* age */
9249: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9250: /* but they will change */
1.288 brouard 9251: firstA1=0;firstA2=0;
1.266 brouard 9252: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9253: sumnewm[cptcod]=0.;
9254: sumnewmr[cptcod]=0.;
9255: for (i=1; i<=nlstate;i++){
9256: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9257: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9258: }
9259: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9260: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9261: agemaxgoodr[cptcod]=age; /* age min */
9262: for (i=1; i<=nlstate;i++)
9263: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9264: }else{ /* bad we change the value with the values of good ages */
9265: for (i=1; i<=nlstate;i++){
9266: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9267: } /* i */
9268: } /* end bad */
9269: }else{
9270: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9271: agemaxgood[cptcod]=age;
9272: }else{ /* bad we change the value with the values of good ages */
9273: for (i=1; i<=nlstate;i++){
9274: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9275: } /* i */
9276: } /* end bad */
9277: }/* end else */
9278: sum=0.;sumr=0.;
9279: for (i=1; i<=nlstate;i++){
9280: sum+=mobaverage[(int)age][i][cptcod];
9281: sumr+=probs[(int)age][i][cptcod];
9282: }
9283: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9284: if(!firstA1){
9285: firstA1=1;
9286: 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);
9287: }
9288: 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 9289: } /* end bad */
9290: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9291: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9292: if(!firstA2){
9293: firstA2=1;
9294: 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);
9295: }
9296: 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 9297: } /* end bad */
9298: }/* age */
1.266 brouard 9299:
9300: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9301: sumnewm[cptcod]=0.;
1.266 brouard 9302: sumnewmr[cptcod]=0.;
1.222 brouard 9303: for (i=1; i<=nlstate;i++){
9304: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9305: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9306: }
9307: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9308: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9309: agemingoodr[cptcod]=age;
9310: for (i=1; i<=nlstate;i++)
9311: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9312: }else{ /* bad we change the value with the values of good ages */
9313: for (i=1; i<=nlstate;i++){
9314: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9315: } /* i */
9316: } /* end bad */
9317: }else{
9318: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9319: agemingood[cptcod]=age;
9320: }else{ /* bad */
9321: for (i=1; i<=nlstate;i++){
9322: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9323: } /* i */
9324: } /* end bad */
9325: }/* end else */
9326: sum=0.;sumr=0.;
9327: for (i=1; i<=nlstate;i++){
9328: sum+=mobaverage[(int)age][i][cptcod];
9329: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9330: }
1.266 brouard 9331: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9332: 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 9333: } /* end bad */
9334: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9335: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9336: 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 9337: } /* end bad */
9338: }/* age */
1.266 brouard 9339:
1.222 brouard 9340:
9341: for (age=bage; age<=fage; age++){
1.235 brouard 9342: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9343: sumnewp[cptcod]=0.;
9344: sumnewm[cptcod]=0.;
9345: for (i=1; i<=nlstate;i++){
9346: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9347: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9348: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9349: }
9350: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9351: }
9352: /* printf("\n"); */
9353: /* } */
1.266 brouard 9354:
1.222 brouard 9355: /* brutal averaging */
1.266 brouard 9356: /* for (i=1; i<=nlstate;i++){ */
9357: /* for (age=1; age<=bage; age++){ */
9358: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9359: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9360: /* } */
9361: /* for (age=fage; age<=AGESUP; age++){ */
9362: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9363: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9364: /* } */
9365: /* } /\* end i status *\/ */
9366: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9367: /* for (age=1; age<=AGESUP; age++){ */
9368: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9369: /* mobaverage[(int)age][i][cptcod]=0.; */
9370: /* } */
9371: /* } */
1.222 brouard 9372: }/* end cptcod */
1.266 brouard 9373: free_vector(agemaxgoodr,1, ncovcombmax);
9374: free_vector(agemaxgood,1, ncovcombmax);
9375: free_vector(agemingood,1, ncovcombmax);
9376: free_vector(agemingoodr,1, ncovcombmax);
9377: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9378: free_vector(sumnewm,1, ncovcombmax);
9379: free_vector(sumnewp,1, ncovcombmax);
9380: return 0;
9381: }/* End movingaverage */
1.218 brouard 9382:
1.126 brouard 9383:
1.296 brouard 9384:
1.126 brouard 9385: /************** Forecasting ******************/
1.296 brouard 9386: /* 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)*/
9387: 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){
9388: /* dateintemean, mean date of interviews
9389: dateprojd, year, month, day of starting projection
9390: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9391: agemin, agemax range of age
9392: dateprev1 dateprev2 range of dates during which prevalence is computed
9393: */
1.296 brouard 9394: /* double anprojd, mprojd, jprojd; */
9395: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9396: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9397: double agec; /* generic age */
1.296 brouard 9398: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9399: double *popeffectif,*popcount;
9400: double ***p3mat;
1.218 brouard 9401: /* double ***mobaverage; */
1.126 brouard 9402: char fileresf[FILENAMELENGTH];
9403:
9404: agelim=AGESUP;
1.211 brouard 9405: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9406: in each health status at the date of interview (if between dateprev1 and dateprev2).
9407: We still use firstpass and lastpass as another selection.
9408: */
1.214 brouard 9409: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9410: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9411:
1.201 brouard 9412: strcpy(fileresf,"F_");
9413: strcat(fileresf,fileresu);
1.126 brouard 9414: if((ficresf=fopen(fileresf,"w"))==NULL) {
9415: printf("Problem with forecast resultfile: %s\n", fileresf);
9416: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9417: }
1.235 brouard 9418: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9419: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9420:
1.225 brouard 9421: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9422:
9423:
9424: stepsize=(int) (stepm+YEARM-1)/YEARM;
9425: if (stepm<=12) stepsize=1;
9426: if(estepm < stepm){
9427: printf ("Problem %d lower than %d\n",estepm, stepm);
9428: }
1.270 brouard 9429: else{
9430: hstepm=estepm;
9431: }
9432: if(estepm > stepm){ /* Yes every two year */
9433: stepsize=2;
9434: }
1.296 brouard 9435: hstepm=hstepm/stepm;
1.126 brouard 9436:
1.296 brouard 9437:
9438: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9439: /* fractional in yp1 *\/ */
9440: /* aintmean=yp; */
9441: /* yp2=modf((yp1*12),&yp); */
9442: /* mintmean=yp; */
9443: /* yp1=modf((yp2*30.5),&yp); */
9444: /* jintmean=yp; */
9445: /* if(jintmean==0) jintmean=1; */
9446: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9447:
1.296 brouard 9448:
9449: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9450: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9451: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9452: i1=pow(2,cptcoveff);
1.126 brouard 9453: if (cptcovn < 1){i1=1;}
9454:
1.296 brouard 9455: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9456:
9457: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9458:
1.126 brouard 9459: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9460: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9461: 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) */
1.253 brouard 9462: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9463: continue;
1.227 brouard 9464: if(invalidvarcomb[k]){
9465: printf("\nCombination (%d) projection ignored because no cases \n",k);
9466: continue;
9467: }
9468: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9469: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9470: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
9471: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9472: }
1.235 brouard 9473: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9474: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9475: }
1.227 brouard 9476: fprintf(ficresf," yearproj age");
9477: for(j=1; j<=nlstate+ndeath;j++){
9478: for(i=1; i<=nlstate;i++)
9479: fprintf(ficresf," p%d%d",i,j);
9480: fprintf(ficresf," wp.%d",j);
9481: }
1.296 brouard 9482: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9483: fprintf(ficresf,"\n");
1.296 brouard 9484: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9485: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9486: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9487: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9488: nhstepm = nhstepm/hstepm;
9489: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9490: oldm=oldms;savm=savms;
1.268 brouard 9491: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9492: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9493: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9494: for (h=0; h<=nhstepm; h++){
9495: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9496: break;
9497: }
9498: }
9499: fprintf(ficresf,"\n");
9500: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9501: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
9502: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9503: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9504:
9505: for(j=1; j<=nlstate+ndeath;j++) {
9506: ppij=0.;
9507: for(i=1; i<=nlstate;i++) {
1.278 brouard 9508: if (mobilav>=1)
9509: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9510: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9511: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9512: }
1.268 brouard 9513: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9514: } /* end i */
9515: fprintf(ficresf," %.3f", ppij);
9516: }/* end j */
1.227 brouard 9517: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9518: } /* end agec */
1.266 brouard 9519: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9520: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9521: } /* end yearp */
9522: } /* end k */
1.219 brouard 9523:
1.126 brouard 9524: fclose(ficresf);
1.215 brouard 9525: printf("End of Computing forecasting \n");
9526: fprintf(ficlog,"End of Computing forecasting\n");
9527:
1.126 brouard 9528: }
9529:
1.269 brouard 9530: /************** Back Forecasting ******************/
1.296 brouard 9531: /* 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){ */
9532: 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){
9533: /* back1, year, month, day of starting backprojection
1.267 brouard 9534: agemin, agemax range of age
9535: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9536: anback2 year of end of backprojection (same day and month as back1).
9537: prevacurrent and prev are prevalences.
1.267 brouard 9538: */
9539: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9540: double agec; /* generic age */
1.302 brouard 9541: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 9542: double *popeffectif,*popcount;
9543: double ***p3mat;
9544: /* double ***mobaverage; */
9545: char fileresfb[FILENAMELENGTH];
9546:
1.268 brouard 9547: agelim=AGEINF;
1.267 brouard 9548: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9549: in each health status at the date of interview (if between dateprev1 and dateprev2).
9550: We still use firstpass and lastpass as another selection.
9551: */
9552: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9553: /* firstpass, lastpass, stepm, weightopt, model); */
9554:
9555: /*Do we need to compute prevalence again?*/
9556:
9557: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9558:
9559: strcpy(fileresfb,"FB_");
9560: strcat(fileresfb,fileresu);
9561: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9562: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9563: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9564: }
9565: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9566: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9567:
9568: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9569:
9570:
9571: stepsize=(int) (stepm+YEARM-1)/YEARM;
9572: if (stepm<=12) stepsize=1;
9573: if(estepm < stepm){
9574: printf ("Problem %d lower than %d\n",estepm, stepm);
9575: }
1.270 brouard 9576: else{
9577: hstepm=estepm;
9578: }
9579: if(estepm >= stepm){ /* Yes every two year */
9580: stepsize=2;
9581: }
1.267 brouard 9582:
9583: hstepm=hstepm/stepm;
1.296 brouard 9584: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9585: /* fractional in yp1 *\/ */
9586: /* aintmean=yp; */
9587: /* yp2=modf((yp1*12),&yp); */
9588: /* mintmean=yp; */
9589: /* yp1=modf((yp2*30.5),&yp); */
9590: /* jintmean=yp; */
9591: /* if(jintmean==0) jintmean=1; */
9592: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9593:
9594: i1=pow(2,cptcoveff);
9595: if (cptcovn < 1){i1=1;}
9596:
1.296 brouard 9597: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9598: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9599:
9600: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9601:
9602: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9603: for(k=1; k<=i1;k++){
9604: if(i1 != 1 && TKresult[nres]!= k)
9605: continue;
9606: if(invalidvarcomb[k]){
9607: printf("\nCombination (%d) projection ignored because no cases \n",k);
9608: continue;
9609: }
1.268 brouard 9610: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9611: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9612: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 9613: }
9614: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9615: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9616: }
9617: fprintf(ficresfb," yearbproj age");
9618: for(j=1; j<=nlstate+ndeath;j++){
9619: for(i=1; i<=nlstate;i++)
1.268 brouard 9620: fprintf(ficresfb," b%d%d",i,j);
9621: fprintf(ficresfb," b.%d",j);
1.267 brouard 9622: }
1.296 brouard 9623: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9624: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9625: fprintf(ficresfb,"\n");
1.296 brouard 9626: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9627: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9628: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9629: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9630: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9631: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9632: nhstepm = nhstepm/hstepm;
9633: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9634: oldm=oldms;savm=savms;
1.268 brouard 9635: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9636: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9637: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9638: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9639: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9640: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9641: for (h=0; h<=nhstepm; h++){
1.268 brouard 9642: if (h*hstepm/YEARM*stepm ==-yearp) {
9643: break;
9644: }
9645: }
9646: fprintf(ficresfb,"\n");
9647: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9648: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 9649: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9650: for(i=1; i<=nlstate+ndeath;i++) {
9651: ppij=0.;ppi=0.;
9652: for(j=1; j<=nlstate;j++) {
9653: /* if (mobilav==1) */
1.269 brouard 9654: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9655: ppi=ppi+prevacurrent[(int)agec][j][k];
9656: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9657: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9658: /* else { */
9659: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9660: /* } */
1.268 brouard 9661: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9662: } /* end j */
9663: if(ppi <0.99){
9664: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9665: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9666: }
9667: fprintf(ficresfb," %.3f", ppij);
9668: }/* end j */
1.267 brouard 9669: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9670: } /* end agec */
9671: } /* end yearp */
9672: } /* end k */
1.217 brouard 9673:
1.267 brouard 9674: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9675:
1.267 brouard 9676: fclose(ficresfb);
9677: printf("End of Computing Back forecasting \n");
9678: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9679:
1.267 brouard 9680: }
1.217 brouard 9681:
1.269 brouard 9682: /* Variance of prevalence limit: varprlim */
9683: 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 9684: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9685:
9686: char fileresvpl[FILENAMELENGTH];
9687: FILE *ficresvpl;
9688: double **oldm, **savm;
9689: double **varpl; /* Variances of prevalence limits by age */
9690: int i1, k, nres, j ;
9691:
9692: strcpy(fileresvpl,"VPL_");
9693: strcat(fileresvpl,fileresu);
9694: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9695: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9696: exit(0);
9697: }
1.288 brouard 9698: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9699: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9700:
9701: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9702: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9703:
9704: i1=pow(2,cptcoveff);
9705: if (cptcovn < 1){i1=1;}
9706:
1.337 brouard 9707: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9708: k=TKresult[nres];
1.338 brouard 9709: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9710: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 9711: if(i1 != 1 && TKresult[nres]!= k)
9712: continue;
9713: fprintf(ficresvpl,"\n#****** ");
9714: printf("\n#****** ");
9715: fprintf(ficlog,"\n#****** ");
1.337 brouard 9716: for(j=1;j<=cptcovs;j++) {
9717: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9718: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9719: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9720: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9721: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 9722: }
1.337 brouard 9723: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9724: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9725: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9726: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9727: /* } */
1.269 brouard 9728: fprintf(ficresvpl,"******\n");
9729: printf("******\n");
9730: fprintf(ficlog,"******\n");
9731:
9732: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9733: oldm=oldms;savm=savms;
9734: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9735: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9736: /*}*/
9737: }
9738:
9739: fclose(ficresvpl);
1.288 brouard 9740: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9741: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9742:
9743: }
9744: /* Variance of back prevalence: varbprlim */
9745: 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){
9746: /*------- Variance of back (stable) prevalence------*/
9747:
9748: char fileresvbl[FILENAMELENGTH];
9749: FILE *ficresvbl;
9750:
9751: double **oldm, **savm;
9752: double **varbpl; /* Variances of back prevalence limits by age */
9753: int i1, k, nres, j ;
9754:
9755: strcpy(fileresvbl,"VBL_");
9756: strcat(fileresvbl,fileresu);
9757: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9758: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9759: exit(0);
9760: }
9761: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9762: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9763:
9764:
9765: i1=pow(2,cptcoveff);
9766: if (cptcovn < 1){i1=1;}
9767:
1.337 brouard 9768: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9769: k=TKresult[nres];
1.338 brouard 9770: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9771: /* for(k=1; k<=i1;k++){ */
9772: /* if(i1 != 1 && TKresult[nres]!= k) */
9773: /* continue; */
1.269 brouard 9774: fprintf(ficresvbl,"\n#****** ");
9775: printf("\n#****** ");
9776: fprintf(ficlog,"\n#****** ");
1.337 brouard 9777: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 9778: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
9779: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
9780: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 9781: /* for(j=1;j<=cptcoveff;j++) { */
9782: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9783: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9784: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9785: /* } */
9786: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9787: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9788: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9789: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 9790: }
9791: fprintf(ficresvbl,"******\n");
9792: printf("******\n");
9793: fprintf(ficlog,"******\n");
9794:
9795: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9796: oldm=oldms;savm=savms;
9797:
9798: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9799: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9800: /*}*/
9801: }
9802:
9803: fclose(ficresvbl);
9804: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9805: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9806:
9807: } /* End of varbprlim */
9808:
1.126 brouard 9809: /************** Forecasting *****not tested NB*************/
1.227 brouard 9810: /* 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 9811:
1.227 brouard 9812: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9813: /* int *popage; */
9814: /* double calagedatem, agelim, kk1, kk2; */
9815: /* double *popeffectif,*popcount; */
9816: /* double ***p3mat,***tabpop,***tabpopprev; */
9817: /* /\* double ***mobaverage; *\/ */
9818: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9819:
1.227 brouard 9820: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9821: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9822: /* agelim=AGESUP; */
9823: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9824:
1.227 brouard 9825: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9826:
9827:
1.227 brouard 9828: /* strcpy(filerespop,"POP_"); */
9829: /* strcat(filerespop,fileresu); */
9830: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9831: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9832: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9833: /* } */
9834: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9835: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9836:
1.227 brouard 9837: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9838:
1.227 brouard 9839: /* /\* if (mobilav!=0) { *\/ */
9840: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9841: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9842: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9843: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9844: /* /\* } *\/ */
9845: /* /\* } *\/ */
1.126 brouard 9846:
1.227 brouard 9847: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9848: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9849:
1.227 brouard 9850: /* agelim=AGESUP; */
1.126 brouard 9851:
1.227 brouard 9852: /* hstepm=1; */
9853: /* hstepm=hstepm/stepm; */
1.218 brouard 9854:
1.227 brouard 9855: /* if (popforecast==1) { */
9856: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9857: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9858: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9859: /* } */
9860: /* popage=ivector(0,AGESUP); */
9861: /* popeffectif=vector(0,AGESUP); */
9862: /* popcount=vector(0,AGESUP); */
1.126 brouard 9863:
1.227 brouard 9864: /* i=1; */
9865: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9866:
1.227 brouard 9867: /* imx=i; */
9868: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9869: /* } */
1.218 brouard 9870:
1.227 brouard 9871: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9872: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9873: /* k=k+1; */
9874: /* fprintf(ficrespop,"\n#******"); */
9875: /* for(j=1;j<=cptcoveff;j++) { */
9876: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9877: /* } */
9878: /* fprintf(ficrespop,"******\n"); */
9879: /* fprintf(ficrespop,"# Age"); */
9880: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9881: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9882:
1.227 brouard 9883: /* for (cpt=0; cpt<=0;cpt++) { */
9884: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9885:
1.227 brouard 9886: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9887: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9888: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9889:
1.227 brouard 9890: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9891: /* oldm=oldms;savm=savms; */
9892: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9893:
1.227 brouard 9894: /* for (h=0; h<=nhstepm; h++){ */
9895: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9896: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9897: /* } */
9898: /* for(j=1; j<=nlstate+ndeath;j++) { */
9899: /* kk1=0.;kk2=0; */
9900: /* for(i=1; i<=nlstate;i++) { */
9901: /* if (mobilav==1) */
9902: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9903: /* else { */
9904: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9905: /* } */
9906: /* } */
9907: /* if (h==(int)(calagedatem+12*cpt)){ */
9908: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9909: /* /\*fprintf(ficrespop," %.3f", kk1); */
9910: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9911: /* } */
9912: /* } */
9913: /* for(i=1; i<=nlstate;i++){ */
9914: /* kk1=0.; */
9915: /* for(j=1; j<=nlstate;j++){ */
9916: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9917: /* } */
9918: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9919: /* } */
1.218 brouard 9920:
1.227 brouard 9921: /* if (h==(int)(calagedatem+12*cpt)) */
9922: /* for(j=1; j<=nlstate;j++) */
9923: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9924: /* } */
9925: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9926: /* } */
9927: /* } */
1.218 brouard 9928:
1.227 brouard 9929: /* /\******\/ */
1.218 brouard 9930:
1.227 brouard 9931: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9932: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9933: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9934: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9935: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9936:
1.227 brouard 9937: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9938: /* oldm=oldms;savm=savms; */
9939: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9940: /* for (h=0; h<=nhstepm; h++){ */
9941: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9942: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9943: /* } */
9944: /* for(j=1; j<=nlstate+ndeath;j++) { */
9945: /* kk1=0.;kk2=0; */
9946: /* for(i=1; i<=nlstate;i++) { */
9947: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9948: /* } */
9949: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9950: /* } */
9951: /* } */
9952: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9953: /* } */
9954: /* } */
9955: /* } */
9956: /* } */
1.218 brouard 9957:
1.227 brouard 9958: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9959:
1.227 brouard 9960: /* if (popforecast==1) { */
9961: /* free_ivector(popage,0,AGESUP); */
9962: /* free_vector(popeffectif,0,AGESUP); */
9963: /* free_vector(popcount,0,AGESUP); */
9964: /* } */
9965: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9966: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9967: /* fclose(ficrespop); */
9968: /* } /\* End of popforecast *\/ */
1.218 brouard 9969:
1.126 brouard 9970: int fileappend(FILE *fichier, char *optionfich)
9971: {
9972: if((fichier=fopen(optionfich,"a"))==NULL) {
9973: printf("Problem with file: %s\n", optionfich);
9974: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9975: return (0);
9976: }
9977: fflush(fichier);
9978: return (1);
9979: }
9980:
9981:
9982: /**************** function prwizard **********************/
9983: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9984: {
9985:
9986: /* Wizard to print covariance matrix template */
9987:
1.164 brouard 9988: char ca[32], cb[32];
9989: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9990: int numlinepar;
9991:
9992: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9993: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9994: for(i=1; i <=nlstate; i++){
9995: jj=0;
9996: for(j=1; j <=nlstate+ndeath; j++){
9997: if(j==i) continue;
9998: jj++;
9999: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10000: printf("%1d%1d",i,j);
10001: fprintf(ficparo,"%1d%1d",i,j);
10002: for(k=1; k<=ncovmodel;k++){
10003: /* printf(" %lf",param[i][j][k]); */
10004: /* fprintf(ficparo," %lf",param[i][j][k]); */
10005: printf(" 0.");
10006: fprintf(ficparo," 0.");
10007: }
10008: printf("\n");
10009: fprintf(ficparo,"\n");
10010: }
10011: }
10012: printf("# Scales (for hessian or gradient estimation)\n");
10013: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10014: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10015: for(i=1; i <=nlstate; i++){
10016: jj=0;
10017: for(j=1; j <=nlstate+ndeath; j++){
10018: if(j==i) continue;
10019: jj++;
10020: fprintf(ficparo,"%1d%1d",i,j);
10021: printf("%1d%1d",i,j);
10022: fflush(stdout);
10023: for(k=1; k<=ncovmodel;k++){
10024: /* printf(" %le",delti3[i][j][k]); */
10025: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10026: printf(" 0.");
10027: fprintf(ficparo," 0.");
10028: }
10029: numlinepar++;
10030: printf("\n");
10031: fprintf(ficparo,"\n");
10032: }
10033: }
10034: printf("# Covariance matrix\n");
10035: /* # 121 Var(a12)\n\ */
10036: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10037: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10038: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10039: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10040: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10041: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10042: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10043: fflush(stdout);
10044: fprintf(ficparo,"# Covariance matrix\n");
10045: /* # 121 Var(a12)\n\ */
10046: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10047: /* # ...\n\ */
10048: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10049:
10050: for(itimes=1;itimes<=2;itimes++){
10051: jj=0;
10052: for(i=1; i <=nlstate; i++){
10053: for(j=1; j <=nlstate+ndeath; j++){
10054: if(j==i) continue;
10055: for(k=1; k<=ncovmodel;k++){
10056: jj++;
10057: ca[0]= k+'a'-1;ca[1]='\0';
10058: if(itimes==1){
10059: printf("#%1d%1d%d",i,j,k);
10060: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10061: }else{
10062: printf("%1d%1d%d",i,j,k);
10063: fprintf(ficparo,"%1d%1d%d",i,j,k);
10064: /* printf(" %.5le",matcov[i][j]); */
10065: }
10066: ll=0;
10067: for(li=1;li <=nlstate; li++){
10068: for(lj=1;lj <=nlstate+ndeath; lj++){
10069: if(lj==li) continue;
10070: for(lk=1;lk<=ncovmodel;lk++){
10071: ll++;
10072: if(ll<=jj){
10073: cb[0]= lk +'a'-1;cb[1]='\0';
10074: if(ll<jj){
10075: if(itimes==1){
10076: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10077: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10078: }else{
10079: printf(" 0.");
10080: fprintf(ficparo," 0.");
10081: }
10082: }else{
10083: if(itimes==1){
10084: printf(" Var(%s%1d%1d)",ca,i,j);
10085: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10086: }else{
10087: printf(" 0.");
10088: fprintf(ficparo," 0.");
10089: }
10090: }
10091: }
10092: } /* end lk */
10093: } /* end lj */
10094: } /* end li */
10095: printf("\n");
10096: fprintf(ficparo,"\n");
10097: numlinepar++;
10098: } /* end k*/
10099: } /*end j */
10100: } /* end i */
10101: } /* end itimes */
10102:
10103: } /* end of prwizard */
10104: /******************* Gompertz Likelihood ******************************/
10105: double gompertz(double x[])
10106: {
1.302 brouard 10107: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10108: int i,n=0; /* n is the size of the sample */
10109:
1.220 brouard 10110: for (i=1;i<=imx ; i++) {
1.126 brouard 10111: sump=sump+weight[i];
10112: /* sump=sump+1;*/
10113: num=num+1;
10114: }
1.302 brouard 10115: L=0.0;
10116: /* agegomp=AGEGOMP; */
1.126 brouard 10117: /* for (i=0; i<=imx; i++)
10118: 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]);*/
10119:
1.302 brouard 10120: for (i=1;i<=imx ; i++) {
10121: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10122: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10123: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10124: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10125: * +
10126: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10127: */
10128: if (wav[i] > 1 || agedc[i] < AGESUP) {
10129: if (cens[i] == 1){
10130: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10131: } else if (cens[i] == 0){
1.126 brouard 10132: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10133: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10134: } else
10135: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10136: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10137: L=L+A*weight[i];
1.126 brouard 10138: /* 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 10139: }
10140: }
1.126 brouard 10141:
1.302 brouard 10142: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10143:
10144: return -2*L*num/sump;
10145: }
10146:
1.136 brouard 10147: #ifdef GSL
10148: /******************* Gompertz_f Likelihood ******************************/
10149: double gompertz_f(const gsl_vector *v, void *params)
10150: {
1.302 brouard 10151: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10152: double *x= (double *) v->data;
10153: int i,n=0; /* n is the size of the sample */
10154:
10155: for (i=0;i<=imx-1 ; i++) {
10156: sump=sump+weight[i];
10157: /* sump=sump+1;*/
10158: num=num+1;
10159: }
10160:
10161:
10162: /* for (i=0; i<=imx; i++)
10163: 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]);*/
10164: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10165: for (i=1;i<=imx ; i++)
10166: {
10167: if (cens[i] == 1 && wav[i]>1)
10168: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10169:
10170: if (cens[i] == 0 && wav[i]>1)
10171: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10172: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10173:
10174: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10175: if (wav[i] > 1 ) { /* ??? */
10176: LL=LL+A*weight[i];
10177: /* 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]);*/
10178: }
10179: }
10180:
10181: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10182: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10183:
10184: return -2*LL*num/sump;
10185: }
10186: #endif
10187:
1.126 brouard 10188: /******************* Printing html file ***********/
1.201 brouard 10189: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10190: int lastpass, int stepm, int weightopt, char model[],\
10191: int imx, double p[],double **matcov,double agemortsup){
10192: int i,k;
10193:
10194: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10195: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10196: for (i=1;i<=2;i++)
10197: 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 10198: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10199: fprintf(fichtm,"</ul>");
10200:
10201: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10202:
10203: 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>");
10204:
10205: for (k=agegomp;k<(agemortsup-2);k++)
10206: 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]);
10207:
10208:
10209: fflush(fichtm);
10210: }
10211:
10212: /******************* Gnuplot file **************/
1.201 brouard 10213: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10214:
10215: char dirfileres[132],optfileres[132];
1.164 brouard 10216:
1.126 brouard 10217: int ng;
10218:
10219:
10220: /*#ifdef windows */
10221: fprintf(ficgp,"cd \"%s\" \n",pathc);
10222: /*#endif */
10223:
10224:
10225: strcpy(dirfileres,optionfilefiname);
10226: strcpy(optfileres,"vpl");
1.199 brouard 10227: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10228: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10229: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10230: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10231: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10232:
10233: }
10234:
1.136 brouard 10235: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10236: {
1.126 brouard 10237:
1.136 brouard 10238: /*-------- data file ----------*/
10239: FILE *fic;
10240: char dummy[]=" ";
1.240 brouard 10241: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10242: int lstra;
1.136 brouard 10243: int linei, month, year,iout;
1.302 brouard 10244: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10245: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10246: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10247: char *stratrunc;
1.223 brouard 10248:
1.240 brouard 10249: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
10250: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 10251: for(v=1;v<NCOVMAX;v++){
10252: DummyV[v]=0;
10253: FixedV[v]=0;
10254: }
1.126 brouard 10255:
1.240 brouard 10256: for(v=1; v <=ncovcol;v++){
10257: DummyV[v]=0;
10258: FixedV[v]=0;
10259: }
10260: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
10261: DummyV[v]=1;
10262: FixedV[v]=0;
10263: }
10264: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
10265: DummyV[v]=0;
10266: FixedV[v]=1;
10267: }
10268: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
10269: DummyV[v]=1;
10270: FixedV[v]=1;
10271: }
10272: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
10273: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
10274: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
10275: }
1.339 brouard 10276:
10277: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10278:
1.136 brouard 10279: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10280: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10281: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10282: }
1.126 brouard 10283:
1.302 brouard 10284: /* Is it a BOM UTF-8 Windows file? */
10285: /* First data line */
10286: linei=0;
10287: while(fgets(line, MAXLINE, fic)) {
10288: noffset=0;
10289: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10290: {
10291: noffset=noffset+3;
10292: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10293: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10294: fflush(ficlog); return 1;
10295: }
10296: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10297: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10298: {
10299: noffset=noffset+2;
1.304 brouard 10300: 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);
10301: 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 10302: fflush(ficlog); return 1;
10303: }
10304: else if( line[0] == 0 && line[1] == 0)
10305: {
10306: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10307: noffset=noffset+4;
1.304 brouard 10308: 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);
10309: 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 10310: fflush(ficlog); return 1;
10311: }
10312: } else{
10313: ;/*printf(" Not a BOM file\n");*/
10314: }
10315: /* If line starts with a # it is a comment */
10316: if (line[noffset] == '#') {
10317: linei=linei+1;
10318: break;
10319: }else{
10320: break;
10321: }
10322: }
10323: fclose(fic);
10324: if((fic=fopen(datafile,"r"))==NULL) {
10325: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10326: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10327: }
10328: /* Not a Bom file */
10329:
1.136 brouard 10330: i=1;
10331: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10332: linei=linei+1;
10333: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10334: if(line[j] == '\t')
10335: line[j] = ' ';
10336: }
10337: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10338: ;
10339: };
10340: line[j+1]=0; /* Trims blanks at end of line */
10341: if(line[0]=='#'){
10342: fprintf(ficlog,"Comment line\n%s\n",line);
10343: printf("Comment line\n%s\n",line);
10344: continue;
10345: }
10346: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10347: strcpy(line, linetmp);
1.223 brouard 10348:
10349: /* Loops on waves */
10350: for (j=maxwav;j>=1;j--){
10351: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10352: cutv(stra, strb, line, ' ');
10353: if(strb[0]=='.') { /* Missing value */
10354: lval=-1;
10355: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 ! brouard 10356: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10357: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10358: 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);
10359: 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);
10360: return 1;
10361: }
10362: }else{
10363: errno=0;
10364: /* what_kind_of_number(strb); */
10365: dval=strtod(strb,&endptr);
10366: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10367: /* if(strb != endptr && *endptr == '\0') */
10368: /* dval=dlval; */
10369: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10370: if( strb[0]=='\0' || (*endptr != '\0')){
10371: 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);
10372: 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);
10373: return 1;
10374: }
10375: cotqvar[j][iv][i]=dval;
1.341 ! brouard 10376: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10377: }
10378: strcpy(line,stra);
1.223 brouard 10379: }/* end loop ntqv */
1.225 brouard 10380:
1.223 brouard 10381: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10382: cutv(stra, strb, line, ' ');
10383: if(strb[0]=='.') { /* Missing value */
10384: lval=-1;
10385: }else{
10386: errno=0;
10387: lval=strtol(strb,&endptr,10);
10388: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10389: if( strb[0]=='\0' || (*endptr != '\0')){
10390: 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);
10391: 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);
10392: return 1;
10393: }
10394: }
10395: if(lval <-1 || lval >1){
10396: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10397: 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 10398: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10399: For example, for multinomial values like 1, 2 and 3,\n \
10400: build V1=0 V2=0 for the reference value (1),\n \
10401: V1=1 V2=0 for (2) \n \
1.223 brouard 10402: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10403: output of IMaCh is often meaningless.\n \
1.319 brouard 10404: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10405: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10406: 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 10407: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10408: For example, for multinomial values like 1, 2 and 3,\n \
10409: build V1=0 V2=0 for the reference value (1),\n \
10410: V1=1 V2=0 for (2) \n \
1.223 brouard 10411: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10412: output of IMaCh is often meaningless.\n \
1.319 brouard 10413: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10414: return 1;
10415: }
1.341 ! brouard 10416: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10417: strcpy(line,stra);
1.223 brouard 10418: }/* end loop ntv */
1.225 brouard 10419:
1.223 brouard 10420: /* Statuses at wave */
1.137 brouard 10421: cutv(stra, strb, line, ' ');
1.223 brouard 10422: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10423: lval=-1;
1.136 brouard 10424: }else{
1.238 brouard 10425: errno=0;
10426: lval=strtol(strb,&endptr,10);
10427: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10428: if( strb[0]=='\0' || (*endptr != '\0')){
10429: 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);
10430: 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);
10431: return 1;
10432: }
1.136 brouard 10433: }
1.225 brouard 10434:
1.136 brouard 10435: s[j][i]=lval;
1.225 brouard 10436:
1.223 brouard 10437: /* Date of Interview */
1.136 brouard 10438: strcpy(line,stra);
10439: cutv(stra, strb,line,' ');
1.169 brouard 10440: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10441: }
1.169 brouard 10442: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10443: month=99;
10444: year=9999;
1.136 brouard 10445: }else{
1.225 brouard 10446: 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);
10447: 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);
10448: return 1;
1.136 brouard 10449: }
10450: anint[j][i]= (double) year;
1.302 brouard 10451: mint[j][i]= (double)month;
10452: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10453: /* 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]); */
10454: /* 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]); */
10455: /* } */
1.136 brouard 10456: strcpy(line,stra);
1.223 brouard 10457: } /* End loop on waves */
1.225 brouard 10458:
1.223 brouard 10459: /* Date of death */
1.136 brouard 10460: cutv(stra, strb,line,' ');
1.169 brouard 10461: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10462: }
1.169 brouard 10463: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10464: month=99;
10465: year=9999;
10466: }else{
1.141 brouard 10467: 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 10468: 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);
10469: return 1;
1.136 brouard 10470: }
10471: andc[i]=(double) year;
10472: moisdc[i]=(double) month;
10473: strcpy(line,stra);
10474:
1.223 brouard 10475: /* Date of birth */
1.136 brouard 10476: cutv(stra, strb,line,' ');
1.169 brouard 10477: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10478: }
1.169 brouard 10479: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10480: month=99;
10481: year=9999;
10482: }else{
1.141 brouard 10483: 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);
10484: 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 10485: return 1;
1.136 brouard 10486: }
10487: if (year==9999) {
1.141 brouard 10488: 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);
10489: 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 10490: return 1;
10491:
1.136 brouard 10492: }
10493: annais[i]=(double)(year);
1.302 brouard 10494: moisnais[i]=(double)(month);
10495: for (j=1;j<=maxwav;j++){
10496: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10497: 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]);
10498: 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]);
10499: }
10500: }
10501:
1.136 brouard 10502: strcpy(line,stra);
1.225 brouard 10503:
1.223 brouard 10504: /* Sample weight */
1.136 brouard 10505: cutv(stra, strb,line,' ');
10506: errno=0;
10507: dval=strtod(strb,&endptr);
10508: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10509: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10510: 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 10511: fflush(ficlog);
10512: return 1;
10513: }
10514: weight[i]=dval;
10515: strcpy(line,stra);
1.225 brouard 10516:
1.223 brouard 10517: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10518: cutv(stra, strb, line, ' ');
10519: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10520: lval=-1;
1.311 brouard 10521: coqvar[iv][i]=NAN;
10522: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10523: }else{
1.225 brouard 10524: errno=0;
10525: /* what_kind_of_number(strb); */
10526: dval=strtod(strb,&endptr);
10527: /* if(strb != endptr && *endptr == '\0') */
10528: /* dval=dlval; */
10529: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10530: if( strb[0]=='\0' || (*endptr != '\0')){
10531: 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);
10532: 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);
10533: return 1;
10534: }
10535: coqvar[iv][i]=dval;
1.226 brouard 10536: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10537: }
10538: strcpy(line,stra);
10539: }/* end loop nqv */
1.136 brouard 10540:
1.223 brouard 10541: /* Covariate values */
1.136 brouard 10542: for (j=ncovcol;j>=1;j--){
10543: cutv(stra, strb,line,' ');
1.223 brouard 10544: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10545: lval=-1;
1.136 brouard 10546: }else{
1.225 brouard 10547: errno=0;
10548: lval=strtol(strb,&endptr,10);
10549: if( strb[0]=='\0' || (*endptr != '\0')){
10550: 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);
10551: 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);
10552: return 1;
10553: }
1.136 brouard 10554: }
10555: if(lval <-1 || lval >1){
1.225 brouard 10556: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10557: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10558: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10559: For example, for multinomial values like 1, 2 and 3,\n \
10560: build V1=0 V2=0 for the reference value (1),\n \
10561: V1=1 V2=0 for (2) \n \
1.136 brouard 10562: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10563: output of IMaCh is often meaningless.\n \
1.136 brouard 10564: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 10565: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10566: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10567: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10568: For example, for multinomial values like 1, 2 and 3,\n \
10569: build V1=0 V2=0 for the reference value (1),\n \
10570: V1=1 V2=0 for (2) \n \
1.136 brouard 10571: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10572: output of IMaCh is often meaningless.\n \
1.136 brouard 10573: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10574: return 1;
1.136 brouard 10575: }
10576: covar[j][i]=(double)(lval);
10577: strcpy(line,stra);
10578: }
10579: lstra=strlen(stra);
1.225 brouard 10580:
1.136 brouard 10581: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10582: stratrunc = &(stra[lstra-9]);
10583: num[i]=atol(stratrunc);
10584: }
10585: else
10586: num[i]=atol(stra);
10587: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10588: 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;}*/
10589:
10590: i=i+1;
10591: } /* End loop reading data */
1.225 brouard 10592:
1.136 brouard 10593: *imax=i-1; /* Number of individuals */
10594: fclose(fic);
1.225 brouard 10595:
1.136 brouard 10596: return (0);
1.164 brouard 10597: /* endread: */
1.225 brouard 10598: printf("Exiting readdata: ");
10599: fclose(fic);
10600: return (1);
1.223 brouard 10601: }
1.126 brouard 10602:
1.234 brouard 10603: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10604: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10605: while (*p2 == ' ')
1.234 brouard 10606: p2++;
10607: /* while ((*p1++ = *p2++) !=0) */
10608: /* ; */
10609: /* do */
10610: /* while (*p2 == ' ') */
10611: /* p2++; */
10612: /* while (*p1++ == *p2++); */
10613: *stri=p2;
1.145 brouard 10614: }
10615:
1.330 brouard 10616: int decoderesult( char resultline[], int nres)
1.230 brouard 10617: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10618: {
1.235 brouard 10619: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10620: char resultsav[MAXLINE];
1.330 brouard 10621: /* int resultmodel[MAXLINE]; */
1.334 brouard 10622: /* int modelresult[MAXLINE]; */
1.230 brouard 10623: char stra[80], strb[80], strc[80], strd[80],stre[80];
10624:
1.234 brouard 10625: removefirstspace(&resultline);
1.332 brouard 10626: printf("decoderesult:%s\n",resultline);
1.230 brouard 10627:
1.332 brouard 10628: strcpy(resultsav,resultline);
10629: printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline);
1.230 brouard 10630: if (strlen(resultsav) >1){
1.334 brouard 10631: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 10632: }
1.253 brouard 10633: if(j == 0){ /* Resultline but no = */
10634: TKresult[nres]=0; /* Combination for the nresult and the model */
10635: return (0);
10636: }
1.234 brouard 10637: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 10638: 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);
10639: 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 10640: /* return 1;*/
1.234 brouard 10641: }
1.334 brouard 10642: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 10643: if(nbocc(resultsav,'=') >1){
1.318 brouard 10644: 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 10645: /* 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 10646: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 10647: /* If a blank, then strc="V4=" and strd='\0' */
10648: if(strc[0]=='\0'){
10649: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
10650: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
10651: return 1;
10652: }
1.234 brouard 10653: }else
10654: cutl(strc,strd,resultsav,'=');
1.318 brouard 10655: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10656:
1.230 brouard 10657: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10658: 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 10659: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10660: /* cptcovsel++; */
10661: if (nbocc(stra,'=') >0)
10662: strcpy(resultsav,stra); /* and analyzes it */
10663: }
1.235 brouard 10664: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10665: /* 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 10666: 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 10667: if(Typevar[k1]==0){ /* Single covariate in model */
10668: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10669: match=0;
1.318 brouard 10670: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10671: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10672: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10673: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10674: break;
10675: }
10676: }
10677: if(match == 0){
1.338 brouard 10678: 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]);
10679: 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 10680: return 1;
1.234 brouard 10681: }
1.332 brouard 10682: }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*/
10683: /* We feed resultmodel[k1]=k2; */
10684: match=0;
10685: 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 */
10686: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10687: 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 10688: resultmodel[nres][k1]=k2; /* Added here */
10689: printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]);
10690: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10691: break;
10692: }
10693: }
10694: if(match == 0){
1.338 brouard 10695: 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]);
10696: 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 10697: return 1;
10698: }
10699: }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/
10700: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
10701: match=0;
10702: 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]);
10703: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10704: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10705: /* modelresult[k2]=k1; */
10706: printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]);
10707: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10708: }
10709: }
10710: if(match == 0){
1.338 brouard 10711: printf("Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
10712: fprintf(ficlog,"Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 10713: return 1;
10714: }
10715: match=0;
10716: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10717: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10718: /* modelresult[k2]=k1;*/
10719: printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]);
10720: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10721: break;
10722: }
10723: }
10724: if(match == 0){
1.338 brouard 10725: printf("Error in result line (Product without age second variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
10726: fprintf(ficlog,"Error in result line (Product without age second variable): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 10727: return 1;
10728: }
10729: }/* End of testing */
1.333 brouard 10730: }/* End loop cptcovt */
1.235 brouard 10731: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10732: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 10733: 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)
10734: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 10735: match=0;
1.318 brouard 10736: 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 10737: if(Typevar[k1]==0){ /* Single only */
1.237 brouard 10738: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.330 brouard 10739: 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 10740: 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 10741: ++match;
10742: }
10743: }
10744: }
10745: if(match == 0){
1.338 brouard 10746: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
10747: 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 10748: return 1;
1.234 brouard 10749: }else if(match > 1){
1.338 brouard 10750: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
10751: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 10752: return 1;
1.234 brouard 10753: }
10754: }
1.334 brouard 10755: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 10756: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10757: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 10758: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10759: /* 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*/
10760: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 10761: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10762: /* 1 0 0 0 */
10763: /* 2 1 0 0 */
10764: /* 3 0 1 0 */
1.330 brouard 10765: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 10766: /* 5 0 0 1 */
1.330 brouard 10767: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 10768: /* 7 0 1 1 */
10769: /* 8 1 1 1 */
1.237 brouard 10770: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10771: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10772: /* V5*age V5 known which value for nres? */
10773: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 10774: 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.
10775: * loop on position k1 in the MODEL LINE */
1.331 brouard 10776: /* k counting number of combination of single dummies in the equation model */
10777: /* k4 counting single dummies in the equation model */
10778: /* k4q counting single quantitatives in the equation model */
1.334 brouard 10779: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, k1 is sorting according to MODEL, but k3 to resultline */
10780: /* 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 10781: /* 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 10782: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 10783: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
10784: /* k3 is the position in the nres result line of the k1th variable of the model equation */
10785: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
10786: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
10787: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 10788: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 10789: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 10790: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 10791: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
10792: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
10793: 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 10794: 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 10795: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 10796: /* Tinvresult[nres][4]=1 */
1.334 brouard 10797: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
10798: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
10799: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
10800: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 10801: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 10802: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.332 brouard 10803: 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 10804: k4++;;
1.331 brouard 10805: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 10806: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 10807: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 10808: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 10809: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
10810: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
10811: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 10812: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
10813: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
10814: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
10815: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10816: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
10817: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 10818: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 10819: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 10820: precov[nres][k1]=Tvalsel[k3q];
10821: 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 10822: k4q++;;
1.331 brouard 10823: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
10824: /* Tvar[k1]; */ /* Age variable */
1.332 brouard 10825: /* Wrong we want the value of variable name Tvar[k1] */
10826:
10827: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
1.331 brouard 10828: 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)*/
1.334 brouard 10829: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
1.332 brouard 10830: precov[nres][k1]=Tvalsel[k3];
10831: 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 10832: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.332 brouard 10833: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.331 brouard 10834: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 10835: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
1.332 brouard 10836: precov[nres][k1]=Tvalsel[k3q];
1.334 brouard 10837: 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]);
1.331 brouard 10838: }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
1.332 brouard 10839: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
10840: 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 10841: }else{
1.332 brouard 10842: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
10843: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 10844: }
10845: }
1.234 brouard 10846:
1.334 brouard 10847: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 10848: return (0);
10849: }
1.235 brouard 10850:
1.230 brouard 10851: int decodemodel( char model[], int lastobs)
10852: /**< This routine decodes the model and returns:
1.224 brouard 10853: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10854: * - nagesqr = 1 if age*age in the model, otherwise 0.
10855: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10856: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10857: * - cptcovage number of covariates with age*products =2
10858: * - cptcovs number of simple covariates
1.339 brouard 10859: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 10860: * - 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 10861: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 10862: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10863: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10864: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10865: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10866: */
1.319 brouard 10867: /* 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 10868: {
1.238 brouard 10869: int i, j, k, ks, v;
1.227 brouard 10870: int j1, k1, k2, k3, k4;
1.136 brouard 10871: char modelsav[80];
1.145 brouard 10872: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10873: char *strpt;
1.136 brouard 10874:
1.145 brouard 10875: /*removespace(model);*/
1.136 brouard 10876: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10877: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10878: if (strstr(model,"AGE") !=0){
1.192 brouard 10879: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10880: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10881: return 1;
10882: }
1.141 brouard 10883: if (strstr(model,"v") !=0){
1.338 brouard 10884: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
10885: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 10886: return 1;
10887: }
1.187 brouard 10888: strcpy(modelsav,model);
10889: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 10890: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 10891: if(strpt != model){
1.338 brouard 10892: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10893: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10894: corresponding column of parameters.\n",model);
1.338 brouard 10895: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10896: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10897: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10898: return 1;
1.225 brouard 10899: }
1.187 brouard 10900: nagesqr=1;
10901: if (strstr(model,"+age*age") !=0)
1.234 brouard 10902: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10903: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10904: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10905: else
1.234 brouard 10906: substrchaine(modelsav, model, "age*age");
1.187 brouard 10907: }else
10908: nagesqr=0;
10909: if (strlen(modelsav) >1){
10910: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10911: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10912: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10913: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10914: * cst, age and age*age
10915: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10916: /* including age products which are counted in cptcovage.
10917: * but the covariates which are products must be treated
10918: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10919: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10920: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10921:
10922:
1.187 brouard 10923: /* Design
10924: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10925: * < ncovcol=8 >
10926: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10927: * k= 1 2 3 4 5 6 7 8
10928: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10929: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10930: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10931: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10932: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10933: * Tage[++cptcovage]=k
10934: * if products, new covar are created after ncovcol with k1
10935: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10936: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10937: * 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
10938: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10939: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10940: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10941: * < ncovcol=8 >
10942: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10943: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10944: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10945: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10946: * p Tprod[1]@2={ 6, 5}
10947: *p Tvard[1][1]@4= {7, 8, 5, 6}
10948: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10949: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10950: *How to reorganize? Tvars(orted)
1.187 brouard 10951: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10952: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10953: * {2, 1, 4, 8, 5, 6, 3, 7}
10954: * Struct []
10955: */
1.225 brouard 10956:
1.187 brouard 10957: /* This loop fills the array Tvar from the string 'model'.*/
10958: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10959: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10960: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10961: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10962: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10963: /* k=1 Tvar[1]=2 (from V2) */
10964: /* k=5 Tvar[5] */
10965: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10966: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10967: /* } */
1.198 brouard 10968: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10969: /*
10970: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10971: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10972: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10973: }
1.187 brouard 10974: cptcovage=0;
1.319 brouard 10975: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10976: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10977: 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" */
10978: if (nbocc(modelsav,'+')==0)
10979: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10980: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10981: /*scanf("%d",i);*/
1.319 brouard 10982: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10983: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
1.234 brouard 10984: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10985: /* covar is not filled and then is empty */
10986: cptcovprod--;
10987: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10988: 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 */
1.234 brouard 10989: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10990: cptcovage++; /* Counts the number of covariates which include age as a product */
10991: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.234 brouard 10992: /*printf("stre=%s ", stre);*/
10993: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10994: cptcovprod--;
10995: cutl(stre,strb,strc,'V');
10996: Tvar[k]=atoi(stre);
10997: Typevar[k]=1; /* 1 for age product */
10998: cptcovage++;
10999: Tage[cptcovage]=k;
11000: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
11001: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
11002: cptcovn++;
11003: cptcovprodnoage++;k1++;
11004: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.339 brouard 11005: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
1.234 brouard 11006: because this model-covariate is a construction we invent a new column
11007: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.335 brouard 11008: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
1.319 brouard 11009: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
1.339 brouard 11010: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
1.335 brouard 11011: /* Please remark that the new variables are model dependent */
11012: /* If we have 4 variable but the model uses only 3, like in
11013: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11014: * k= 1 2 3 4 5 6 7 8
11015: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11016: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11017: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11018: */
1.339 brouard 11019: Typevar[k]=2; /* 2 for product */
1.234 brouard 11020: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11021: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 11022: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 11023: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
1.330 brouard 11024: Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
1.234 brouard 11025: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
1.330 brouard 11026: Tvardk[k][2] =atoi(stre); /* n 4 for V4*/
1.234 brouard 11027: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11028: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11029: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 11030: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 11031: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
1.339 brouard 11032: 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 */
11033: for (i=1; i<=lastobs;i++){/* For fixed product */
1.234 brouard 11034: /* Computes the new covariate which is a product of
11035: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
1.339 brouard 11036: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11037: }
11038: } /*End of FixedV */
1.234 brouard 11039: } /* End age is not in the model */
11040: } /* End if model includes a product */
1.319 brouard 11041: else { /* not a product */
1.234 brouard 11042: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11043: /* scanf("%d",i);*/
11044: cutl(strd,strc,strb,'V');
11045: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11046: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11047: Tvar[k]=atoi(strd);
11048: Typevar[k]=0; /* 0 for simple covariates */
11049: }
11050: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11051: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11052: scanf("%d",i);*/
1.187 brouard 11053: } /* end of loop + on total covariates */
11054: } /* end if strlen(modelsave == 0) age*age might exist */
11055: } /* end if strlen(model == 0) */
1.136 brouard 11056:
11057: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11058: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11059:
1.136 brouard 11060: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11061: printf("cptcovprod=%d ", cptcovprod);
11062: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11063: scanf("%d ",i);*/
11064:
11065:
1.230 brouard 11066: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11067: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11068: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11069: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11070: k = 1 2 3 4 5 6 7 8 9
11071: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11072: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11073: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11074: Dummy[k] 1 0 0 0 3 1 1 2 3
11075: Tmodelind[combination of covar]=k;
1.225 brouard 11076: */
11077: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11078: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11079: /* 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 11080: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11081: printf("Model=1+age+%s\n\
1.227 brouard 11082: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11083: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11084: 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 11085: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 11086: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11087: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11088: 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);
1.285 brouard 11089: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.339 brouard 11090: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt */
1.234 brouard 11091: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11092: Fixed[k]= 0;
11093: Dummy[k]= 0;
1.225 brouard 11094: ncoveff++;
1.232 brouard 11095: ncovf++;
1.234 brouard 11096: nsd++;
11097: modell[k].maintype= FTYPE;
11098: TvarsD[nsd]=Tvar[k];
11099: TvarsDind[nsd]=k;
1.330 brouard 11100: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11101: TvarF[ncovf]=Tvar[k];
11102: TvarFind[ncovf]=k;
11103: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11104: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11105: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
11106: }else if( Tposprod[k]>0 && Typevar[k]==2 && 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 */
1.234 brouard 11107: Fixed[k]= 0;
11108: Dummy[k]= 0;
11109: ncoveff++;
11110: ncovf++;
11111: modell[k].maintype= FTYPE;
11112: TvarF[ncovf]=Tvar[k];
1.330 brouard 11113: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
1.234 brouard 11114: TvarFind[ncovf]=k;
1.230 brouard 11115: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 11116: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 11117: }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 11118: Fixed[k]= 0;
11119: Dummy[k]= 1;
1.230 brouard 11120: nqfveff++;
1.234 brouard 11121: modell[k].maintype= FTYPE;
11122: modell[k].subtype= FQ;
11123: nsq++;
1.334 brouard 11124: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11125: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11126: ncovf++;
1.234 brouard 11127: TvarF[ncovf]=Tvar[k];
11128: TvarFind[ncovf]=k;
1.231 brouard 11129: 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 11130: 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 11131: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11132: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11133: /* model V1+V3+age*V1+age*V3+V1*V3 */
11134: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11135: ncovvt++;
11136: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11137: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11138:
1.227 brouard 11139: Fixed[k]= 1;
11140: Dummy[k]= 0;
1.225 brouard 11141: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11142: modell[k].maintype= VTYPE;
11143: modell[k].subtype= VD;
11144: nsd++;
11145: TvarsD[nsd]=Tvar[k];
11146: TvarsDind[nsd]=k;
1.330 brouard 11147: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11148: ncovv++; /* Only simple time varying variables */
11149: TvarV[ncovv]=Tvar[k];
1.242 brouard 11150: 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 11151: 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 */
11152: 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 11153: 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);
11154: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11155: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11156: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11157: /* model V1+V3+age*V1+age*V3+V1*V3 */
11158: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11159: ncovvt++;
11160: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11161: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11162:
1.234 brouard 11163: Fixed[k]= 1;
11164: Dummy[k]= 1;
11165: nqtveff++;
11166: modell[k].maintype= VTYPE;
11167: modell[k].subtype= VQ;
11168: ncovv++; /* Only simple time varying variables */
11169: nsq++;
1.334 brouard 11170: 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) */
11171: 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 11172: TvarV[ncovv]=Tvar[k];
1.242 brouard 11173: 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 11174: 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 */
11175: 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 11176: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11177: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
11178: printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%d,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv);
1.228 brouard 11179: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 11180: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11181: ncova++;
11182: TvarA[ncova]=Tvar[k];
11183: TvarAind[ncova]=k;
1.231 brouard 11184: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11185: Fixed[k]= 2;
11186: Dummy[k]= 2;
11187: modell[k].maintype= ATYPE;
11188: modell[k].subtype= APFD;
11189: /* ncoveff++; */
1.227 brouard 11190: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11191: Fixed[k]= 2;
11192: Dummy[k]= 3;
11193: modell[k].maintype= ATYPE;
11194: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
11195: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11196: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11197: Fixed[k]= 3;
11198: Dummy[k]= 2;
11199: modell[k].maintype= ATYPE;
11200: modell[k].subtype= APVD; /* Product age * varying dummy */
11201: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11202: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11203: Fixed[k]= 3;
11204: Dummy[k]= 3;
11205: modell[k].maintype= ATYPE;
11206: modell[k].subtype= APVQ; /* Product age * varying quantitative */
11207: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11208: }
1.339 brouard 11209: }else if (Typevar[k] == 2) { /* product 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 */
11210: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11211: /* model V1+V3+age*V1+age*V3+V1*V3 */
11212: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11213: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1} k1=1 first product but second time varying because of V3 */
11214: ncovvt++;
11215: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11216: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11217: ncovvt++;
11218: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11219: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11220:
11221:
11222: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11223: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.240 brouard 11224: Fixed[k]= 1;
11225: Dummy[k]= 0;
11226: modell[k].maintype= FTYPE;
11227: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11228: ncovf++; /* Fixed variables without age */
11229: TvarF[ncovf]=Tvar[k];
11230: TvarFind[ncovf]=k;
1.339 brouard 11231: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11232: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11233: Dummy[k]= 1;
11234: modell[k].maintype= FTYPE;
11235: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11236: ncovf++; /* Varying variables without age */
11237: TvarF[ncovf]=Tvar[k];
11238: TvarFind[ncovf]=k;
1.339 brouard 11239: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.240 brouard 11240: Fixed[k]= 1;
11241: Dummy[k]= 0;
11242: modell[k].maintype= VTYPE;
11243: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11244: ncovv++; /* Varying variables without age */
1.339 brouard 11245: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11246: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11247: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.240 brouard 11248: Fixed[k]= 1;
11249: Dummy[k]= 1;
11250: modell[k].maintype= VTYPE;
11251: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11252: ncovv++; /* Varying variables without age */
11253: TvarV[ncovv]=Tvar[k];
11254: TvarVind[ncovv]=k;
11255: }
1.339 brouard 11256: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11257: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11258: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11259: Dummy[k]= 1;
11260: modell[k].maintype= FTYPE;
11261: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11262: ncovf++; /* Fixed variables without age */
11263: TvarF[ncovf]=Tvar[k];
11264: TvarFind[ncovf]=k;
1.339 brouard 11265: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.240 brouard 11266: Fixed[k]= 1;
11267: Dummy[k]= 1;
11268: modell[k].maintype= VTYPE;
11269: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11270: ncovv++; /* Varying variables without age */
11271: TvarV[ncovv]=Tvar[k];
11272: TvarVind[ncovv]=k;
1.339 brouard 11273: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.240 brouard 11274: Fixed[k]= 1;
11275: Dummy[k]= 1;
11276: modell[k].maintype= VTYPE;
11277: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11278: ncovv++; /* Varying variables without age */
11279: TvarV[ncovv]=Tvar[k];
11280: TvarVind[ncovv]=k;
11281: ncovv++; /* Varying variables without age */
11282: TvarV[ncovv]=Tvar[k];
11283: TvarVind[ncovv]=k;
11284: }
1.339 brouard 11285: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 11286: if(Tvard[k1][2] <=ncovcol){
11287: Fixed[k]= 1;
11288: Dummy[k]= 1;
11289: modell[k].maintype= VTYPE;
11290: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11291: ncovv++; /* Varying variables without age */
11292: TvarV[ncovv]=Tvar[k];
11293: TvarVind[ncovv]=k;
11294: }else if(Tvard[k1][2] <=ncovcol+nqv){
11295: Fixed[k]= 1;
11296: Dummy[k]= 1;
11297: modell[k].maintype= VTYPE;
11298: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11299: ncovv++; /* Varying variables without age */
11300: TvarV[ncovv]=Tvar[k];
11301: TvarVind[ncovv]=k;
11302: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11303: Fixed[k]= 1;
11304: Dummy[k]= 0;
11305: modell[k].maintype= VTYPE;
11306: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
11307: ncovv++; /* Varying variables without age */
11308: TvarV[ncovv]=Tvar[k];
11309: TvarVind[ncovv]=k;
11310: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11311: Fixed[k]= 1;
11312: Dummy[k]= 1;
11313: modell[k].maintype= VTYPE;
11314: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
11315: ncovv++; /* Varying variables without age */
11316: TvarV[ncovv]=Tvar[k];
11317: TvarVind[ncovv]=k;
11318: }
1.339 brouard 11319: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 11320: if(Tvard[k1][2] <=ncovcol){
11321: Fixed[k]= 1;
11322: Dummy[k]= 1;
11323: modell[k].maintype= VTYPE;
11324: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
11325: ncovv++; /* Varying variables without age */
11326: TvarV[ncovv]=Tvar[k];
11327: TvarVind[ncovv]=k;
11328: }else if(Tvard[k1][2] <=ncovcol+nqv){
11329: Fixed[k]= 1;
11330: Dummy[k]= 1;
11331: modell[k].maintype= VTYPE;
11332: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
11333: ncovv++; /* Varying variables without age */
11334: TvarV[ncovv]=Tvar[k];
11335: TvarVind[ncovv]=k;
11336: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11337: Fixed[k]= 1;
11338: Dummy[k]= 1;
11339: modell[k].maintype= VTYPE;
11340: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
11341: ncovv++; /* Varying variables without age */
11342: TvarV[ncovv]=Tvar[k];
11343: TvarVind[ncovv]=k;
11344: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11345: Fixed[k]= 1;
11346: Dummy[k]= 1;
11347: modell[k].maintype= VTYPE;
11348: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
11349: ncovv++; /* Varying variables without age */
11350: TvarV[ncovv]=Tvar[k];
11351: TvarVind[ncovv]=k;
11352: }
1.227 brouard 11353: }else{
1.240 brouard 11354: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11355: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11356: } /*end k1*/
1.225 brouard 11357: }else{
1.226 brouard 11358: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
11359: 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 11360: }
1.227 brouard 11361: 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]);
1.231 brouard 11362: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 11363: 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]);
11364: }
11365: /* Searching for doublons in the model */
11366: for(k1=1; k1<= cptcovt;k1++){
11367: for(k2=1; k2 <k1;k2++){
1.285 brouard 11368: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
11369: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 11370: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
11371: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 11372: 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]);
11373: 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 11374: return(1);
11375: }
11376: }else if (Typevar[k1] ==2){
11377: k3=Tposprod[k1];
11378: k4=Tposprod[k2];
11379: 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 11380: 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]]);
11381: 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 11382: return(1);
11383: }
11384: }
1.227 brouard 11385: }
11386: }
1.225 brouard 11387: }
11388: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
11389: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 11390: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
11391: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 11392: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 11393: /*endread:*/
1.225 brouard 11394: printf("Exiting decodemodel: ");
11395: return (1);
1.136 brouard 11396: }
11397:
1.169 brouard 11398: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 11399: {/* Check ages at death */
1.136 brouard 11400: int i, m;
1.218 brouard 11401: int firstone=0;
11402:
1.136 brouard 11403: for (i=1; i<=imx; i++) {
11404: for(m=2; (m<= maxwav); m++) {
11405: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
11406: anint[m][i]=9999;
1.216 brouard 11407: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
11408: s[m][i]=-1;
1.136 brouard 11409: }
11410: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 11411: *nberr = *nberr + 1;
1.218 brouard 11412: if(firstone == 0){
11413: firstone=1;
1.260 brouard 11414: 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 11415: }
1.262 brouard 11416: 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 11417: s[m][i]=-1; /* Droping the death status */
1.136 brouard 11418: }
11419: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 11420: (*nberr)++;
1.259 brouard 11421: 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 11422: 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 11423: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 11424: }
11425: }
11426: }
11427:
11428: for (i=1; i<=imx; i++) {
11429: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
11430: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 11431: 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 11432: if (s[m][i] >= nlstate+1) {
1.169 brouard 11433: if(agedc[i]>0){
11434: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 11435: agev[m][i]=agedc[i];
1.214 brouard 11436: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 11437: }else {
1.136 brouard 11438: if ((int)andc[i]!=9999){
11439: nbwarn++;
11440: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
11441: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
11442: agev[m][i]=-1;
11443: }
11444: }
1.169 brouard 11445: } /* agedc > 0 */
1.214 brouard 11446: } /* end if */
1.136 brouard 11447: else if(s[m][i] !=9){ /* Standard case, age in fractional
11448: years but with the precision of a month */
11449: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
11450: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
11451: agev[m][i]=1;
11452: else if(agev[m][i] < *agemin){
11453: *agemin=agev[m][i];
11454: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
11455: }
11456: else if(agev[m][i] >*agemax){
11457: *agemax=agev[m][i];
1.156 brouard 11458: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 11459: }
11460: /*agev[m][i]=anint[m][i]-annais[i];*/
11461: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 11462: } /* en if 9*/
1.136 brouard 11463: else { /* =9 */
1.214 brouard 11464: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 11465: agev[m][i]=1;
11466: s[m][i]=-1;
11467: }
11468: }
1.214 brouard 11469: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 11470: agev[m][i]=1;
1.214 brouard 11471: else{
11472: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11473: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11474: agev[m][i]=0;
11475: }
11476: } /* End for lastpass */
11477: }
1.136 brouard 11478:
11479: for (i=1; i<=imx; i++) {
11480: for(m=firstpass; (m<=lastpass); m++){
11481: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 11482: (*nberr)++;
1.136 brouard 11483: 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);
11484: 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);
11485: return 1;
11486: }
11487: }
11488: }
11489:
11490: /*for (i=1; i<=imx; i++){
11491: for (m=firstpass; (m<lastpass); m++){
11492: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
11493: }
11494:
11495: }*/
11496:
11497:
1.139 brouard 11498: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
11499: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 11500:
11501: return (0);
1.164 brouard 11502: /* endread:*/
1.136 brouard 11503: printf("Exiting calandcheckages: ");
11504: return (1);
11505: }
11506:
1.172 brouard 11507: #if defined(_MSC_VER)
11508: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11509: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11510: //#include "stdafx.h"
11511: //#include <stdio.h>
11512: //#include <tchar.h>
11513: //#include <windows.h>
11514: //#include <iostream>
11515: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
11516:
11517: LPFN_ISWOW64PROCESS fnIsWow64Process;
11518:
11519: BOOL IsWow64()
11520: {
11521: BOOL bIsWow64 = FALSE;
11522:
11523: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
11524: // (HANDLE, PBOOL);
11525:
11526: //LPFN_ISWOW64PROCESS fnIsWow64Process;
11527:
11528: HMODULE module = GetModuleHandle(_T("kernel32"));
11529: const char funcName[] = "IsWow64Process";
11530: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
11531: GetProcAddress(module, funcName);
11532:
11533: if (NULL != fnIsWow64Process)
11534: {
11535: if (!fnIsWow64Process(GetCurrentProcess(),
11536: &bIsWow64))
11537: //throw std::exception("Unknown error");
11538: printf("Unknown error\n");
11539: }
11540: return bIsWow64 != FALSE;
11541: }
11542: #endif
1.177 brouard 11543:
1.191 brouard 11544: void syscompilerinfo(int logged)
1.292 brouard 11545: {
11546: #include <stdint.h>
11547:
11548: /* #include "syscompilerinfo.h"*/
1.185 brouard 11549: /* command line Intel compiler 32bit windows, XP compatible:*/
11550: /* /GS /W3 /Gy
11551: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
11552: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
11553: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 11554: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
11555: */
11556: /* 64 bits */
1.185 brouard 11557: /*
11558: /GS /W3 /Gy
11559: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
11560: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
11561: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
11562: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
11563: /* Optimization are useless and O3 is slower than O2 */
11564: /*
11565: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
11566: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
11567: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
11568: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
11569: */
1.186 brouard 11570: /* Link is */ /* /OUT:"visual studio
1.185 brouard 11571: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
11572: /PDB:"visual studio
11573: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
11574: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
11575: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
11576: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
11577: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
11578: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
11579: uiAccess='false'"
11580: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
11581: /NOLOGO /TLBID:1
11582: */
1.292 brouard 11583:
11584:
1.177 brouard 11585: #if defined __INTEL_COMPILER
1.178 brouard 11586: #if defined(__GNUC__)
11587: struct utsname sysInfo; /* For Intel on Linux and OS/X */
11588: #endif
1.177 brouard 11589: #elif defined(__GNUC__)
1.179 brouard 11590: #ifndef __APPLE__
1.174 brouard 11591: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 11592: #endif
1.177 brouard 11593: struct utsname sysInfo;
1.178 brouard 11594: int cross = CROSS;
11595: if (cross){
11596: printf("Cross-");
1.191 brouard 11597: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 11598: }
1.174 brouard 11599: #endif
11600:
1.191 brouard 11601: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 11602: #if defined(__clang__)
1.191 brouard 11603: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 11604: #endif
11605: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 11606: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 11607: #endif
11608: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 11609: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 11610: #endif
11611: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 11612: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 11613: #endif
11614: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 11615: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 11616: #endif
11617: #if defined(_MSC_VER)
1.191 brouard 11618: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 11619: #endif
11620: #if defined(__PGI)
1.191 brouard 11621: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 11622: #endif
11623: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 11624: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 11625: #endif
1.191 brouard 11626: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 11627:
1.167 brouard 11628: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
11629: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
11630: // Windows (x64 and x86)
1.191 brouard 11631: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 11632: #elif __unix__ // all unices, not all compilers
11633: // Unix
1.191 brouard 11634: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 11635: #elif __linux__
11636: // linux
1.191 brouard 11637: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 11638: #elif __APPLE__
1.174 brouard 11639: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 11640: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 11641: #endif
11642:
11643: /* __MINGW32__ */
11644: /* __CYGWIN__ */
11645: /* __MINGW64__ */
11646: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
11647: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
11648: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
11649: /* _WIN64 // Defined for applications for Win64. */
11650: /* _M_X64 // Defined for compilations that target x64 processors. */
11651: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 11652:
1.167 brouard 11653: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 11654: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 11655: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 11656: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 11657: #else
1.191 brouard 11658: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 11659: #endif
11660:
1.169 brouard 11661: #if defined(__GNUC__)
11662: # if defined(__GNUC_PATCHLEVEL__)
11663: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11664: + __GNUC_MINOR__ * 100 \
11665: + __GNUC_PATCHLEVEL__)
11666: # else
11667: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11668: + __GNUC_MINOR__ * 100)
11669: # endif
1.174 brouard 11670: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 11671: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 11672:
11673: if (uname(&sysInfo) != -1) {
11674: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 11675: 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 11676: }
11677: else
11678: perror("uname() error");
1.179 brouard 11679: //#ifndef __INTEL_COMPILER
11680: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 11681: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 11682: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 11683: #endif
1.169 brouard 11684: #endif
1.172 brouard 11685:
1.286 brouard 11686: // void main ()
1.172 brouard 11687: // {
1.169 brouard 11688: #if defined(_MSC_VER)
1.174 brouard 11689: if (IsWow64()){
1.191 brouard 11690: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
11691: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 11692: }
11693: else{
1.191 brouard 11694: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
11695: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 11696: }
1.172 brouard 11697: // printf("\nPress Enter to continue...");
11698: // getchar();
11699: // }
11700:
1.169 brouard 11701: #endif
11702:
1.167 brouard 11703:
1.219 brouard 11704: }
1.136 brouard 11705:
1.219 brouard 11706: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 11707: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 11708: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 11709: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 11710: /* double ftolpl = 1.e-10; */
1.180 brouard 11711: double age, agebase, agelim;
1.203 brouard 11712: double tot;
1.180 brouard 11713:
1.202 brouard 11714: strcpy(filerespl,"PL_");
11715: strcat(filerespl,fileresu);
11716: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 11717: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
11718: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11719: }
1.288 brouard 11720: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11721: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11722: pstamp(ficrespl);
1.288 brouard 11723: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11724: fprintf(ficrespl,"#Age ");
11725: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11726: fprintf(ficrespl,"\n");
1.180 brouard 11727:
1.219 brouard 11728: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11729:
1.219 brouard 11730: agebase=ageminpar;
11731: agelim=agemaxpar;
1.180 brouard 11732:
1.227 brouard 11733: /* i1=pow(2,ncoveff); */
1.234 brouard 11734: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11735: if (cptcovn < 1){i1=1;}
1.180 brouard 11736:
1.337 brouard 11737: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 11738: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 11739: k=TKresult[nres];
1.338 brouard 11740: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11741: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
11742: /* continue; */
1.235 brouard 11743:
1.238 brouard 11744: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11745: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11746: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11747: /* k=k+1; */
11748: /* to clean */
1.332 brouard 11749: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11750: fprintf(ficrespl,"#******");
11751: printf("#******");
11752: fprintf(ficlog,"#******");
1.337 brouard 11753: 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 11754: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 11755: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11756: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11757: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11758: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11759: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11760: }
11761: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11762: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11763: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11764: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11765: /* } */
1.238 brouard 11766: fprintf(ficrespl,"******\n");
11767: printf("******\n");
11768: fprintf(ficlog,"******\n");
11769: if(invalidvarcomb[k]){
11770: printf("\nCombination (%d) ignored because no case \n",k);
11771: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
11772: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
11773: continue;
11774: }
1.219 brouard 11775:
1.238 brouard 11776: fprintf(ficrespl,"#Age ");
1.337 brouard 11777: /* for(j=1;j<=cptcoveff;j++) { */
11778: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11779: /* } */
11780: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
11781: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11782: }
11783: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
11784: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 11785:
1.238 brouard 11786: for (age=agebase; age<=agelim; age++){
11787: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 11788: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
11789: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 11790: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 11791: /* for(j=1;j<=cptcoveff;j++) */
11792: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11793: for(j=1;j<=cptcovs;j++)
11794: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11795: tot=0.;
11796: for(i=1; i<=nlstate;i++){
11797: tot += prlim[i][i];
11798: fprintf(ficrespl," %.5f", prlim[i][i]);
11799: }
11800: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
11801: } /* Age */
11802: /* was end of cptcod */
1.337 brouard 11803: } /* nres */
11804: /* } /\* for each combination *\/ */
1.219 brouard 11805: return 0;
1.180 brouard 11806: }
11807:
1.218 brouard 11808: 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 11809: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 11810:
11811: /* Computes the back prevalence limit for any combination of covariate values
11812: * at any age between ageminpar and agemaxpar
11813: */
1.235 brouard 11814: int i, j, k, i1, nres=0 ;
1.217 brouard 11815: /* double ftolpl = 1.e-10; */
11816: double age, agebase, agelim;
11817: double tot;
1.218 brouard 11818: /* double ***mobaverage; */
11819: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 11820:
11821: strcpy(fileresplb,"PLB_");
11822: strcat(fileresplb,fileresu);
11823: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 11824: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
11825: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 11826: }
1.288 brouard 11827: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
11828: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 11829: pstamp(ficresplb);
1.288 brouard 11830: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 11831: fprintf(ficresplb,"#Age ");
11832: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
11833: fprintf(ficresplb,"\n");
11834:
1.218 brouard 11835:
11836: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
11837:
11838: agebase=ageminpar;
11839: agelim=agemaxpar;
11840:
11841:
1.227 brouard 11842: i1=pow(2,cptcoveff);
1.218 brouard 11843: if (cptcovn < 1){i1=1;}
1.227 brouard 11844:
1.238 brouard 11845: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 11846: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
11847: k=TKresult[nres];
11848: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11849: /* if(i1 != 1 && TKresult[nres]!= k) */
11850: /* continue; */
11851: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 11852: fprintf(ficresplb,"#******");
11853: printf("#******");
11854: fprintf(ficlog,"#******");
1.338 brouard 11855: 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) */
11856: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11857: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11858: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11859: }
1.338 brouard 11860: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
11861: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11862: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11863: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11864: /* } */
11865: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11866: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11867: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11868: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11869: /* } */
1.238 brouard 11870: fprintf(ficresplb,"******\n");
11871: printf("******\n");
11872: fprintf(ficlog,"******\n");
11873: if(invalidvarcomb[k]){
11874: printf("\nCombination (%d) ignored because no cases \n",k);
11875: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
11876: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
11877: continue;
11878: }
1.218 brouard 11879:
1.238 brouard 11880: fprintf(ficresplb,"#Age ");
1.338 brouard 11881: for(j=1;j<=cptcovs;j++) {
11882: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11883: }
11884: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
11885: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 11886:
11887:
1.238 brouard 11888: for (age=agebase; age<=agelim; age++){
11889: /* for (age=agebase; age<=agebase; age++){ */
11890: if(mobilavproj > 0){
11891: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11892: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11893: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11894: }else if (mobilavproj == 0){
11895: 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);
11896: 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);
11897: exit(1);
11898: }else{
11899: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11900: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11901: /* printf("TOTOT\n"); */
11902: /* exit(1); */
1.238 brouard 11903: }
11904: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 11905: for(j=1;j<=cptcovs;j++)
11906: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11907: tot=0.;
11908: for(i=1; i<=nlstate;i++){
11909: tot += bprlim[i][i];
11910: fprintf(ficresplb," %.5f", bprlim[i][i]);
11911: }
11912: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11913: } /* Age */
11914: /* was end of cptcod */
1.255 brouard 11915: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 11916: /* } /\* end of any combination *\/ */
1.238 brouard 11917: } /* end of nres */
1.218 brouard 11918: /* hBijx(p, bage, fage); */
11919: /* fclose(ficrespijb); */
11920:
11921: return 0;
1.217 brouard 11922: }
1.218 brouard 11923:
1.180 brouard 11924: int hPijx(double *p, int bage, int fage){
11925: /*------------- h Pij x at various ages ------------*/
1.336 brouard 11926: /* to be optimized with precov */
1.180 brouard 11927: int stepsize;
11928: int agelim;
11929: int hstepm;
11930: int nhstepm;
1.235 brouard 11931: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11932:
11933: double agedeb;
11934: double ***p3mat;
11935:
1.337 brouard 11936: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
11937: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11938: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11939: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11940: }
11941: printf("Computing pij: result on file '%s' \n", filerespij);
11942: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11943:
11944: stepsize=(int) (stepm+YEARM-1)/YEARM;
11945: /*if (stepm<=24) stepsize=2;*/
11946:
11947: agelim=AGESUP;
11948: hstepm=stepsize*YEARM; /* Every year of age */
11949: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11950:
11951: /* hstepm=1; aff par mois*/
11952: pstamp(ficrespij);
11953: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
11954: i1= pow(2,cptcoveff);
11955: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11956: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11957: /* k=k+1; */
11958: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11959: k=TKresult[nres];
1.338 brouard 11960: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11961: /* for(k=1; k<=i1;k++){ */
11962: /* if(i1 != 1 && TKresult[nres]!= k) */
11963: /* continue; */
11964: fprintf(ficrespij,"\n#****** ");
11965: for(j=1;j<=cptcovs;j++){
11966: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11967: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11968: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11969: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11970: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11971: }
11972: fprintf(ficrespij,"******\n");
11973:
11974: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11975: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11976: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11977:
11978: /* nhstepm=nhstepm*YEARM; aff par mois*/
11979:
11980: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11981: oldm=oldms;savm=savms;
11982: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
11983: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11984: for(i=1; i<=nlstate;i++)
11985: for(j=1; j<=nlstate+ndeath;j++)
11986: fprintf(ficrespij," %1d-%1d",i,j);
11987: fprintf(ficrespij,"\n");
11988: for (h=0; h<=nhstepm; h++){
11989: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11990: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 11991: for(i=1; i<=nlstate;i++)
11992: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 11993: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 11994: fprintf(ficrespij,"\n");
11995: }
1.337 brouard 11996: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11997: fprintf(ficrespij,"\n");
1.180 brouard 11998: }
1.337 brouard 11999: }
12000: /*}*/
12001: return 0;
1.180 brouard 12002: }
1.218 brouard 12003:
12004: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12005: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12006: /* To be optimized with precov */
1.217 brouard 12007: int stepsize;
1.218 brouard 12008: /* int agelim; */
12009: int ageminl;
1.217 brouard 12010: int hstepm;
12011: int nhstepm;
1.238 brouard 12012: int h, i, i1, j, k, nres;
1.218 brouard 12013:
1.217 brouard 12014: double agedeb;
12015: double ***p3mat;
1.218 brouard 12016:
12017: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12018: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12019: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12020: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12021: }
12022: printf("Computing pij back: result on file '%s' \n", filerespijb);
12023: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12024:
12025: stepsize=(int) (stepm+YEARM-1)/YEARM;
12026: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12027:
1.218 brouard 12028: /* agelim=AGESUP; */
1.289 brouard 12029: ageminl=AGEINF; /* was 30 */
1.218 brouard 12030: hstepm=stepsize*YEARM; /* Every year of age */
12031: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12032:
12033: /* hstepm=1; aff par mois*/
12034: pstamp(ficrespijb);
1.255 brouard 12035: 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 12036: i1= pow(2,cptcoveff);
1.218 brouard 12037: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12038: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12039: /* k=k+1; */
1.238 brouard 12040: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12041: k=TKresult[nres];
1.338 brouard 12042: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12043: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12044: /* if(i1 != 1 && TKresult[nres]!= k) */
12045: /* continue; */
12046: fprintf(ficrespijb,"\n#****** ");
12047: for(j=1;j<=cptcovs;j++){
1.338 brouard 12048: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12049: /* for(j=1;j<=cptcoveff;j++) */
12050: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12051: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12052: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12053: }
12054: fprintf(ficrespijb,"******\n");
12055: if(invalidvarcomb[k]){ /* Is it necessary here? */
12056: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12057: continue;
12058: }
12059:
12060: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12061: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12062: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12063: 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 */
12064: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12065:
12066: /* nhstepm=nhstepm*YEARM; aff par mois*/
12067:
12068: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12069: /* and memory limitations if stepm is small */
12070:
12071: /* oldm=oldms;savm=savms; */
12072: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12073: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12074: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12075: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12076: for(i=1; i<=nlstate;i++)
12077: for(j=1; j<=nlstate+ndeath;j++)
12078: fprintf(ficrespijb," %1d-%1d",i,j);
12079: fprintf(ficrespijb,"\n");
12080: for (h=0; h<=nhstepm; h++){
12081: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12082: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12083: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12084: for(i=1; i<=nlstate;i++)
12085: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12086: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12087: fprintf(ficrespijb,"\n");
1.337 brouard 12088: }
12089: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12090: fprintf(ficrespijb,"\n");
12091: } /* end age deb */
12092: /* } /\* end combination *\/ */
1.238 brouard 12093: } /* end nres */
1.218 brouard 12094: return 0;
12095: } /* hBijx */
1.217 brouard 12096:
1.180 brouard 12097:
1.136 brouard 12098: /***********************************************/
12099: /**************** Main Program *****************/
12100: /***********************************************/
12101:
12102: int main(int argc, char *argv[])
12103: {
12104: #ifdef GSL
12105: const gsl_multimin_fminimizer_type *T;
12106: size_t iteri = 0, it;
12107: int rval = GSL_CONTINUE;
12108: int status = GSL_SUCCESS;
12109: double ssval;
12110: #endif
12111: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12112: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12113: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12114: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12115: int jj, ll, li, lj, lk;
1.136 brouard 12116: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12117: int num_filled;
1.136 brouard 12118: int itimes;
12119: int NDIM=2;
12120: int vpopbased=0;
1.235 brouard 12121: int nres=0;
1.258 brouard 12122: int endishere=0;
1.277 brouard 12123: int noffset=0;
1.274 brouard 12124: int ncurrv=0; /* Temporary variable */
12125:
1.164 brouard 12126: char ca[32], cb[32];
1.136 brouard 12127: /* FILE *fichtm; *//* Html File */
12128: /* FILE *ficgp;*/ /*Gnuplot File */
12129: struct stat info;
1.191 brouard 12130: double agedeb=0.;
1.194 brouard 12131:
12132: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 12133: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 12134:
1.165 brouard 12135: double fret;
1.191 brouard 12136: double dum=0.; /* Dummy variable */
1.136 brouard 12137: double ***p3mat;
1.218 brouard 12138: /* double ***mobaverage; */
1.319 brouard 12139: double wald;
1.164 brouard 12140:
12141: char line[MAXLINE];
1.197 brouard 12142: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
12143:
1.234 brouard 12144: char modeltemp[MAXLINE];
1.332 brouard 12145: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 12146:
1.136 brouard 12147: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 12148: char *tok, *val; /* pathtot */
1.334 brouard 12149: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 12150: int c, h , cpt, c2;
1.191 brouard 12151: int jl=0;
12152: int i1, j1, jk, stepsize=0;
1.194 brouard 12153: int count=0;
12154:
1.164 brouard 12155: int *tab;
1.136 brouard 12156: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 12157: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
12158: /* double anprojf, mprojf, jprojf; */
12159: /* double jintmean,mintmean,aintmean; */
12160: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12161: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12162: double yrfproj= 10.0; /* Number of years of forward projections */
12163: double yrbproj= 10.0; /* Number of years of backward projections */
12164: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 12165: int mobilav=0,popforecast=0;
1.191 brouard 12166: int hstepm=0, nhstepm=0;
1.136 brouard 12167: int agemortsup;
12168: float sumlpop=0.;
12169: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
12170: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
12171:
1.191 brouard 12172: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 12173: double ftolpl=FTOL;
12174: double **prlim;
1.217 brouard 12175: double **bprlim;
1.317 brouard 12176: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
12177: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 12178: double ***paramstart; /* Matrix of starting parameter values */
12179: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 12180: double **matcov; /* Matrix of covariance */
1.203 brouard 12181: double **hess; /* Hessian matrix */
1.136 brouard 12182: double ***delti3; /* Scale */
12183: double *delti; /* Scale */
12184: double ***eij, ***vareij;
12185: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 12186:
1.136 brouard 12187: double *epj, vepp;
1.164 brouard 12188:
1.273 brouard 12189: double dateprev1, dateprev2;
1.296 brouard 12190: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
12191: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
12192:
1.217 brouard 12193:
1.136 brouard 12194: double **ximort;
1.145 brouard 12195: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 12196: int *dcwave;
12197:
1.164 brouard 12198: char z[1]="c";
1.136 brouard 12199:
12200: /*char *strt;*/
12201: char strtend[80];
1.126 brouard 12202:
1.164 brouard 12203:
1.126 brouard 12204: /* setlocale (LC_ALL, ""); */
12205: /* bindtextdomain (PACKAGE, LOCALEDIR); */
12206: /* textdomain (PACKAGE); */
12207: /* setlocale (LC_CTYPE, ""); */
12208: /* setlocale (LC_MESSAGES, ""); */
12209:
12210: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 12211: rstart_time = time(NULL);
12212: /* (void) gettimeofday(&start_time,&tzp);*/
12213: start_time = *localtime(&rstart_time);
1.126 brouard 12214: curr_time=start_time;
1.157 brouard 12215: /*tml = *localtime(&start_time.tm_sec);*/
12216: /* strcpy(strstart,asctime(&tml)); */
12217: strcpy(strstart,asctime(&start_time));
1.126 brouard 12218:
12219: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 12220: /* tp.tm_sec = tp.tm_sec +86400; */
12221: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 12222: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
12223: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
12224: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 12225: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 12226: /* strt=asctime(&tmg); */
12227: /* printf("Time(after) =%s",strstart); */
12228: /* (void) time (&time_value);
12229: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
12230: * tm = *localtime(&time_value);
12231: * strstart=asctime(&tm);
12232: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
12233: */
12234:
12235: nberr=0; /* Number of errors and warnings */
12236: nbwarn=0;
1.184 brouard 12237: #ifdef WIN32
12238: _getcwd(pathcd, size);
12239: #else
1.126 brouard 12240: getcwd(pathcd, size);
1.184 brouard 12241: #endif
1.191 brouard 12242: syscompilerinfo(0);
1.196 brouard 12243: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 12244: if(argc <=1){
12245: printf("\nEnter the parameter file name: ");
1.205 brouard 12246: if(!fgets(pathr,FILENAMELENGTH,stdin)){
12247: printf("ERROR Empty parameter file name\n");
12248: goto end;
12249: }
1.126 brouard 12250: i=strlen(pathr);
12251: if(pathr[i-1]=='\n')
12252: pathr[i-1]='\0';
1.156 brouard 12253: i=strlen(pathr);
1.205 brouard 12254: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 12255: pathr[i-1]='\0';
1.205 brouard 12256: }
12257: i=strlen(pathr);
12258: if( i==0 ){
12259: printf("ERROR Empty parameter file name\n");
12260: goto end;
12261: }
12262: for (tok = pathr; tok != NULL; ){
1.126 brouard 12263: printf("Pathr |%s|\n",pathr);
12264: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
12265: printf("val= |%s| pathr=%s\n",val,pathr);
12266: strcpy (pathtot, val);
12267: if(pathr[0] == '\0') break; /* Dirty */
12268: }
12269: }
1.281 brouard 12270: else if (argc<=2){
12271: strcpy(pathtot,argv[1]);
12272: }
1.126 brouard 12273: else{
12274: strcpy(pathtot,argv[1]);
1.281 brouard 12275: strcpy(z,argv[2]);
12276: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 12277: }
12278: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
12279: /*cygwin_split_path(pathtot,path,optionfile);
12280: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
12281: /* cutv(path,optionfile,pathtot,'\\');*/
12282:
12283: /* Split argv[0], imach program to get pathimach */
12284: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
12285: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12286: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12287: /* strcpy(pathimach,argv[0]); */
12288: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
12289: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
12290: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 12291: #ifdef WIN32
12292: _chdir(path); /* Can be a relative path */
12293: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
12294: #else
1.126 brouard 12295: chdir(path); /* Can be a relative path */
1.184 brouard 12296: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
12297: #endif
12298: printf("Current directory %s!\n",pathcd);
1.126 brouard 12299: strcpy(command,"mkdir ");
12300: strcat(command,optionfilefiname);
12301: if((outcmd=system(command)) != 0){
1.169 brouard 12302: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 12303: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
12304: /* fclose(ficlog); */
12305: /* exit(1); */
12306: }
12307: /* if((imk=mkdir(optionfilefiname))<0){ */
12308: /* perror("mkdir"); */
12309: /* } */
12310:
12311: /*-------- arguments in the command line --------*/
12312:
1.186 brouard 12313: /* Main Log file */
1.126 brouard 12314: strcat(filelog, optionfilefiname);
12315: strcat(filelog,".log"); /* */
12316: if((ficlog=fopen(filelog,"w"))==NULL) {
12317: printf("Problem with logfile %s\n",filelog);
12318: goto end;
12319: }
12320: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 12321: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 12322: fprintf(ficlog,"\nEnter the parameter file name: \n");
12323: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
12324: path=%s \n\
12325: optionfile=%s\n\
12326: optionfilext=%s\n\
1.156 brouard 12327: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 12328:
1.197 brouard 12329: syscompilerinfo(1);
1.167 brouard 12330:
1.126 brouard 12331: printf("Local time (at start):%s",strstart);
12332: fprintf(ficlog,"Local time (at start): %s",strstart);
12333: fflush(ficlog);
12334: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 12335: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 12336:
12337: /* */
12338: strcpy(fileres,"r");
12339: strcat(fileres, optionfilefiname);
1.201 brouard 12340: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 12341: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 12342: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 12343:
1.186 brouard 12344: /* Main ---------arguments file --------*/
1.126 brouard 12345:
12346: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 12347: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
12348: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 12349: fflush(ficlog);
1.149 brouard 12350: /* goto end; */
12351: exit(70);
1.126 brouard 12352: }
12353:
12354: strcpy(filereso,"o");
1.201 brouard 12355: strcat(filereso,fileresu);
1.126 brouard 12356: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
12357: printf("Problem with Output resultfile: %s\n", filereso);
12358: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
12359: fflush(ficlog);
12360: goto end;
12361: }
1.278 brouard 12362: /*-------- Rewriting parameter file ----------*/
12363: strcpy(rfileres,"r"); /* "Rparameterfile */
12364: strcat(rfileres,optionfilefiname); /* Parameter file first name */
12365: strcat(rfileres,"."); /* */
12366: strcat(rfileres,optionfilext); /* Other files have txt extension */
12367: if((ficres =fopen(rfileres,"w"))==NULL) {
12368: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
12369: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
12370: fflush(ficlog);
12371: goto end;
12372: }
12373: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 12374:
1.278 brouard 12375:
1.126 brouard 12376: /* Reads comments: lines beginning with '#' */
12377: numlinepar=0;
1.277 brouard 12378: /* Is it a BOM UTF-8 Windows file? */
12379: /* First parameter line */
1.197 brouard 12380: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 12381: noffset=0;
12382: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12383: {
12384: noffset=noffset+3;
12385: printf("# File is an UTF8 Bom.\n"); // 0xBF
12386: }
1.302 brouard 12387: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12388: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 12389: {
12390: noffset=noffset+2;
12391: printf("# File is an UTF16BE BOM file\n");
12392: }
12393: else if( line[0] == 0 && line[1] == 0)
12394: {
12395: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12396: noffset=noffset+4;
12397: printf("# File is an UTF16BE BOM file\n");
12398: }
12399: } else{
12400: ;/*printf(" Not a BOM file\n");*/
12401: }
12402:
1.197 brouard 12403: /* If line starts with a # it is a comment */
1.277 brouard 12404: if (line[noffset] == '#') {
1.197 brouard 12405: numlinepar++;
12406: fputs(line,stdout);
12407: fputs(line,ficparo);
1.278 brouard 12408: fputs(line,ficres);
1.197 brouard 12409: fputs(line,ficlog);
12410: continue;
12411: }else
12412: break;
12413: }
12414: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
12415: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
12416: if (num_filled != 5) {
12417: printf("Should be 5 parameters\n");
1.283 brouard 12418: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 12419: }
1.126 brouard 12420: numlinepar++;
1.197 brouard 12421: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 12422: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12423: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12424: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 12425: }
12426: /* Second parameter line */
12427: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 12428: /* while(fscanf(ficpar,"%[^\n]", line)) { */
12429: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 12430: if (line[0] == '#') {
12431: numlinepar++;
1.283 brouard 12432: printf("%s",line);
12433: fprintf(ficres,"%s",line);
12434: fprintf(ficparo,"%s",line);
12435: fprintf(ficlog,"%s",line);
1.197 brouard 12436: continue;
12437: }else
12438: break;
12439: }
1.223 brouard 12440: 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", \
12441: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
12442: if (num_filled != 11) {
12443: 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 12444: printf("but line=%s\n",line);
1.283 brouard 12445: 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");
12446: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 12447: }
1.286 brouard 12448: if( lastpass > maxwav){
12449: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12450: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12451: fflush(ficlog);
12452: goto end;
12453: }
12454: 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 12455: 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 12456: 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 12457: 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 12458: }
1.203 brouard 12459: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 12460: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 12461: /* Third parameter line */
12462: while(fgets(line, MAXLINE, ficpar)) {
12463: /* If line starts with a # it is a comment */
12464: if (line[0] == '#') {
12465: numlinepar++;
1.283 brouard 12466: printf("%s",line);
12467: fprintf(ficres,"%s",line);
12468: fprintf(ficparo,"%s",line);
12469: fprintf(ficlog,"%s",line);
1.197 brouard 12470: continue;
12471: }else
12472: break;
12473: }
1.201 brouard 12474: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 12475: if (num_filled != 1){
1.302 brouard 12476: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
12477: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 12478: model[0]='\0';
12479: goto end;
12480: }
12481: else{
12482: if (model[0]=='+'){
12483: for(i=1; i<=strlen(model);i++)
12484: modeltemp[i-1]=model[i];
1.201 brouard 12485: strcpy(model,modeltemp);
1.197 brouard 12486: }
12487: }
1.338 brouard 12488: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 12489: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 12490: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
12491: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
12492: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 12493: }
12494: /* 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); */
12495: /* numlinepar=numlinepar+3; /\* In general *\/ */
12496: /* 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 12497: /* 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); */
12498: /* 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 12499: fflush(ficlog);
1.190 brouard 12500: /* if(model[0]=='#'|| model[0]== '\0'){ */
12501: if(model[0]=='#'){
1.279 brouard 12502: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
12503: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
12504: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 12505: if(mle != -1){
1.279 brouard 12506: 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 12507: exit(1);
12508: }
12509: }
1.126 brouard 12510: while((c=getc(ficpar))=='#' && c!= EOF){
12511: ungetc(c,ficpar);
12512: fgets(line, MAXLINE, ficpar);
12513: numlinepar++;
1.195 brouard 12514: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
12515: z[0]=line[1];
12516: }
12517: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 12518: fputs(line, stdout);
12519: //puts(line);
1.126 brouard 12520: fputs(line,ficparo);
12521: fputs(line,ficlog);
12522: }
12523: ungetc(c,ficpar);
12524:
12525:
1.290 brouard 12526: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
12527: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
12528: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 ! brouard 12529: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
! 12530: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 12531: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
12532: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
12533: v1+v2*age+v2*v3 makes cptcovn = 3
12534: */
12535: if (strlen(model)>1)
1.187 brouard 12536: 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 12537: else
1.187 brouard 12538: ncovmodel=2; /* Constant and age */
1.133 brouard 12539: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
12540: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 12541: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
12542: 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);
12543: 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);
12544: fflush(stdout);
12545: fclose (ficlog);
12546: goto end;
12547: }
1.126 brouard 12548: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12549: delti=delti3[1][1];
12550: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
12551: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 12552: /* We could also provide initial parameters values giving by simple logistic regression
12553: * only one way, that is without matrix product. We will have nlstate maximizations */
12554: /* for(i=1;i<nlstate;i++){ */
12555: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12556: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12557: /* } */
1.126 brouard 12558: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 12559: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
12560: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12561: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12562: fclose (ficparo);
12563: fclose (ficlog);
12564: goto end;
12565: exit(0);
1.220 brouard 12566: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 12567: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 12568: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
12569: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12570: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12571: matcov=matrix(1,npar,1,npar);
1.203 brouard 12572: hess=matrix(1,npar,1,npar);
1.220 brouard 12573: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 12574: /* Read guessed parameters */
1.126 brouard 12575: /* Reads comments: lines beginning with '#' */
12576: while((c=getc(ficpar))=='#' && c!= EOF){
12577: ungetc(c,ficpar);
12578: fgets(line, MAXLINE, ficpar);
12579: numlinepar++;
1.141 brouard 12580: fputs(line,stdout);
1.126 brouard 12581: fputs(line,ficparo);
12582: fputs(line,ficlog);
12583: }
12584: ungetc(c,ficpar);
12585:
12586: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 12587: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 12588: for(i=1; i <=nlstate; i++){
1.234 brouard 12589: j=0;
1.126 brouard 12590: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 12591: if(jj==i) continue;
12592: j++;
1.292 brouard 12593: while((c=getc(ficpar))=='#' && c!= EOF){
12594: ungetc(c,ficpar);
12595: fgets(line, MAXLINE, ficpar);
12596: numlinepar++;
12597: fputs(line,stdout);
12598: fputs(line,ficparo);
12599: fputs(line,ficlog);
12600: }
12601: ungetc(c,ficpar);
1.234 brouard 12602: fscanf(ficpar,"%1d%1d",&i1,&j1);
12603: if ((i1 != i) || (j1 != jj)){
12604: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 12605: It might be a problem of design; if ncovcol and the model are correct\n \
12606: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 12607: exit(1);
12608: }
12609: fprintf(ficparo,"%1d%1d",i1,j1);
12610: if(mle==1)
12611: printf("%1d%1d",i,jj);
12612: fprintf(ficlog,"%1d%1d",i,jj);
12613: for(k=1; k<=ncovmodel;k++){
12614: fscanf(ficpar," %lf",¶m[i][j][k]);
12615: if(mle==1){
12616: printf(" %lf",param[i][j][k]);
12617: fprintf(ficlog," %lf",param[i][j][k]);
12618: }
12619: else
12620: fprintf(ficlog," %lf",param[i][j][k]);
12621: fprintf(ficparo," %lf",param[i][j][k]);
12622: }
12623: fscanf(ficpar,"\n");
12624: numlinepar++;
12625: if(mle==1)
12626: printf("\n");
12627: fprintf(ficlog,"\n");
12628: fprintf(ficparo,"\n");
1.126 brouard 12629: }
12630: }
12631: fflush(ficlog);
1.234 brouard 12632:
1.251 brouard 12633: /* Reads parameters values */
1.126 brouard 12634: p=param[1][1];
1.251 brouard 12635: pstart=paramstart[1][1];
1.126 brouard 12636:
12637: /* Reads comments: lines beginning with '#' */
12638: while((c=getc(ficpar))=='#' && c!= EOF){
12639: ungetc(c,ficpar);
12640: fgets(line, MAXLINE, ficpar);
12641: numlinepar++;
1.141 brouard 12642: fputs(line,stdout);
1.126 brouard 12643: fputs(line,ficparo);
12644: fputs(line,ficlog);
12645: }
12646: ungetc(c,ficpar);
12647:
12648: for(i=1; i <=nlstate; i++){
12649: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 12650: fscanf(ficpar,"%1d%1d",&i1,&j1);
12651: if ( (i1-i) * (j1-j) != 0){
12652: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
12653: exit(1);
12654: }
12655: printf("%1d%1d",i,j);
12656: fprintf(ficparo,"%1d%1d",i1,j1);
12657: fprintf(ficlog,"%1d%1d",i1,j1);
12658: for(k=1; k<=ncovmodel;k++){
12659: fscanf(ficpar,"%le",&delti3[i][j][k]);
12660: printf(" %le",delti3[i][j][k]);
12661: fprintf(ficparo," %le",delti3[i][j][k]);
12662: fprintf(ficlog," %le",delti3[i][j][k]);
12663: }
12664: fscanf(ficpar,"\n");
12665: numlinepar++;
12666: printf("\n");
12667: fprintf(ficparo,"\n");
12668: fprintf(ficlog,"\n");
1.126 brouard 12669: }
12670: }
12671: fflush(ficlog);
1.234 brouard 12672:
1.145 brouard 12673: /* Reads covariance matrix */
1.126 brouard 12674: delti=delti3[1][1];
1.220 brouard 12675:
12676:
1.126 brouard 12677: /* 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 12678:
1.126 brouard 12679: /* Reads comments: lines beginning with '#' */
12680: while((c=getc(ficpar))=='#' && c!= EOF){
12681: ungetc(c,ficpar);
12682: fgets(line, MAXLINE, ficpar);
12683: numlinepar++;
1.141 brouard 12684: fputs(line,stdout);
1.126 brouard 12685: fputs(line,ficparo);
12686: fputs(line,ficlog);
12687: }
12688: ungetc(c,ficpar);
1.220 brouard 12689:
1.126 brouard 12690: matcov=matrix(1,npar,1,npar);
1.203 brouard 12691: hess=matrix(1,npar,1,npar);
1.131 brouard 12692: for(i=1; i <=npar; i++)
12693: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 12694:
1.194 brouard 12695: /* Scans npar lines */
1.126 brouard 12696: for(i=1; i <=npar; i++){
1.226 brouard 12697: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 12698: if(count != 3){
1.226 brouard 12699: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12700: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12701: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12702: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12703: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12704: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12705: exit(1);
1.220 brouard 12706: }else{
1.226 brouard 12707: if(mle==1)
12708: printf("%1d%1d%d",i1,j1,jk);
12709: }
12710: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
12711: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 12712: for(j=1; j <=i; j++){
1.226 brouard 12713: fscanf(ficpar," %le",&matcov[i][j]);
12714: if(mle==1){
12715: printf(" %.5le",matcov[i][j]);
12716: }
12717: fprintf(ficlog," %.5le",matcov[i][j]);
12718: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 12719: }
12720: fscanf(ficpar,"\n");
12721: numlinepar++;
12722: if(mle==1)
1.220 brouard 12723: printf("\n");
1.126 brouard 12724: fprintf(ficlog,"\n");
12725: fprintf(ficparo,"\n");
12726: }
1.194 brouard 12727: /* End of read covariance matrix npar lines */
1.126 brouard 12728: for(i=1; i <=npar; i++)
12729: for(j=i+1;j<=npar;j++)
1.226 brouard 12730: matcov[i][j]=matcov[j][i];
1.126 brouard 12731:
12732: if(mle==1)
12733: printf("\n");
12734: fprintf(ficlog,"\n");
12735:
12736: fflush(ficlog);
12737:
12738: } /* End of mle != -3 */
1.218 brouard 12739:
1.186 brouard 12740: /* Main data
12741: */
1.290 brouard 12742: nobs=lastobs-firstobs+1; /* was = lastobs;*/
12743: /* num=lvector(1,n); */
12744: /* moisnais=vector(1,n); */
12745: /* annais=vector(1,n); */
12746: /* moisdc=vector(1,n); */
12747: /* andc=vector(1,n); */
12748: /* weight=vector(1,n); */
12749: /* agedc=vector(1,n); */
12750: /* cod=ivector(1,n); */
12751: /* for(i=1;i<=n;i++){ */
12752: num=lvector(firstobs,lastobs);
12753: moisnais=vector(firstobs,lastobs);
12754: annais=vector(firstobs,lastobs);
12755: moisdc=vector(firstobs,lastobs);
12756: andc=vector(firstobs,lastobs);
12757: weight=vector(firstobs,lastobs);
12758: agedc=vector(firstobs,lastobs);
12759: cod=ivector(firstobs,lastobs);
12760: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12761: num[i]=0;
12762: moisnais[i]=0;
12763: annais[i]=0;
12764: moisdc[i]=0;
12765: andc[i]=0;
12766: agedc[i]=0;
12767: cod[i]=0;
12768: weight[i]=1.0; /* Equal weights, 1 by default */
12769: }
1.290 brouard 12770: mint=matrix(1,maxwav,firstobs,lastobs);
12771: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 12772: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 12773: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 12774: tab=ivector(1,NCOVMAX);
1.144 brouard 12775: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 12776: 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 12777:
1.136 brouard 12778: /* Reads data from file datafile */
12779: if (readdata(datafile, firstobs, lastobs, &imx)==1)
12780: goto end;
12781:
12782: /* Calculation of the number of parameters from char model */
1.234 brouard 12783: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 12784: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
12785: k=3 V4 Tvar[k=3]= 4 (from V4)
12786: k=2 V1 Tvar[k=2]= 1 (from V1)
12787: k=1 Tvar[1]=2 (from V2)
1.234 brouard 12788: */
12789:
12790: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
12791: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 12792: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 12793: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 12794: TvarsD=ivector(1,NCOVMAX); /* */
12795: TvarsQind=ivector(1,NCOVMAX); /* */
12796: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 12797: TvarF=ivector(1,NCOVMAX); /* */
12798: TvarFind=ivector(1,NCOVMAX); /* */
12799: TvarV=ivector(1,NCOVMAX); /* */
12800: TvarVind=ivector(1,NCOVMAX); /* */
12801: TvarA=ivector(1,NCOVMAX); /* */
12802: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 12803: TvarFD=ivector(1,NCOVMAX); /* */
12804: TvarFDind=ivector(1,NCOVMAX); /* */
12805: TvarFQ=ivector(1,NCOVMAX); /* */
12806: TvarFQind=ivector(1,NCOVMAX); /* */
12807: TvarVD=ivector(1,NCOVMAX); /* */
12808: TvarVDind=ivector(1,NCOVMAX); /* */
12809: TvarVQ=ivector(1,NCOVMAX); /* */
12810: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 12811: TvarVV=ivector(1,NCOVMAX); /* */
12812: TvarVVind=ivector(1,NCOVMAX); /* */
1.231 brouard 12813:
1.230 brouard 12814: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 12815: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 12816: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
12817: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
12818: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 12819: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
12820: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
12821: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
12822: */
12823: /* For model-covariate k tells which data-covariate to use but
12824: because this model-covariate is a construction we invent a new column
12825: ncovcol + k1
12826: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
12827: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 12828: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
12829: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 12830: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
12831: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 12832: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 12833: */
1.145 brouard 12834: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
12835: 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 12836: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
12837: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.330 brouard 12838: Tvardk=imatrix(1,NCOVMAX,1,2);
1.145 brouard 12839: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 12840: 4 covariates (3 plus signs)
12841: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 12842: */
12843: for(i=1;i<NCOVMAX;i++)
12844: Tage[i]=0;
1.230 brouard 12845: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 12846: * individual dummy, fixed or varying:
12847: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
12848: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 12849: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
12850: * V1 df, V2 qf, V3 & V4 dv, V5 qv
12851: * Tmodelind[1]@9={9,0,3,2,}*/
12852: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
12853: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 12854: * individual quantitative, fixed or varying:
12855: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
12856: * 3, 1, 0, 0, 0, 0, 0, 0},
12857: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 12858: /* Main decodemodel */
12859:
1.187 brouard 12860:
1.223 brouard 12861: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 12862: goto end;
12863:
1.137 brouard 12864: if((double)(lastobs-imx)/(double)imx > 1.10){
12865: nbwarn++;
12866: 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);
12867: 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);
12868: }
1.136 brouard 12869: /* if(mle==1){*/
1.137 brouard 12870: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
12871: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 12872: }
12873:
12874: /*-calculation of age at interview from date of interview and age at death -*/
12875: agev=matrix(1,maxwav,1,imx);
12876:
12877: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
12878: goto end;
12879:
1.126 brouard 12880:
1.136 brouard 12881: agegomp=(int)agemin;
1.290 brouard 12882: free_vector(moisnais,firstobs,lastobs);
12883: free_vector(annais,firstobs,lastobs);
1.126 brouard 12884: /* free_matrix(mint,1,maxwav,1,n);
12885: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 12886: /* free_vector(moisdc,1,n); */
12887: /* free_vector(andc,1,n); */
1.145 brouard 12888: /* */
12889:
1.126 brouard 12890: wav=ivector(1,imx);
1.214 brouard 12891: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
12892: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
12893: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
12894: 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.*/
12895: bh=imatrix(1,lastpass-firstpass+2,1,imx);
12896: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 12897:
12898: /* Concatenates waves */
1.214 brouard 12899: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
12900: Death is a valid wave (if date is known).
12901: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
12902: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
12903: and mw[mi+1][i]. dh depends on stepm.
12904: */
12905:
1.126 brouard 12906: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12907: /* Concatenates waves */
1.145 brouard 12908:
1.290 brouard 12909: free_vector(moisdc,firstobs,lastobs);
12910: free_vector(andc,firstobs,lastobs);
1.215 brouard 12911:
1.126 brouard 12912: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12913: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12914: ncodemax[1]=1;
1.145 brouard 12915: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12916: cptcoveff=0;
1.220 brouard 12917: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 12918: 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 12919: }
12920:
12921: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 12922: invalidvarcomb=ivector(0, ncovcombmax);
12923: for(i=0;i<ncovcombmax;i++)
1.227 brouard 12924: invalidvarcomb[i]=0;
12925:
1.211 brouard 12926: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12927: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12928: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12929:
1.200 brouard 12930: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12931: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12932: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12933: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12934: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12935: * (currently 0 or 1) in the data.
12936: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12937: * corresponding modality (h,j).
12938: */
12939:
1.145 brouard 12940: h=0;
12941: /*if (cptcovn > 0) */
1.126 brouard 12942: m=pow(2,cptcoveff);
12943:
1.144 brouard 12944: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12945: * For k=4 covariates, h goes from 1 to m=2**k
12946: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12947: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 12948: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
12949: *______________________________ *______________________
12950: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
12951: * 2 2 1 1 1 * 1 0 0 0 1
12952: * 3 i=2 1 2 1 1 * 2 0 0 1 0
12953: * 4 2 2 1 1 * 3 0 0 1 1
12954: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
12955: * 6 2 1 2 1 * 5 0 1 0 1
12956: * 7 i=4 1 2 2 1 * 6 0 1 1 0
12957: * 8 2 2 2 1 * 7 0 1 1 1
12958: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
12959: * 10 2 1 1 2 * 9 1 0 0 1
12960: * 11 i=6 1 2 1 2 * 10 1 0 1 0
12961: * 12 2 2 1 2 * 11 1 0 1 1
12962: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
12963: * 14 2 1 2 2 * 13 1 1 0 1
12964: * 15 i=8 1 2 2 2 * 14 1 1 1 0
12965: * 16 2 2 2 2 * 15 1 1 1 1
12966: */
1.212 brouard 12967: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12968: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12969: * and the value of each covariate?
12970: * V1=1, V2=1, V3=2, V4=1 ?
12971: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12972: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12973: * In order to get the real value in the data, we use nbcode
12974: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12975: * We are keeping this crazy system in order to be able (in the future?)
12976: * to have more than 2 values (0 or 1) for a covariate.
12977: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12978: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12979: * bbbbbbbb
12980: * 76543210
12981: * h-1 00000101 (6-1=5)
1.219 brouard 12982: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12983: * &
12984: * 1 00000001 (1)
1.219 brouard 12985: * 00000000 = 1 & ((h-1) >> (k-1))
12986: * +1= 00000001 =1
1.211 brouard 12987: *
12988: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12989: * h' 1101 =2^3+2^2+0x2^1+2^0
12990: * >>k' 11
12991: * & 00000001
12992: * = 00000001
12993: * +1 = 00000010=2 = codtabm(14,3)
12994: * Reverse h=6 and m=16?
12995: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12996: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12997: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12998: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12999: * V3=decodtabm(14,3,2**4)=2
13000: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13001: *(h-1) >> (j-1) 0011 =13 >> 2
13002: * &1 000000001
13003: * = 000000001
13004: * +1= 000000010 =2
13005: * 2211
13006: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13007: * V3=2
1.220 brouard 13008: * codtabm and decodtabm are identical
1.211 brouard 13009: */
13010:
1.145 brouard 13011:
13012: free_ivector(Ndum,-1,NCOVMAX);
13013:
13014:
1.126 brouard 13015:
1.186 brouard 13016: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13017: strcpy(optionfilegnuplot,optionfilefiname);
13018: if(mle==-3)
1.201 brouard 13019: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13020: strcat(optionfilegnuplot,".gp");
13021:
13022: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13023: printf("Problem with file %s",optionfilegnuplot);
13024: }
13025: else{
1.204 brouard 13026: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13027: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13028: //fprintf(ficgp,"set missing 'NaNq'\n");
13029: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13030: }
13031: /* fclose(ficgp);*/
1.186 brouard 13032:
13033:
13034: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13035:
13036: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13037: if(mle==-3)
1.201 brouard 13038: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13039: strcat(optionfilehtm,".htm");
13040: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13041: printf("Problem with %s \n",optionfilehtm);
13042: exit(0);
1.126 brouard 13043: }
13044:
13045: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13046: strcat(optionfilehtmcov,"-cov.htm");
13047: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13048: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13049: }
13050: else{
13051: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13052: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13053: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13054: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13055: }
13056:
1.335 brouard 13057: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13058: <title>IMaCh %s</title></head>\n\
13059: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13060: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13061: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13062: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13063: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13064:
13065: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13066: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13067: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13068: 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 13069: \n\
13070: <hr size=\"2\" color=\"#EC5E5E\">\
13071: <ul><li><h4>Parameter files</h4>\n\
13072: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13073: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13074: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13075: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13076: - Date and time at start: %s</ul>\n",\
1.335 brouard 13077: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13078: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13079: fileres,fileres,\
13080: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13081: fflush(fichtm);
13082:
13083: strcpy(pathr,path);
13084: strcat(pathr,optionfilefiname);
1.184 brouard 13085: #ifdef WIN32
13086: _chdir(optionfilefiname); /* Move to directory named optionfile */
13087: #else
1.126 brouard 13088: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 13089: #endif
13090:
1.126 brouard 13091:
1.220 brouard 13092: /* Calculates basic frequencies. Computes observed prevalence at single age
13093: and for any valid combination of covariates
1.126 brouard 13094: and prints on file fileres'p'. */
1.251 brouard 13095: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 13096: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 13097:
13098: fprintf(fichtm,"\n");
1.286 brouard 13099: 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 13100: ftol, stepm);
13101: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
13102: ncurrv=1;
13103: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
13104: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
13105: ncurrv=i;
13106: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13107: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 13108: ncurrv=i;
13109: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13110: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 13111: ncurrv=i;
13112: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
13113: 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", \
13114: nlstate, ndeath, maxwav, mle, weightopt);
13115:
13116: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
13117: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
13118:
13119:
1.317 brouard 13120: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 13121: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
13122: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 13123: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 13124: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 13125: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13126: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13127: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13128: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 13129:
1.126 brouard 13130: /* For Powell, parameters are in a vector p[] starting at p[1]
13131: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
13132: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
13133:
13134: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 13135: /* For mortality only */
1.126 brouard 13136: if (mle==-3){
1.136 brouard 13137: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 13138: for(i=1;i<=NDIM;i++)
13139: for(j=1;j<=NDIM;j++)
13140: ximort[i][j]=0.;
1.186 brouard 13141: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 13142: cens=ivector(firstobs,lastobs);
13143: ageexmed=vector(firstobs,lastobs);
13144: agecens=vector(firstobs,lastobs);
13145: dcwave=ivector(firstobs,lastobs);
1.223 brouard 13146:
1.126 brouard 13147: for (i=1; i<=imx; i++){
13148: dcwave[i]=-1;
13149: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 13150: if (s[m][i]>nlstate) {
13151: dcwave[i]=m;
13152: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
13153: break;
13154: }
1.126 brouard 13155: }
1.226 brouard 13156:
1.126 brouard 13157: for (i=1; i<=imx; i++) {
13158: if (wav[i]>0){
1.226 brouard 13159: ageexmed[i]=agev[mw[1][i]][i];
13160: j=wav[i];
13161: agecens[i]=1.;
13162:
13163: if (ageexmed[i]> 1 && wav[i] > 0){
13164: agecens[i]=agev[mw[j][i]][i];
13165: cens[i]= 1;
13166: }else if (ageexmed[i]< 1)
13167: cens[i]= -1;
13168: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
13169: cens[i]=0 ;
1.126 brouard 13170: }
13171: else cens[i]=-1;
13172: }
13173:
13174: for (i=1;i<=NDIM;i++) {
13175: for (j=1;j<=NDIM;j++)
1.226 brouard 13176: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 13177: }
13178:
1.302 brouard 13179: p[1]=0.0268; p[NDIM]=0.083;
13180: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 13181:
13182:
1.136 brouard 13183: #ifdef GSL
13184: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 13185: #else
1.126 brouard 13186: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 13187: #endif
1.201 brouard 13188: strcpy(filerespow,"POW-MORT_");
13189: strcat(filerespow,fileresu);
1.126 brouard 13190: if((ficrespow=fopen(filerespow,"w"))==NULL) {
13191: printf("Problem with resultfile: %s\n", filerespow);
13192: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
13193: }
1.136 brouard 13194: #ifdef GSL
13195: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 13196: #else
1.126 brouard 13197: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 13198: #endif
1.126 brouard 13199: /* for (i=1;i<=nlstate;i++)
13200: for(j=1;j<=nlstate+ndeath;j++)
13201: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
13202: */
13203: fprintf(ficrespow,"\n");
1.136 brouard 13204: #ifdef GSL
13205: /* gsl starts here */
13206: T = gsl_multimin_fminimizer_nmsimplex;
13207: gsl_multimin_fminimizer *sfm = NULL;
13208: gsl_vector *ss, *x;
13209: gsl_multimin_function minex_func;
13210:
13211: /* Initial vertex size vector */
13212: ss = gsl_vector_alloc (NDIM);
13213:
13214: if (ss == NULL){
13215: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
13216: }
13217: /* Set all step sizes to 1 */
13218: gsl_vector_set_all (ss, 0.001);
13219:
13220: /* Starting point */
1.126 brouard 13221:
1.136 brouard 13222: x = gsl_vector_alloc (NDIM);
13223:
13224: if (x == NULL){
13225: gsl_vector_free(ss);
13226: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
13227: }
13228:
13229: /* Initialize method and iterate */
13230: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 13231: /* gsl_vector_set(x, 0, 0.0268); */
13232: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 13233: gsl_vector_set(x, 0, p[1]);
13234: gsl_vector_set(x, 1, p[2]);
13235:
13236: minex_func.f = &gompertz_f;
13237: minex_func.n = NDIM;
13238: minex_func.params = (void *)&p; /* ??? */
13239:
13240: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
13241: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
13242:
13243: printf("Iterations beginning .....\n\n");
13244: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
13245:
13246: iteri=0;
13247: while (rval == GSL_CONTINUE){
13248: iteri++;
13249: status = gsl_multimin_fminimizer_iterate(sfm);
13250:
13251: if (status) printf("error: %s\n", gsl_strerror (status));
13252: fflush(0);
13253:
13254: if (status)
13255: break;
13256:
13257: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
13258: ssval = gsl_multimin_fminimizer_size (sfm);
13259:
13260: if (rval == GSL_SUCCESS)
13261: printf ("converged to a local maximum at\n");
13262:
13263: printf("%5d ", iteri);
13264: for (it = 0; it < NDIM; it++){
13265: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
13266: }
13267: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
13268: }
13269:
13270: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
13271:
13272: gsl_vector_free(x); /* initial values */
13273: gsl_vector_free(ss); /* inital step size */
13274: for (it=0; it<NDIM; it++){
13275: p[it+1]=gsl_vector_get(sfm->x,it);
13276: fprintf(ficrespow," %.12lf", p[it]);
13277: }
13278: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
13279: #endif
13280: #ifdef POWELL
13281: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
13282: #endif
1.126 brouard 13283: fclose(ficrespow);
13284:
1.203 brouard 13285: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 13286:
13287: for(i=1; i <=NDIM; i++)
13288: for(j=i+1;j<=NDIM;j++)
1.220 brouard 13289: matcov[i][j]=matcov[j][i];
1.126 brouard 13290:
13291: printf("\nCovariance matrix\n ");
1.203 brouard 13292: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 13293: for(i=1; i <=NDIM; i++) {
13294: for(j=1;j<=NDIM;j++){
1.220 brouard 13295: printf("%f ",matcov[i][j]);
13296: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 13297: }
1.203 brouard 13298: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 13299: }
13300:
13301: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 13302: for (i=1;i<=NDIM;i++) {
1.126 brouard 13303: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 13304: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
13305: }
1.302 brouard 13306: lsurv=vector(agegomp,AGESUP);
13307: lpop=vector(agegomp,AGESUP);
13308: tpop=vector(agegomp,AGESUP);
1.126 brouard 13309: lsurv[agegomp]=100000;
13310:
13311: for (k=agegomp;k<=AGESUP;k++) {
13312: agemortsup=k;
13313: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
13314: }
13315:
13316: for (k=agegomp;k<agemortsup;k++)
13317: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
13318:
13319: for (k=agegomp;k<agemortsup;k++){
13320: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
13321: sumlpop=sumlpop+lpop[k];
13322: }
13323:
13324: tpop[agegomp]=sumlpop;
13325: for (k=agegomp;k<(agemortsup-3);k++){
13326: /* tpop[k+1]=2;*/
13327: tpop[k+1]=tpop[k]-lpop[k];
13328: }
13329:
13330:
13331: printf("\nAge lx qx dx Lx Tx e(x)\n");
13332: for (k=agegomp;k<(agemortsup-2);k++)
13333: 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]);
13334:
13335:
13336: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 13337: ageminpar=50;
13338: agemaxpar=100;
1.194 brouard 13339: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
13340: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13341: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13342: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
13343: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13344: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13345: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13346: }else{
13347: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
13348: 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 13349: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 13350: }
1.201 brouard 13351: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 13352: stepm, weightopt,\
13353: model,imx,p,matcov,agemortsup);
13354:
1.302 brouard 13355: free_vector(lsurv,agegomp,AGESUP);
13356: free_vector(lpop,agegomp,AGESUP);
13357: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 13358: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 13359: free_ivector(dcwave,firstobs,lastobs);
13360: free_vector(agecens,firstobs,lastobs);
13361: free_vector(ageexmed,firstobs,lastobs);
13362: free_ivector(cens,firstobs,lastobs);
1.220 brouard 13363: #ifdef GSL
1.136 brouard 13364: #endif
1.186 brouard 13365: } /* Endof if mle==-3 mortality only */
1.205 brouard 13366: /* Standard */
13367: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
13368: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13369: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 13370: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 13371: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
13372: for (k=1; k<=npar;k++)
13373: printf(" %d %8.5f",k,p[k]);
13374: printf("\n");
1.205 brouard 13375: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
13376: /* mlikeli uses func not funcone */
1.247 brouard 13377: /* for(i=1;i<nlstate;i++){ */
13378: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13379: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13380: /* } */
1.205 brouard 13381: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
13382: }
13383: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
13384: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13385: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
13386: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13387: }
13388: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 13389: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13390: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 13391: /* exit(0); */
1.126 brouard 13392: for (k=1; k<=npar;k++)
13393: printf(" %d %8.5f",k,p[k]);
13394: printf("\n");
13395:
13396: /*--------- results files --------------*/
1.283 brouard 13397: /* 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 13398:
13399:
13400: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13401: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 13402: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13403:
13404: printf("#model= 1 + age ");
13405: fprintf(ficres,"#model= 1 + age ");
13406: fprintf(ficlog,"#model= 1 + age ");
13407: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
13408: </ul>", model);
13409:
13410: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
13411: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
13412: if(nagesqr==1){
13413: printf(" + age*age ");
13414: fprintf(ficres," + age*age ");
13415: fprintf(ficlog," + age*age ");
13416: fprintf(fichtm, "<th>+ age*age</th>");
13417: }
13418: for(j=1;j <=ncovmodel-2;j++){
13419: if(Typevar[j]==0) {
13420: printf(" + V%d ",Tvar[j]);
13421: fprintf(ficres," + V%d ",Tvar[j]);
13422: fprintf(ficlog," + V%d ",Tvar[j]);
13423: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13424: }else if(Typevar[j]==1) {
13425: printf(" + V%d*age ",Tvar[j]);
13426: fprintf(ficres," + V%d*age ",Tvar[j]);
13427: fprintf(ficlog," + V%d*age ",Tvar[j]);
13428: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13429: }else if(Typevar[j]==2) {
13430: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13431: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13432: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13433: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13434: }
13435: }
13436: printf("\n");
13437: fprintf(ficres,"\n");
13438: fprintf(ficlog,"\n");
13439: fprintf(fichtm, "</tr>");
13440: fprintf(fichtm, "\n");
13441:
13442:
1.126 brouard 13443: for(i=1,jk=1; i <=nlstate; i++){
13444: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 13445: if (k != i) {
1.319 brouard 13446: fprintf(fichtm, "<tr>");
1.225 brouard 13447: printf("%d%d ",i,k);
13448: fprintf(ficlog,"%d%d ",i,k);
13449: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 13450: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13451: for(j=1; j <=ncovmodel; j++){
13452: printf("%12.7f ",p[jk]);
13453: fprintf(ficlog,"%12.7f ",p[jk]);
13454: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 13455: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 13456: jk++;
13457: }
13458: printf("\n");
13459: fprintf(ficlog,"\n");
13460: fprintf(ficres,"\n");
1.319 brouard 13461: fprintf(fichtm, "</tr>\n");
1.225 brouard 13462: }
1.126 brouard 13463: }
13464: }
1.319 brouard 13465: /* fprintf(fichtm,"</tr>\n"); */
13466: fprintf(fichtm,"</table>\n");
13467: fprintf(fichtm, "\n");
13468:
1.203 brouard 13469: if(mle != 0){
13470: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 13471: ftolhess=ftol; /* Usually correct */
1.203 brouard 13472: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
13473: 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");
13474: 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 13475: 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 13476: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
13477: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
13478: if(nagesqr==1){
13479: printf(" + age*age ");
13480: fprintf(ficres," + age*age ");
13481: fprintf(ficlog," + age*age ");
13482: fprintf(fichtm, "<th>+ age*age</th>");
13483: }
13484: for(j=1;j <=ncovmodel-2;j++){
13485: if(Typevar[j]==0) {
13486: printf(" + V%d ",Tvar[j]);
13487: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13488: }else if(Typevar[j]==1) {
13489: printf(" + V%d*age ",Tvar[j]);
13490: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13491: }else if(Typevar[j]==2) {
13492: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13493: }
13494: }
13495: fprintf(fichtm, "</tr>\n");
13496:
1.203 brouard 13497: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 13498: for(k=1; k <=(nlstate+ndeath); k++){
13499: if (k != i) {
1.319 brouard 13500: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 13501: printf("%d%d ",i,k);
13502: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 13503: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13504: for(j=1; j <=ncovmodel; j++){
1.319 brouard 13505: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 13506: 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]));
13507: 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 13508: if(fabs(wald) > 1.96){
1.321 brouard 13509: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 13510: }else{
13511: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
13512: }
1.324 brouard 13513: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 13514: 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 13515: jk++;
13516: }
13517: printf("\n");
13518: fprintf(ficlog,"\n");
1.319 brouard 13519: fprintf(fichtm, "</tr>\n");
1.225 brouard 13520: }
13521: }
1.193 brouard 13522: }
1.203 brouard 13523: } /* end of hesscov and Wald tests */
1.319 brouard 13524: fprintf(fichtm,"</table>\n");
1.225 brouard 13525:
1.203 brouard 13526: /* */
1.126 brouard 13527: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
13528: printf("# Scales (for hessian or gradient estimation)\n");
13529: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
13530: for(i=1,jk=1; i <=nlstate; i++){
13531: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 13532: if (j!=i) {
13533: fprintf(ficres,"%1d%1d",i,j);
13534: printf("%1d%1d",i,j);
13535: fprintf(ficlog,"%1d%1d",i,j);
13536: for(k=1; k<=ncovmodel;k++){
13537: printf(" %.5e",delti[jk]);
13538: fprintf(ficlog," %.5e",delti[jk]);
13539: fprintf(ficres," %.5e",delti[jk]);
13540: jk++;
13541: }
13542: printf("\n");
13543: fprintf(ficlog,"\n");
13544: fprintf(ficres,"\n");
13545: }
1.126 brouard 13546: }
13547: }
13548:
13549: 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");
1.203 brouard 13550: if(mle >= 1) /* To big for the screen */
1.126 brouard 13551: 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");
13552: 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");
13553: /* # 121 Var(a12)\n\ */
13554: /* # 122 Cov(b12,a12) Var(b12)\n\ */
13555: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
13556: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
13557: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
13558: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
13559: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
13560: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
13561:
13562:
13563: /* Just to have a covariance matrix which will be more understandable
13564: even is we still don't want to manage dictionary of variables
13565: */
13566: for(itimes=1;itimes<=2;itimes++){
13567: jj=0;
13568: for(i=1; i <=nlstate; i++){
1.225 brouard 13569: for(j=1; j <=nlstate+ndeath; j++){
13570: if(j==i) continue;
13571: for(k=1; k<=ncovmodel;k++){
13572: jj++;
13573: ca[0]= k+'a'-1;ca[1]='\0';
13574: if(itimes==1){
13575: if(mle>=1)
13576: printf("#%1d%1d%d",i,j,k);
13577: fprintf(ficlog,"#%1d%1d%d",i,j,k);
13578: fprintf(ficres,"#%1d%1d%d",i,j,k);
13579: }else{
13580: if(mle>=1)
13581: printf("%1d%1d%d",i,j,k);
13582: fprintf(ficlog,"%1d%1d%d",i,j,k);
13583: fprintf(ficres,"%1d%1d%d",i,j,k);
13584: }
13585: ll=0;
13586: for(li=1;li <=nlstate; li++){
13587: for(lj=1;lj <=nlstate+ndeath; lj++){
13588: if(lj==li) continue;
13589: for(lk=1;lk<=ncovmodel;lk++){
13590: ll++;
13591: if(ll<=jj){
13592: cb[0]= lk +'a'-1;cb[1]='\0';
13593: if(ll<jj){
13594: if(itimes==1){
13595: if(mle>=1)
13596: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13597: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13598: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13599: }else{
13600: if(mle>=1)
13601: printf(" %.5e",matcov[jj][ll]);
13602: fprintf(ficlog," %.5e",matcov[jj][ll]);
13603: fprintf(ficres," %.5e",matcov[jj][ll]);
13604: }
13605: }else{
13606: if(itimes==1){
13607: if(mle>=1)
13608: printf(" Var(%s%1d%1d)",ca,i,j);
13609: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
13610: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
13611: }else{
13612: if(mle>=1)
13613: printf(" %.7e",matcov[jj][ll]);
13614: fprintf(ficlog," %.7e",matcov[jj][ll]);
13615: fprintf(ficres," %.7e",matcov[jj][ll]);
13616: }
13617: }
13618: }
13619: } /* end lk */
13620: } /* end lj */
13621: } /* end li */
13622: if(mle>=1)
13623: printf("\n");
13624: fprintf(ficlog,"\n");
13625: fprintf(ficres,"\n");
13626: numlinepar++;
13627: } /* end k*/
13628: } /*end j */
1.126 brouard 13629: } /* end i */
13630: } /* end itimes */
13631:
13632: fflush(ficlog);
13633: fflush(ficres);
1.225 brouard 13634: while(fgets(line, MAXLINE, ficpar)) {
13635: /* If line starts with a # it is a comment */
13636: if (line[0] == '#') {
13637: numlinepar++;
13638: fputs(line,stdout);
13639: fputs(line,ficparo);
13640: fputs(line,ficlog);
1.299 brouard 13641: fputs(line,ficres);
1.225 brouard 13642: continue;
13643: }else
13644: break;
13645: }
13646:
1.209 brouard 13647: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
13648: /* ungetc(c,ficpar); */
13649: /* fgets(line, MAXLINE, ficpar); */
13650: /* fputs(line,stdout); */
13651: /* fputs(line,ficparo); */
13652: /* } */
13653: /* ungetc(c,ficpar); */
1.126 brouard 13654:
13655: estepm=0;
1.209 brouard 13656: 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 13657:
13658: if (num_filled != 6) {
13659: 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);
13660: 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);
13661: goto end;
13662: }
13663: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
13664: }
13665: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
13666: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
13667:
1.209 brouard 13668: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 13669: if (estepm==0 || estepm < stepm) estepm=stepm;
13670: if (fage <= 2) {
13671: bage = ageminpar;
13672: fage = agemaxpar;
13673: }
13674:
13675: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 13676: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
13677: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 13678:
1.186 brouard 13679: /* Other stuffs, more or less useful */
1.254 brouard 13680: while(fgets(line, MAXLINE, ficpar)) {
13681: /* If line starts with a # it is a comment */
13682: if (line[0] == '#') {
13683: numlinepar++;
13684: fputs(line,stdout);
13685: fputs(line,ficparo);
13686: fputs(line,ficlog);
1.299 brouard 13687: fputs(line,ficres);
1.254 brouard 13688: continue;
13689: }else
13690: break;
13691: }
13692:
13693: 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){
13694:
13695: if (num_filled != 7) {
13696: 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);
13697: 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);
13698: goto end;
13699: }
13700: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
13701: 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);
13702: 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);
13703: 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 13704: }
1.254 brouard 13705:
13706: while(fgets(line, MAXLINE, ficpar)) {
13707: /* If line starts with a # it is a comment */
13708: if (line[0] == '#') {
13709: numlinepar++;
13710: fputs(line,stdout);
13711: fputs(line,ficparo);
13712: fputs(line,ficlog);
1.299 brouard 13713: fputs(line,ficres);
1.254 brouard 13714: continue;
13715: }else
13716: break;
1.126 brouard 13717: }
13718:
13719:
13720: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
13721: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
13722:
1.254 brouard 13723: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
13724: if (num_filled != 1) {
13725: 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);
13726: 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);
13727: goto end;
13728: }
13729: printf("pop_based=%d\n",popbased);
13730: fprintf(ficlog,"pop_based=%d\n",popbased);
13731: fprintf(ficparo,"pop_based=%d\n",popbased);
13732: fprintf(ficres,"pop_based=%d\n",popbased);
13733: }
13734:
1.258 brouard 13735: /* Results */
1.332 brouard 13736: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
13737: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
13738: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 13739: endishere=0;
1.258 brouard 13740: nresult=0;
1.308 brouard 13741: parameterline=0;
1.258 brouard 13742: do{
13743: if(!fgets(line, MAXLINE, ficpar)){
13744: endishere=1;
1.308 brouard 13745: parameterline=15;
1.258 brouard 13746: }else if (line[0] == '#') {
13747: /* If line starts with a # it is a comment */
1.254 brouard 13748: numlinepar++;
13749: fputs(line,stdout);
13750: fputs(line,ficparo);
13751: fputs(line,ficlog);
1.299 brouard 13752: fputs(line,ficres);
1.254 brouard 13753: continue;
1.258 brouard 13754: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
13755: parameterline=11;
1.296 brouard 13756: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 13757: parameterline=12;
1.307 brouard 13758: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 13759: parameterline=13;
1.307 brouard 13760: }
1.258 brouard 13761: else{
13762: parameterline=14;
1.254 brouard 13763: }
1.308 brouard 13764: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13765: case 11:
1.296 brouard 13766: 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)){
13767: 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 13768: 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);
13769: 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);
13770: 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);
13771: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 13772: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
13773: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 13774: prvforecast = 1;
13775: }
13776: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 13777: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13778: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13779: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 13780: prvforecast = 2;
13781: }
13782: else {
13783: 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);
13784: 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);
13785: goto end;
1.258 brouard 13786: }
1.254 brouard 13787: break;
1.258 brouard 13788: case 12:
1.296 brouard 13789: 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)){
13790: 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);
13791: 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);
13792: 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);
13793: 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);
13794: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 13795: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
13796: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 13797: prvbackcast = 1;
13798: }
13799: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 13800: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13801: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13802: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 13803: prvbackcast = 2;
13804: }
13805: else {
13806: 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);
13807: 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);
13808: goto end;
1.258 brouard 13809: }
1.230 brouard 13810: break;
1.258 brouard 13811: case 13:
1.332 brouard 13812: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 13813: nresult++; /* Sum of resultlines */
1.332 brouard 13814: printf("Result %d: result:%s\n",nresult, resultlineori);
13815: /* removefirstspace(&resultlineori); */
13816:
13817: if(strstr(resultlineori,"v") !=0){
13818: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
13819: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
13820: return 1;
13821: }
13822: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
13823: printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori);
1.318 brouard 13824: if(nresult > MAXRESULTLINESPONE-1){
13825: 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);
13826: 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 13827: goto end;
13828: }
1.332 brouard 13829:
1.310 brouard 13830: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 13831: fprintf(ficparo,"result: %s\n",resultline);
13832: fprintf(ficres,"result: %s\n",resultline);
13833: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 13834: } else
13835: goto end;
1.307 brouard 13836: break;
13837: case 14:
13838: printf("Error: Unknown command '%s'\n",line);
13839: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 13840: if(line[0] == ' ' || line[0] == '\n'){
13841: printf("It should not be an empty line '%s'\n",line);
13842: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
13843: }
1.307 brouard 13844: if(ncovmodel >=2 && nresult==0 ){
13845: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
13846: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 13847: }
1.307 brouard 13848: /* goto end; */
13849: break;
1.308 brouard 13850: case 15:
13851: printf("End of resultlines.\n");
13852: fprintf(ficlog,"End of resultlines.\n");
13853: break;
13854: default: /* parameterline =0 */
1.307 brouard 13855: nresult=1;
13856: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 13857: } /* End switch parameterline */
13858: }while(endishere==0); /* End do */
1.126 brouard 13859:
1.230 brouard 13860: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 13861: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 13862:
13863: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 13864: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 13865: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13866: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13867: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 13868: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13869: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13870: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13871: }else{
1.270 brouard 13872: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 13873: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
13874: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
13875: if(prvforecast==1){
13876: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
13877: jprojd=jproj1;
13878: mprojd=mproj1;
13879: anprojd=anproj1;
13880: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
13881: jprojf=jproj2;
13882: mprojf=mproj2;
13883: anprojf=anproj2;
13884: } else if(prvforecast == 2){
13885: dateprojd=dateintmean;
13886: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
13887: dateprojf=dateintmean+yrfproj;
13888: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
13889: }
13890: if(prvbackcast==1){
13891: datebackd=(jback1+12*mback1+365*anback1)/365;
13892: jbackd=jback1;
13893: mbackd=mback1;
13894: anbackd=anback1;
13895: datebackf=(jback2+12*mback2+365*anback2)/365;
13896: jbackf=jback2;
13897: mbackf=mback2;
13898: anbackf=anback2;
13899: } else if(prvbackcast == 2){
13900: datebackd=dateintmean;
13901: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
13902: datebackf=dateintmean-yrbproj;
13903: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
13904: }
13905:
13906: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 13907: }
13908: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 13909: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
13910: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 13911:
1.225 brouard 13912: /*------------ free_vector -------------*/
13913: /* chdir(path); */
1.220 brouard 13914:
1.215 brouard 13915: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
13916: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
13917: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
13918: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 13919: free_lvector(num,firstobs,lastobs);
13920: free_vector(agedc,firstobs,lastobs);
1.126 brouard 13921: /*free_matrix(covar,0,NCOVMAX,1,n);*/
13922: /*free_matrix(covar,1,NCOVMAX,1,n);*/
13923: fclose(ficparo);
13924: fclose(ficres);
1.220 brouard 13925:
13926:
1.186 brouard 13927: /* Other results (useful)*/
1.220 brouard 13928:
13929:
1.126 brouard 13930: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13931: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13932: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 13933: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 13934: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13935: fclose(ficrespl);
13936:
13937: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13938: /*#include "hpijx.h"*/
1.332 brouard 13939: /** 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?*/
13940: /* calls hpxij with combination k */
1.180 brouard 13941: hPijx(p, bage, fage);
1.145 brouard 13942: fclose(ficrespij);
1.227 brouard 13943:
1.220 brouard 13944: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 13945: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 13946: k=1;
1.126 brouard 13947: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13948:
1.269 brouard 13949: /* Prevalence for each covariate combination in probs[age][status][cov] */
13950: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13951: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13952: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13953: for(k=1;k<=ncovcombmax;k++)
13954: probs[i][j][k]=0.;
1.269 brouard 13955: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13956: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13957: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13958: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13959: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13960: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13961: for(k=1;k<=ncovcombmax;k++)
13962: mobaverages[i][j][k]=0.;
1.219 brouard 13963: mobaverage=mobaverages;
13964: if (mobilav!=0) {
1.235 brouard 13965: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13966: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13967: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13968: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13969: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13970: }
1.269 brouard 13971: } else if (mobilavproj !=0) {
1.235 brouard 13972: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13973: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13974: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13975: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13976: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13977: }
1.269 brouard 13978: }else{
13979: printf("Internal error moving average\n");
13980: fflush(stdout);
13981: exit(1);
1.219 brouard 13982: }
13983: }/* end if moving average */
1.227 brouard 13984:
1.126 brouard 13985: /*---------- Forecasting ------------------*/
1.296 brouard 13986: if(prevfcast==1){
13987: /* /\* if(stepm ==1){*\/ */
13988: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13989: /*This done previously after freqsummary.*/
13990: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13991: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13992:
13993: /* } else if (prvforecast==2){ */
13994: /* /\* if(stepm ==1){*\/ */
13995: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13996: /* } */
13997: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13998: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13999: }
1.269 brouard 14000:
1.296 brouard 14001: /* Prevbcasting */
14002: if(prevbcast==1){
1.219 brouard 14003: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14004: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14005: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14006:
14007: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14008:
14009: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14010:
1.219 brouard 14011: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14012: fclose(ficresplb);
14013:
1.222 brouard 14014: hBijx(p, bage, fage, mobaverage);
14015: fclose(ficrespijb);
1.219 brouard 14016:
1.296 brouard 14017: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14018: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14019: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14020: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14021: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14022: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14023:
14024:
1.269 brouard 14025: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14026:
14027:
1.269 brouard 14028: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14029: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14030: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14031: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14032: } /* end Prevbcasting */
1.268 brouard 14033:
1.186 brouard 14034:
14035: /* ------ Other prevalence ratios------------ */
1.126 brouard 14036:
1.215 brouard 14037: free_ivector(wav,1,imx);
14038: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14039: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14040: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14041:
14042:
1.127 brouard 14043: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14044:
1.201 brouard 14045: strcpy(filerese,"E_");
14046: strcat(filerese,fileresu);
1.126 brouard 14047: if((ficreseij=fopen(filerese,"w"))==NULL) {
14048: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14049: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14050: }
1.208 brouard 14051: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14052: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14053:
14054: pstamp(ficreseij);
1.219 brouard 14055:
1.235 brouard 14056: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14057: if (cptcovn < 1){i1=1;}
14058:
14059: for(nres=1; nres <= nresult; nres++) /* For each resultline */
14060: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 14061: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 14062: continue;
1.219 brouard 14063: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14064: printf("\n#****** ");
1.225 brouard 14065: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 14066: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
14067: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 14068: }
14069: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14070: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14071: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 14072: }
14073: fprintf(ficreseij,"******\n");
1.235 brouard 14074: printf("******\n");
1.219 brouard 14075:
14076: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14077: oldm=oldms;savm=savms;
1.330 brouard 14078: /* 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 14079: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 14080:
1.219 brouard 14081: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 14082: }
14083: fclose(ficreseij);
1.208 brouard 14084: printf("done evsij\n");fflush(stdout);
14085: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 14086:
1.218 brouard 14087:
1.227 brouard 14088: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 14089: /* Should be moved in a function */
1.201 brouard 14090: strcpy(filerest,"T_");
14091: strcat(filerest,fileresu);
1.127 brouard 14092: if((ficrest=fopen(filerest,"w"))==NULL) {
14093: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
14094: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
14095: }
1.208 brouard 14096: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
14097: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 14098: strcpy(fileresstde,"STDE_");
14099: strcat(fileresstde,fileresu);
1.126 brouard 14100: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 14101: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
14102: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 14103: }
1.227 brouard 14104: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
14105: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 14106:
1.201 brouard 14107: strcpy(filerescve,"CVE_");
14108: strcat(filerescve,fileresu);
1.126 brouard 14109: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 14110: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
14111: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 14112: }
1.227 brouard 14113: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
14114: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 14115:
1.201 brouard 14116: strcpy(fileresv,"V_");
14117: strcat(fileresv,fileresu);
1.126 brouard 14118: if((ficresvij=fopen(fileresv,"w"))==NULL) {
14119: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
14120: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
14121: }
1.227 brouard 14122: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
14123: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 14124:
1.235 brouard 14125: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14126: if (cptcovn < 1){i1=1;}
14127:
1.334 brouard 14128: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
14129: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
14130: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
14131: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
14132: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
14133: /* */
14134: 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 14135: continue;
1.321 brouard 14136: printf("\n# model %s \n#****** Result for:", model);
14137: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
14138: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 14139: /* It might not be a good idea to mix dummies and quantitative */
14140: /* 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 *\/ */
14141: 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 */
14142: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
14143: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
14144: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
14145: * (V5 is quanti) V4 and V3 are dummies
14146: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
14147: * l=1 l=2
14148: * k=1 1 1 0 0
14149: * k=2 2 1 1 0
14150: * k=3 [1] [2] 0 1
14151: * k=4 2 2 1 1
14152: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
14153: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
14154: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
14155: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
14156: */
14157: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
14158: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
14159: /* We give up with the combinations!! */
14160: 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 */
14161:
14162: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
1.337 brouard 14163: 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 */
14164: fprintf(ficlog,"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 */
14165: fprintf(ficrest,"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 */
1.334 brouard 14166: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14167: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14168: }else{
14169: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14170: }
14171: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14172: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14173: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
14174: /* For each selected (single) quantitative value */
1.337 brouard 14175: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14176: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14177: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 14178: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14179: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14180: }else{
14181: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14182: }
14183: }else{
14184: 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 */
14185: 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 */
14186: exit(1);
14187: }
1.335 brouard 14188: } /* End loop for each variable in the resultline */
1.334 brouard 14189: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14190: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
14191: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14192: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14193: /* } */
1.208 brouard 14194: fprintf(ficrest,"******\n");
1.227 brouard 14195: fprintf(ficlog,"******\n");
14196: printf("******\n");
1.208 brouard 14197:
14198: fprintf(ficresstdeij,"\n#****** ");
14199: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 14200: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
14201: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 14202: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 14203: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14204: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14205: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14206: }
14207: 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 14208: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
14209: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 14210: }
1.208 brouard 14211: fprintf(ficresstdeij,"******\n");
14212: fprintf(ficrescveij,"******\n");
14213:
14214: fprintf(ficresvij,"\n#****** ");
1.238 brouard 14215: /* pstamp(ficresvij); */
1.225 brouard 14216: for(j=1;j<=cptcoveff;j++)
1.335 brouard 14217: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14218: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 14219: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 14220: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 14221: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 14222: }
1.208 brouard 14223: fprintf(ficresvij,"******\n");
14224:
14225: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14226: oldm=oldms;savm=savms;
1.235 brouard 14227: printf(" cvevsij ");
14228: fprintf(ficlog, " cvevsij ");
14229: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 14230: printf(" end cvevsij \n ");
14231: fprintf(ficlog, " end cvevsij \n ");
14232:
14233: /*
14234: */
14235: /* goto endfree; */
14236:
14237: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14238: pstamp(ficrest);
14239:
1.269 brouard 14240: epj=vector(1,nlstate+1);
1.208 brouard 14241: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 14242: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
14243: cptcod= 0; /* To be deleted */
14244: printf("varevsij vpopbased=%d \n",vpopbased);
14245: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 14246: 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 14247: 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 ");
14248: if(vpopbased==1)
14249: 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);
14250: else
1.288 brouard 14251: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 14252: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 14253: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
14254: fprintf(ficrest,"\n");
14255: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 14256: printf("Computing age specific forward period (stable) prevalences in each health state \n");
14257: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 14258: for(age=bage; age <=fage ;age++){
1.235 brouard 14259: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 14260: if (vpopbased==1) {
14261: if(mobilav ==0){
14262: for(i=1; i<=nlstate;i++)
14263: prlim[i][i]=probs[(int)age][i][k];
14264: }else{ /* mobilav */
14265: for(i=1; i<=nlstate;i++)
14266: prlim[i][i]=mobaverage[(int)age][i][k];
14267: }
14268: }
1.219 brouard 14269:
1.227 brouard 14270: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
14271: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
14272: /* printf(" age %4.0f ",age); */
14273: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
14274: for(i=1, epj[j]=0.;i <=nlstate;i++) {
14275: epj[j] += prlim[i][i]*eij[i][j][(int)age];
14276: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
14277: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
14278: }
14279: epj[nlstate+1] +=epj[j];
14280: }
14281: /* printf(" age %4.0f \n",age); */
1.219 brouard 14282:
1.227 brouard 14283: for(i=1, vepp=0.;i <=nlstate;i++)
14284: for(j=1;j <=nlstate;j++)
14285: vepp += vareij[i][j][(int)age];
14286: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
14287: for(j=1;j <=nlstate;j++){
14288: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
14289: }
14290: fprintf(ficrest,"\n");
14291: }
1.208 brouard 14292: } /* End vpopbased */
1.269 brouard 14293: free_vector(epj,1,nlstate+1);
1.208 brouard 14294: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
14295: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 14296: printf("done selection\n");fflush(stdout);
14297: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 14298:
1.335 brouard 14299: } /* End k selection or end covariate selection for nres */
1.227 brouard 14300:
14301: printf("done State-specific expectancies\n");fflush(stdout);
14302: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
14303:
1.335 brouard 14304: /* variance-covariance of forward period prevalence */
1.269 brouard 14305: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14306:
1.227 brouard 14307:
1.290 brouard 14308: free_vector(weight,firstobs,lastobs);
1.330 brouard 14309: free_imatrix(Tvardk,1,NCOVMAX,1,2);
1.227 brouard 14310: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 14311: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
14312: free_matrix(anint,1,maxwav,firstobs,lastobs);
14313: free_matrix(mint,1,maxwav,firstobs,lastobs);
14314: free_ivector(cod,firstobs,lastobs);
1.227 brouard 14315: free_ivector(tab,1,NCOVMAX);
14316: fclose(ficresstdeij);
14317: fclose(ficrescveij);
14318: fclose(ficresvij);
14319: fclose(ficrest);
14320: fclose(ficpar);
14321:
14322:
1.126 brouard 14323: /*---------- End : free ----------------*/
1.219 brouard 14324: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 14325: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
14326: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 14327: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
14328: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 14329: } /* mle==-3 arrives here for freeing */
1.227 brouard 14330: /* endfree:*/
14331: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
14332: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
14333: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 ! brouard 14334: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
! 14335: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 14336: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
14337: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
14338: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 14339: free_matrix(matcov,1,npar,1,npar);
14340: free_matrix(hess,1,npar,1,npar);
14341: /*free_vector(delti,1,npar);*/
14342: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14343: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 14344: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 14345: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14346:
14347: free_ivector(ncodemax,1,NCOVMAX);
14348: free_ivector(ncodemaxwundef,1,NCOVMAX);
14349: free_ivector(Dummy,-1,NCOVMAX);
14350: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 14351: free_ivector(DummyV,1,NCOVMAX);
14352: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 14353: free_ivector(Typevar,-1,NCOVMAX);
14354: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 14355: free_ivector(TvarsQ,1,NCOVMAX);
14356: free_ivector(TvarsQind,1,NCOVMAX);
14357: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 14358: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 14359: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 14360: free_ivector(TvarFD,1,NCOVMAX);
14361: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 14362: free_ivector(TvarF,1,NCOVMAX);
14363: free_ivector(TvarFind,1,NCOVMAX);
14364: free_ivector(TvarV,1,NCOVMAX);
14365: free_ivector(TvarVind,1,NCOVMAX);
14366: free_ivector(TvarA,1,NCOVMAX);
14367: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 14368: free_ivector(TvarFQ,1,NCOVMAX);
14369: free_ivector(TvarFQind,1,NCOVMAX);
14370: free_ivector(TvarVD,1,NCOVMAX);
14371: free_ivector(TvarVDind,1,NCOVMAX);
14372: free_ivector(TvarVQ,1,NCOVMAX);
14373: free_ivector(TvarVQind,1,NCOVMAX);
1.339 brouard 14374: free_ivector(TvarVV,1,NCOVMAX);
14375: free_ivector(TvarVVind,1,NCOVMAX);
14376:
1.230 brouard 14377: free_ivector(Tvarsel,1,NCOVMAX);
14378: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 14379: free_ivector(Tposprod,1,NCOVMAX);
14380: free_ivector(Tprod,1,NCOVMAX);
14381: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 14382: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 14383: free_ivector(Tage,1,NCOVMAX);
14384: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 14385: free_ivector(TmodelInvind,1,NCOVMAX);
14386: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 14387:
14388: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
14389:
1.227 brouard 14390: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
14391: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 14392: fflush(fichtm);
14393: fflush(ficgp);
14394:
1.227 brouard 14395:
1.126 brouard 14396: if((nberr >0) || (nbwarn>0)){
1.216 brouard 14397: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
14398: 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 14399: }else{
14400: printf("End of Imach\n");
14401: fprintf(ficlog,"End of Imach\n");
14402: }
14403: printf("See log file on %s\n",filelog);
14404: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 14405: /*(void) gettimeofday(&end_time,&tzp);*/
14406: rend_time = time(NULL);
14407: end_time = *localtime(&rend_time);
14408: /* tml = *localtime(&end_time.tm_sec); */
14409: strcpy(strtend,asctime(&end_time));
1.126 brouard 14410: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
14411: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 14412: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 14413:
1.157 brouard 14414: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
14415: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
14416: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 14417: /* printf("Total time was %d uSec.\n", total_usecs);*/
14418: /* if(fileappend(fichtm,optionfilehtm)){ */
14419: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14420: fclose(fichtm);
14421: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14422: fclose(fichtmcov);
14423: fclose(ficgp);
14424: fclose(ficlog);
14425: /*------ End -----------*/
1.227 brouard 14426:
1.281 brouard 14427:
14428: /* Executes gnuplot */
1.227 brouard 14429:
14430: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 14431: #ifdef WIN32
1.227 brouard 14432: if (_chdir(pathcd) != 0)
14433: printf("Can't move to directory %s!\n",path);
14434: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 14435: #else
1.227 brouard 14436: if(chdir(pathcd) != 0)
14437: printf("Can't move to directory %s!\n", path);
14438: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 14439: #endif
1.126 brouard 14440: printf("Current directory %s!\n",pathcd);
14441: /*strcat(plotcmd,CHARSEPARATOR);*/
14442: sprintf(plotcmd,"gnuplot");
1.157 brouard 14443: #ifdef _WIN32
1.126 brouard 14444: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
14445: #endif
14446: if(!stat(plotcmd,&info)){
1.158 brouard 14447: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14448: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 14449: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 14450: }else
14451: strcpy(pplotcmd,plotcmd);
1.157 brouard 14452: #ifdef __unix
1.126 brouard 14453: strcpy(plotcmd,GNUPLOTPROGRAM);
14454: if(!stat(plotcmd,&info)){
1.158 brouard 14455: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14456: }else
14457: strcpy(pplotcmd,plotcmd);
14458: #endif
14459: }else
14460: strcpy(pplotcmd,plotcmd);
14461:
14462: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 14463: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 14464: strcpy(pplotcmd,plotcmd);
1.227 brouard 14465:
1.126 brouard 14466: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 14467: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 14468: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 14469: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 14470: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 14471: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 14472: strcpy(plotcmd,pplotcmd);
14473: }
1.126 brouard 14474: }
1.158 brouard 14475: printf(" Successful, please wait...");
1.126 brouard 14476: while (z[0] != 'q') {
14477: /* chdir(path); */
1.154 brouard 14478: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 14479: scanf("%s",z);
14480: /* if (z[0] == 'c') system("./imach"); */
14481: if (z[0] == 'e') {
1.158 brouard 14482: #ifdef __APPLE__
1.152 brouard 14483: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 14484: #elif __linux
14485: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 14486: #else
1.152 brouard 14487: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 14488: #endif
14489: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
14490: system(pplotcmd);
1.126 brouard 14491: }
14492: else if (z[0] == 'g') system(plotcmd);
14493: else if (z[0] == 'q') exit(0);
14494: }
1.227 brouard 14495: end:
1.126 brouard 14496: while (z[0] != 'q') {
1.195 brouard 14497: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 14498: scanf("%s",z);
14499: }
1.283 brouard 14500: printf("End\n");
1.282 brouard 14501: exit(0);
1.126 brouard 14502: }
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